Discourses on Business Education at the College Level: On the Boundaries of Content and Praxis 9781644691205

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DISCOURSES ON BUSINESS EDUCATION AT THE COLLEGE LEVEL On the Boundaries of Content and Praxis

Touro University Press Books

Series Editors Michael A. Shmidman, PhD (Touro College, New York) Simcha Fishbane, PhD (Touro College, New York)

DISCOURSES ON BUSINESS EDUCATION AT THE COLLEGE LEVEL On the Boundaries of Content and Praxis Edited by Sabra E. Brock and Peter J. McAliney

New-York 2019

Library of Congress Control Number:2019942885

ISBN 978-1-64469-119-9 (hardback) ISBN 978-1-64469-120-5 (electronic, PDF) ISBN 978-1-64469-121-2 (electronic, epub) Book design by PHi Business Solutions Ltd. ©Touro University Press, 2019 Published by Touro University Press and Academic Studies Press. Typeset, printed and distributed by Academic Studies Press. Touro University Press Michael A. Shmidman and Simcha Fishbane, Editors 320 West 31st Street, Fourth Floor, New York, NY 10001, USA [email protected] Academic Studies Press 1577 Beacon Street Brookline, MA 02446, USA [email protected] www.academicstudiespress.com

To Professors Bridget O’Connor, PhD and Michael Bronner, PhD for their contribution to the field of Business Education and for creating a passion in the field for those of us following in their footsteps. We want to thank Dr. Alan Kadish and the Touro College community for their generous support of this project.

Table of Contents

Forewordix Bridget N. O’Connor 1. Challenges and Opportunities for Teaching and Learning in the First Accounting Course Ellen Bartley 2. The Role of Community Colleges in Promoting Financial Literacy: A Proposed Model  William L. Black 3. The Toolbox—an Innovation Connecting Marketing Education and Practice Kevin E. McEvoy 4. Women’s Journeys to the C-Suite and the Emotional Component of Success Sabra E. Brock, Sharon Rowlands 5. Developing Information Technology Fluency in College Students: An Investigation of Learning Environments and Learner Characteristics Nancy B. Sardone 6. Toward More Practical Measurement of Teamwork Skills Sabra E. Brock, Peter J. McAliney, Chunhui Ma 7. The Impact of Group Support Systems on Corporate Teams’ Stages of Development Margaretta J. Caouette, Bridget N. O’Connor 8. Cultural Transition and Adjustment of International East Asian Undergraduate Students Daniel Kerr, Tara Madden-Dent

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  9. Game-Based Learning to Raise Awareness of Nuclear Proliferation148 Nancy B. Sardone 10. Virtual Workplace Learning: Promises Met? 162 Robert G. Brookshire, Lynn B. Keane, Kara Lybarger 11. The Care and Feeding of Interns: A Framework for Maximizing Intern Learning and Productivity 179 Kevin E. McEvoy 12. Understanding MBA Students’ Intention to Transfer to Teamwork Skills: A Theory-Based Model 200 Chunhui Ma 13. Learning: The Experiences of Adults Who Work Full-time while Attending Graduate School Part-time 223 Bridget N. O’Connor, Robert Cordova 14. Identifying and Classifying Corporate Universities in the United States 249 Amy Lui Abel 15. Business School Extended Learning: Perspectives on Non-Degree Executive Education—The Case of “Looking Good” versus “Being Good” 269 Steven S. Mezzio Closing Thoughts: Sustainability 297 Sabra Brock Peter J. McAliney Authors’ Biographies 301 Index307 

Foreword BRIDGET N. O’CONNOR, PhD New York University

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his collection represents a sampling of articles written by a cross-section of PhD graduates from the NYU Business Education program. Most, but not all, are focused on issues related to learning and teaching business subjects at the college level. This group of practitioner scholars has made education for, about, and in business their life’s mission and each has made significant contributions to the profession. Established in 1926, the Business Education Department offered the first curriculum designed to train teachers of business subjects at the secondary level. Years later, as demand for secondary business teachers faded, the Program in Business Education under the leadership of Professors Michael Bronner and Padmakar Sapre expanded the mission to include training professors of business education in community colleges and higher education institutions. In 1984, when I joined the program, we began to incorporate the role of end-user information systems and increasingly focused on learning in business, or organizational learning and development. As my colleagues retired, the doctoral program was folded into the Program in Higher and Postsecondary Education, and the master’s program continued to emphasize organizational learning and development.1 This book is divided into two sections. Section I covers a range of topics related to learning content in business education at the college level: • Ellen Bartley’s “Challenges and Opportunities for Teaching and Learning in the First Accounting Course” determines the important elements

1 For a more complete history of the program, visit “MA in Business and Workplace Education,” accessed December 20, 2018, https://steinhardt.nyu.edu/alt/highered/business/ma.

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of the learning process such as homework, interim deadlines, and inclass reviews that contribute to the students’ academic success. However, she also mentions that some students find the course load lighter than the others, especially if they had previous work experience in the field. In “The Role of Community Colleges in Promoting Financial Literacy,” William L. Black proposes a model for promoting financial literacy for community college students. Kevin McEvoy, in “The Toolbox—an Innovation Connecting Marketing Education and Practice,” suggests that creating a personal library or portfolio of their work and other resources can help marketing students maintain their access to education as evidence of their achievements and as a database of business solutions to be used later in their jobs. Sabra E. Brock and Sharon Rowlands, in “Emotional Journeys of Fifty C-Suite Women,” stress the importance of building confidence in girls and young women and communicating the positive aspects of being a leader. Many C-Suite Women recognized their leadership abilities already in their teenage years. In “Developing Information Technology Fluency in College Students,” Nancy B. Sardone did not find elements of learning environment that could influence the students’ proficiency in information technologies. However, her research showed that students’ wellbeing and their learning efficiency increase when various constructivist learning strategies are employed. Sabra Brock, Chunhui Ma, and Peter McAliney stress the necessity to update the way team skills are measured to reflect the data about successful team presented in their article “Toward More Practical Measurement of Team Skills.” In “The Impact of Group Support Systems on Corporate Teams’ Stages of Development,” Margretta J. ( Judy) Caouette and I note that the two teams we studied developed quite differently, especially in Tuckman’s “storming” stage. Moderating factors were team commitment to the assigned task, group composition, and leadership. Daniel Kerr and Tara Madden-Dent, in “Cultural Transition and Adjustment of International East Asian Undergraduate Students,” observed the benefits of studies in the United States for East Asian undergraduates of a four-week pre-departure cross-cultural treatment.

Foreword

Section II provides strategies and practical solutions for acquiring competencies: • Nancy B. Sardone, in “Game-Based Learning to Raise Awareness of Nuclear Proliferation,” demonstrates that digital games encourage students’ curiosity and motivate them towards learning more than just the headlines. • Lynn Bacon, Robert Brookshire, and Kara Lybarger admit the benefits of virtual workplace learning in “Virtual Learning: Promises Met?” and determine vital success factors such as the presence of a vibrant virtual community, a flexible learning system with high-quality content and technology infrastructure, employees and trainers skilled in virtual learning, and the combination of virtual learning with face-to-face academic guidance. • In “Understanding MBA Students’ Intention to Transfer Teamwork Skills,” Chunhui Ma proposes a theory-based model to expand understanding such transfers. • Kevin McEvoy in “The Care and Feeding of Interns” presents a framework that organizations and universities can use to manage interns better. • In “Learning: The Experiences of Adults who Work Full-Time While Attending Graduate School Part-Time,” Robert Cordova and I stress the importance of education in helping learners explore what it means to be themselves. • Amy Lui Abel, in “Identifying and Classifying Corporate Universities in the United States,” presents a definition of a corporate university and describes the development of this phenomenon. • In “Business School Extended Learning: Perspectives on Non-Degree Executive Education,” Steve Mezzio compares business school rankings to the implementation of quality management in curriculum development. The genesis of this book came from PhD graduates Sabra Brock (Touro College) and Peter McAliney (Montclair State University), who saw a need to put a stamp on the contributions of our graduates. I thank them for their dedication to our Program and to New York University. The authors featured here are primarily doctoral graduates whose dissertation research was supervised either by me or by Professor Michael Bronner. We are proud of the work these scholars did, and continue to do! We also believe that you will be inspired by their work.

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CHAPTER 1

Challenges and Opportunities for Teaching and Learning in the First Accounting Course ELLEN BARTLEY, PhD CMA Farmingdale State College

ABSTRACT

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urpose—Business degrees continue to attract the highest amounts of undergraduate and master level students (McFarland et al., 2017). For most students enrolled in these programs, introductory accounting is a required course. However, students frequently feel anxiety and confusion about the course content and outcomes. Prior studies have shown that students’ preconceptions of the accounting profession are that accounting is a boring field limited to quantitative analysis, and that accountants typically work alone (Albrecht and Sack, 2001; Coate, Mitschow, and Schinski, 2003; Bartley, 2016). Several studies reported that a large percentage of introductory accounting students enter the course expecting to earn a C or a D in the course (Elias, 2005; Rao and Higgins, 1999). Student confidence in the course has also been examined, and in a study of more than 300 business students, only 18% reported high or very high confidence with their performance on introductory accounting exams (Malgwi, 2006). A survey of students’ learning intentions revealed that students

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merely want to pass the introductory accounting course, satisfy a requirement, and move on, rather than to engage and learn the material (Lucas and Meyer, 2004, 2005). Little has previously been done to examine the students’ perspectives about this long-standing situation. In a gateway course that can provide much grounding for further undergraduate and graduate study, understanding the student experience will be critical to improving the course experience, and ultimately outcomes for the students. Design/methodology/approach—This qualitative case study elicited insights from a small group of students before, during, and upon completion of their introductory accounting course by using in-depth field interviews. The first interview focused on the participants’ inputs, attitudes, and perceptions that they held at the onset of the course. In the second interview, held midway through the semester, the participants shared the strategies that they used to learn the material and identified additional opportunities and/or challenges that they had encountered in the class. The final interview, held upon receipt of participants’ final grades, was about how they viewed their experience in light of the course outcomes. Seven students volunteered to participate in the study, three accounting majors and four non-majors. Six of the seven students completed all three interviews. Interview data were transcribed, coded, analyzed, and presented in a case study. Findings—Consistent with existing studies, at the beginning of the course, many of the participants reported stereotypical views of accountants as number-crunchers, had heard that the course was difficult, and were concerned about the level of difficulty. Results strongly indicated that homework preparation with subsequent review in class was the most important way that students learned accounting material. Thematic analysis identified additional themes, including: (1) accounting just clicks for some students, but others have to work hard at it; (2) weekly quizzes created a lot of stress; (3) the lack of prior experience with accounting made the course very challenging; (4) time management is challenging, but interim deadlines for a project were helpful; and (5) some students regretted not asking for tutoring help that was available. In terms of learning outcomes, the participants disclosed their grades and reflected on what the experience meant for them. The course helped some participants decide whether or not they wanted to continue in accounting. The participants unanimously concluded that while the course was challenging, they learned a lot. Some reported lower grades than they initially expected, but were satisfied because of the level of difficulty of the course (Bartley, 2016).

Challenges and Opportunities for Teaching and Learning

Originality/value—This study contributes to the current interest in assessing student learning outcomes. Introductory accounting courses are often a requirement for continued study in both undergraduate and graduate business programs. By better understanding the students’ attitudes and experiences, educators can create learning environments that will give students better opportunities to meet the learning goals for the course. The results of this study extend beyond the introductory accounting course. Introductory courses often provide a student with his or her first exposure to a particular discipline. The current emphasis on outcomes often dictates the material to be covered, but may fail to adequately address the student learning process, particularly in these early courses. “As educators, we sometimes fall prey to the fallacy of equating our covering [emphasis added] material with students learning [emphasis added] the material” (Pincus, 1997, p. 576). Examining the students’ engagement in their learning, or reasons for lack of engagement, within the context of the introductory course may provide additional insights into the challenges that novice learners face in other disciplines as well.

LITERATURE REVIEW This study used a cognitive science framework which describes learning as an input-process-output model (Biggs, 1989, in Duff and McKinstry, 2007; Bryant and Hunton, 2000). The process portion of Biggs’s cognitive learning model was expanded by examining learning and teaching processes separately (U. Lucas, 2002). Both the literature review and the interview structure for my study mirror Biggs’s model. In this study, the term “Student Expectations” was used to capture the various student inputs at the beginning of the course. Consistent with Lucas, teaching and learning were separated into two processes: the Teaching Environment and Student Learning Experiences. Outcomes are identified as Student Learning Outcomes.

Student Expectations A number of things are very clear about the student population in introductory accounting courses. Accounting majors often have certain character traits in common, such as their preference for organization. Yet, the majority of students enrolled in the introductory courses is comprised by non-majors, who do not share these personal preferences to the same degree (Kovar, Ott, and Fisher, 2003; Laribee, 1994; Lawrence and Taylor, 2000). The introductory

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accounting course may be a student’s first exposure to the discipline. Prior knowledge, or lack thereof, may affect how students learn in this course. Prior knowledge has been shown to ensure that less effort being required for the course, with no significant differences in performance, suggesting efficient learning (Halabi, Tuovinen, and Farley, 2005). Yet introductory courses, by their very nature, are often populated by students who have little or no prior experience in the subject. Moreover, students often enter the introductory course with strong negative preconceptions about accounting, find the quantitative nature of accounting course intimidating, and often have strong negative performance expectations (Albrecht and Sack, 2001; Allen, 2004; Coate, Mitschow, and Schinski, 2003; Lucas and Meyer, 2004, 2005). Students are motivated, or not, to learn for a variety of reasons, and these reasons may foster or deter students’ effort and performance in the course (Allen, 2004; Turner, Lesseig and Fulmer, 2006).

The Teaching Environment While the emphasis of this study was on student learning experiences, those experiences are often shaped by the learning environment and the course instructor. Prior studies have shown that the relevant field experience of their accounting professors was important to both accounting majors and nonaccounting majors. Cross (2005) surveyed over 2800 instructors about their teaching goals. Career preparation, teaching facts and principles, and promoting higher-order thinking skills were their primary teaching objectives. This may be especially relevant in understanding student experiences in introductory accounting. The learning objectives of a student who is not preparing for a career in accounting may not be aligned with the instructor’s primary teaching goal(s). Traditionally, accounting instructors have relied heavily on instructor-centered strategies to deliver course content, emphasizing rules and regulations (Boyd, Boyd, and Boyd, 2000). Accounting majors are more likely to prefer these instructor-centered strategies than non-accounting majors (Ulrich, 2005).

Students’ Learning Experiences The examination of learning from the students’ perspective is the least explored part of the cognitive learning model, with respect to accounting education. The research of student approaches to learning in accounting has so far identified deep and surface approaches (Duff and McKinstry, 2007; U. Lucas, 2004; Lu-

Challenges and Opportunities for Teaching and Learning

cas and Meyer, 2004, 2005) and learning strategies as two elements in the learning process. Students who take a deep approach to learning are more likely to make connections to prior knowledge and experiences and demonstrate a desire to assimilate the material (Mezirow, 2000). In a study of 480 introductory accounting students, taught by eight instructors at two universities, researchers found significant positive correlations between a deep approach to learning, expected course grade, and grade point average. Accounting majors and non-business majors tended to use the deep approach more than non-accounting business majors. For accounting students, enjoyment and relevance were linked with deep learning. For non-accounting students, only relevance was linked with deep learning experiences (Elias, 2005).

Student Outcomes Learning outcomes in accounting have traditionally measured learning by using grades on a particular project, assignment, exam, or in the current or subsequent accounting course. Learning outcomes have also been assessed by looking at outcomes after various teaching strategies have been utilized (reviewed in Watson et. al., 2003). Such measurements underscore the teaching paradigm. Perhaps other performance measures could more fully explain student performance in introductory courses. The use of expected grades may provide an additional opportunity for instructors to gather feedback during the course, rather than waiting until the end of the term. In a study of 2200 student evaluations submitted by students enrolled in business classes at a Midwestern university, the researcher found that expected grades correlated with perceived learning (Marks, 2000). When students perceive that they are learning, they expect to do well in the course.

RESEARCH QUESTIONS The overarching research question that guided this study was: “How do students describe their learning experiences in the introductory accounting course?” This was addressed by breaking down the research question into subquestions that mirrored the cognitive learning model. The subquestions were the following. (1) How do students describe their expectations as they enter the introductory accounting course? (2) How do students describe their learning experiences during the course? (3) What specific learning strategies do students use during the course? (4) What other challenges and/or opportunities

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do students face in their learning? (5) How do students describe their learning outcomes in this course?

QUALITATIVE CASE STUDY METHOD Quantitative methods have often been used to gather information about student inputs and outputs in accounting education (Adler, Milne, and Stablein, 2001; Coate, Mitschow, and Schinski, 2003; Debevec, Shih, and Kashyap, 2006; Halabi, Tuovinen, and Farley, 2005; Hanson and Philips, 2006; Huang, O’Shaughnessy, and Wagner, 2005; Hwang, Lui, and Tong, 2005; Malgwi, 2006; Philips and Vaidyanathan, 2004). More recently, researchers in the United Kingdom have included qualitative approaches in their examination of student learning experiences in introductory accounting (Brown, 2005; Lucas and Meyer, 2004, 2005). The introduction of qualitative methods can add more details to our understanding the students’ experience as the students describe it. Since little is known about how students approach their learning in the introductory accounting course, the research questions that guide this study will be explored by using qualitative inquiry to identify how students respond to learning in introductory accounting. Qualitative inquiry is a particularly appropriate way to investigate areas that have not yet been fully examined. In accounting education, learning as seen from the student perspective is one such area, particularly with regard to specific learning strategies that students employ and any other factors that support or challenge students in their learning. While interpretive inquiry can take many forms, Creswell (2007) identifies five types of qualitative inquiry: narrative, phenomenology, grounded theory, ethnography, and case study. The research questions guiding this study were examined using a case study approach to capture the experiences of students in full as they described their learning within the context of their introductory accounting course. Case study is particularly appropriate when the “the inquirer has clearly identifiable cases with boundaries and seeks to provide an in-depth understanding of the cases or a comparison of several cases” (Creswell, 2007, p. 74). Since research clearly indicates that student attitudes toward accounting are overwhelmingly negative, and that the majority of students expect to do poorly in the course, student learning experiences must be examined within the context of a particular course. Further, examining the learning experiences of a small group of learners in a particular environment and discipline that is relevant to the educator is not

Challenges and Opportunities for Teaching and Learning

only a worthwhile endeavor, but really a necessary one. Classroom research and assessment challenge educators to continually review and reinvent the courses they teach. Looking carefully at how even one student learns is often quite revealing. Most of us have an opportunity to observe a wide variety of learners in the act of learning. Moreover, the students that we observe are our students in the process of learning our discipline; they are the most relevant sample of learners that we could imagine (Cross, 1998). This case study was conducted at a small, suburban, four-year liberal arts college in the northeast. Student participants were enrolled in an introductory accounting course during the semester when they participated in the study. Four sections of the course were offered during the semester of the study, with individual class sizes for day sections of approximately twenty-five students and slightly smaller evening sections. Accounting majors and non-accounting majors took the same first course in accounting. Creswell (2007) recommends four or five case studies within a single study. Eight participants were sought, to allow for the possibility that not all participants would complete the study. There are many sampling strategies that may be used in selecting participants for qualitative studies. Sampling for maximum variation within the case is common (Creswell, 2007) to allow both variations and commonalities to surface. For purposes of this study, variation was identified by major (accounting majors and non-accounting majors). As students in many programs other than accounting are required to take an introductory accounting course, participants were sought from among both accounting majors and non-accounting majors in order to capture any variations that might be expressed. The student participants in this study all attended the same suburban, private college. Students attending community colleges, enrolled in colleges and universities in different locations, or taking the class in an online environment may report substantially different introductory accounting experiences. Students self-reported their interim and final grades, as well as completion of homework assignments and projects. To maintain the confidentiality of their participation, these self-reports were not confirmed with the instructor. The participants were selected from courses taught by each of two instructors, and included day and evening students, as well as college students of traditional age and adults returning to school. Students enrolled in the day class met twice per week for one and one-half hours and those enrolled in the evening section met once per week for three hours. None of the participants had ever taken an accounting course prior

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to this semester. All but one of the participants were undergraduate students. One student was pursuing an MBA in accounting. She had no prior accounting courses, and therefore had to take all of the undergraduate accounting courses that accounting majors take. “Table 1, The Participants at a Glance” presents the descriptive characteristics for the seven participants who began the study and illustrates the areas of diversity among the participants. Table 1.  The participants at a glance Name Year in college

FT/PT1 Major/Program Status Accounting, Alice Freshman FT College Honors Program Joe Freshman FT Accounting Vivian Freshman FT Business Administration Ben Junior FT Political Science and Economics majors/minor in Business Kurt Junior FT Mathematics, College Honors Program Charlie Adult PT Organizational Management Isabel Adult PT MBA in Accounting

GPA

Ethnicity Day or Instructor evening

3.8

Caucasian Evening Profitera

3.4 Caucasian Day “did not Caucasian Day do well” Day 3.0 AfricanAmerican

Cash Cash

3.8

Caucasian Day

Profitera

3.9

Caucasian Evening Profitera

3.4

Caucasian Evening Profitera

Profitera

The primary means of gathering data was through a series of three in-depth field interviews with each participant; each interview lasted approximately thirty minutes. Six of the seven participants completed all three interviews; one participant completed only the first two interviews. During the interviews, participants were asked to fully describe their learning experiences as they were unfolding. In each of the interviews, students were asked about one aspect of their course experience, as it aligned with the cognitive learning model, that is, learning as an input-process-outcome. For purposes of this study, the inputs were identified as Student Expectations, the process, consistent with Lucas (2002) was identified as two processes, the Teaching Environment, and Student Learning Experiences, and outcomes were identified as Student Learning

1 Full-time/Part-time

Challenges and Opportunities for Teaching and Learning

Outcomes. Though participants were not limited to any one aspect of the course in their responses during any of the three interviews, the research questions were structured in a way that would follow the flow of the course and the cognitive learning model previously described. The first interview took place as early in the semester as the participants’ schedules permitted in order to capture the students’ initial expectations for the course. The questions in the second interview focused on the course process: what were students doing to learn the material? The final interview was scheduled after the semester ended. The purpose of this final interview was to identify the participant’s actual performance, capture his or her reaction to the grade and interpretation of the grade in light of his or her expectations at the beginning of the course and experiences during the course. Although the final interview began with the prompt, “Tell me how your accounting course went,” in responding, all of the participants began by sharing their grades in the course. Many of the participants revisited a number of the things that they shared in the second interview. Some discussed changes in their own attitude toward the course, the level of difficulty of the course, and/or changes in strategies that they used to cope with the course. The purpose of this final interview was to identify the participant’s actual performance, capture his or her reaction to the grade and interpretation of the grade in light of his or her expectations at the beginning of the course and experiences during the course. The interview questions are included in Appendix A. Appropriate Institutional Review Board (IRB) approval was received from both the researcher’s institution and the research site. Data analysis generally falls into three categories: preparing and organizing the data, reducing the data into themes by coding, and presenting the results (Creswell, 2007, p. 148). For this study, the primary data consisted of three transcribed interviews for each participant, with the exception of one participant who did not respond to multiple attempts to schedule a third interview. With the permission of the participants, all interviews were recorded. The interview recordings were then transcribed and coded, and the codes developed into themes. Member checking was performed to make certain that the transcripts reflected what the student conveyed during the interviews. The coding of the transcripts was an iterative process. The initial round of coding resulted in more than two hundred codes. Similar codes were combined to result in thirty primary codes. These codes are presented in Appendix B. Stake (2005) indicates that a case study is “both a process of inquiry about the case and the product of that inquiry” (p. 444). Case study analysis may use

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both categorical aggregation and direct interpretation of the data (Stake, 1995). By directly interpreting individual cases within the study, the researcher can identify those insights unique to an individual participant. By aggregating data from the multiple cases within the study, the researcher may be able to identify commonalities. I used both techniques in analyzing the interview transcripts so that I could analyze the responses of each participant individually as well as compare responses across cases. These analyses reflect the similarities and differences in the students’ experiences in their first accounting course. Appendix C provides a list of the themes and corresponding primary codes.

RESULTS The various themes were organized as they related to each of the research questions. The results are presented here and included in tabular form in Appendix D. Research question 1: How do students describe their expectations as they enter the introductory accounting course? Three themes emerged from this research question. They are: (1) “I chose accounting because I like math/numbers and because of job opportunities; I have to decide if it is a good match for me,” (2) “I chose a business major (minor) based on job opportunities. Although I know that I need accounting, I’m not really looking forward to it,” and (3) “I didn’t really know what to expect, but based on what I do know, I’m a little bit nervous about it.” These results were consistent with existing literature about how students enter the course. The accounting majors entered the course slightly more informed about what accounting is than their non-major peers. All participants expressed some concerns about the workload and level of difficulty. Research question 2: How do students describe their learning experiences during the course? In response to this question, the theme that emerged was, “For some students, accounting ‘just clicks,’ the rest have to work really hard to learn this.” Most of the participants commented about their classmates and classroom experience in discussing their course experiences. They were aware of who was doing well and who had troubles with understanding the material. This reinforced their belief that some people “just get it” while the rest struggled. The participants concluded this by observing their own and their classmates’ body language, attendance rates, and engagement in classroom problem solving. Research question 3: What specific learning strategies do students use during the course?

Challenges and Opportunities for Teaching and Learning

When asked about specific learning strategies that they used, all of the participants mentioned the preparation of homework, with its subsequent review in class, as the most important factor that helped them to learn the material. All of the participants noted that course homework took a considerable amount of time each week, but that it was important to their grade and their understanding of accounting. Several participants noted that homework was the time where they could determine for themselves whether or not they understood the material. Research question 4: What other challenges or opportunities do students face in their learning? This question evoked a variety of responses that addressed circumstances inside and outside of the course. One of the instructors for the course gave a weekly quiz. The participants in those sections reported that the quizzes, although a small part of their grade, were extremely stressful. While none of the participants in this study had taken an accounting course prior to the semester of the study, several observed that classmates who had taken accounting in high school were finding their college course to be much easier and performed better than those who were experiencing accounting for the first time. Novice learners may find the first course difficult because of the lack of experience in the subject. The research site offered tutoring services, at no charge to the students. Several of the participants acknowledged that they should have taken advantage of the help offered, but had neglected to do so. For many of the participants, time management was always a challenge. As noted, the homework took a considerable amount of time each week. Additionally, both instructors assigned a comprehensive financial statement project. One of the instructors created the interim deadlines for this project. Participants in the sections taught by this instructor reported that the interim deadlines were extremely useful in helping them manage their time and complete the project without the stress that they normally encounter with a term project. Research question 5: How do students describe their learning outcomes in this course? While all participants initially cited their grades as an indication of how the course went, they did provide some reflection on those grades. Some participants reported being satisfied with their grade, even though it is lower than they might have hoped. The participants all concurred that is was a challenging course, but that they did learn a lot. For some of the participants, the course

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helped to confirm that accounting was a good fit, while for others, the course helped to see that accounting was not a good fit.

CONCLUSIONS AND RECOMMENDATIONS Little prior research had investigated the students’ perspectives on a course that has long been seen by students as difficult, boring, and irrelevant, and has consistently resulted in poor performance and high dropout rates. Most business programs require accounting as a foundational course. Given its reputation, it seems that some attention should be paid to what students experience, and that instructors should work to make the course more meaningful for the learners. This qualitative case study followed the participants as they navigated their first accounting course and captured their experiences. The results should be of interest not only to those who teach accounting, but to those who teach mandatory introductory courses in other disciplines as well. This study resulted in several recommendations for instructors’ actions and for additional research. The first suggestion for actions is at an institutional level, the other two are specific to the first accounting course.

Recommendations for Actions In a time when retention is a critical issue for many institutions, helping students to make a wise selection in their course of study could be the key. Consistent with the Cooperative Institutional Research Program (CIRP) Freshmen Survey (Eagan et. al., 2014) on the profile of the 2014 freshmen; participants in this study linked their decision to attend college with the desire to improve their career opportunities. One of the participants in this study chose accounting with little knowledge of what it was like. He assumed that it was about numbers and simple math and that he could get a respectable job. His experience in the course showed him that this was a very simplistic view of accounting; he ultimately opted out of majoring in accounting. Providing students with the opportunity to explore such programs could help with retention rates and improve the quality of life for the students who choose a path more aligned with their own personalities, skill sets, and goals. There is an opportunity here to help students make wiser choices much earlier in the process. In high school, or as part on an ongoing first-year orientation, all students should be encouraged to explore various majors available. Students should discover what they would learn in each major, and what advanced study, if any, would be required to pursue the careers

Challenges and Opportunities for Teaching and Learning

in each field. Particularly in times when tuition-dependent institutions are concerned about retention rates, connecting students to an area of study that best matches their own long-term interests may help the student to persist toward degree attainment in a timely manner. The second recommendation is for instructors to get to know their students every semester, and as early in the semester as possible by creating a “getting to know you” assignment at the beginning of the course. There is a wide variety of ways to accomplish this in small or large classes. Instructors in small classes could use an essay or a series of open-ended questions; instructors in large classes could use an online survey tool to gather the same information. The following information might be helpful to the instructor: the student’s major; why they chose it; why they are taking accounting this semester; how they feel about taking the course; and what concerns, if any, they have about taking the course. Having a more comprehensive understanding of the composition of the students in the course or section should help the instructor to craft a more supportive learning environment. This would need to be undertaken each semester, as the composition of each section will vary from semester to semester. The third recommendation for actions is that instructors spend some time at the beginning of the semester helping students “learn how to learn” in accounting. Such a discussion should also include suggestions for time management: many new college students report time management to be one of their greatest challenges. Sometimes instructors take for granted that students would intuitively know how to study by the time they get to college. The strategies that work best in accounting may not be the same strategies that have worked for the student in the past or will work in every other discipline. Several participants reported that they do not generally read their textbooks, but for this course they found it necessary to go back and review a topic in the text after it was covered in class. In the introductory accounting course, instructors could take some class time to introduce the students to the structure of their textbooks and the principles of using it effectively, such as reading the learning objectives and summary first to see broadly what they will be learning about; then reading each section one at a time, allowing more time to read a technical text than they may be accustomed to. Reading guides may help students focus on the key components of each section. Instructors might better support students in their learning if these issues were discussed at the beginning of the semester. One of the participants said that each semester he tries to “get in the mindset of ” the discipline early in the course. Instructors may be in the best position to guide students in doing this. In reviewing homework in class, instructors

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should point out how to approach the problem and think through the problem aloud with the students. The participants’ reactions to course components such as homework and exams suggests that students may benefit from “learning how to learn” in accounting.

Recommendations for Further Research in Accounting Education While pedagogy has become much more student-centered in recent years, the focus in accounting education still largely remains on content. Still more needs to be done to understand the students’ experiences in the course. Exactly how do students go about learning the material? This study identified the importance of homework and class attendance. All of the participants reported that they consistently went to class and prepared their homework. These results were self-reported and were not confirmed with the instructor in order to maintain the confidentiality of the participants. However, the participants spoke about the importance of homework in a way that suggested that they saw homework as a very valuable learning tool. Further research should investigate the types of homework assignments given in the introductory accounting courses, and could correlate homework performance and attendance with course performance and see what types of homework assignments seem to be the most helpful. While the participants in this study all reported an intent to work hard in order to earn a good grade in this course, the literature has clearly shown that many students enter the course expecting to perform poorly. Two of the participants struggled from early on in the course; they might have improved their performance by making use of available resources, such as free tutoring, yet neither did. Further investigation could examine what resources are available to students to support their learning, to what extent students take advantage of them, and why students do not take advantage of them when they struggle. Perhaps in a study that provided students with anonymity, they would be more forthcoming in discussing why they did not seek help. Further investigation could also examine whether or not interest in accounting would be a good indicator of student success. The range of interest in accounting was demonstrated by the participants’ own words: “It’s okay” ( Joe), “I wish I found out about it earlier” (Kurt), and “I just love it!” (Isabel). Joe saw his performance in the course as successful, but did not find it interesting and did not continue in the major. Kurt was successful in the course, but did not have the space left in his remaining semesters to pursue further study in

Challenges and Opportunities for Teaching and Learning

accounting. Changing majors and delaying graduation was not a financial possibility for him. For Isabel, her loving the subject confirmed that she had made the right choice to return to school for an MBA in Accounting. Encouraging students to be mindful of their attitudes toward a subject could help a student select a field of study that best matches his/her interests.

REFERENCES Adler, R. W., Milne, M. J., and Stablein, R. (2001). Situated motivation: An empirical test in an accounting course. Canadian Journal of Administrative Sciences, 18 (2), 101–115. Albrecht, W. S., and Sack, R. J. (2001). The perilous future of accounting education. The CPA Journal, 71 (3), 16–23. Allen, C. L. (2004). Business students’ perception of the image of accounting. Managerial Auditing Journal, 19 (2), 235–258. Bartley, E. D. (2016). Decoding the Blackbox of Students Learnings: Case Studies from the Introductory Accounting Course. PhD dissertation, Ann Arbor, MI. Boyd, D. T., Boyd, S. C., and Boyd, W. L. (2000). Changes in accounting education: Improving principles content for better understanding. Journal of Education for Business, 76 (1), 36–42. Brown, N. (2005). Meta programs for identifying thinking preferences and their impact on accounting students’ educational experience. Journal of Accounting Education, 23, 232–247. Bryant, S. M., and Hunton, J. E. (2000). The use of technology in the delivery of instruction: implications for accounting educators and education researchers. Issues in Accounting Education, 15 (1), 129–162. Coate, C. J., Mitschow, M. C., and Schinski, M. D. (2003). What students think of CPAs: Is the stereotype alive and well? The CPA Journal, 73 (8), 52–55. Creswell, J. W. (2007). Qualitative inquiry and research design: choosing among five approaches. Thousand Oaks, CA: Sage Publications. Cross, K. P. (1998). Classroom research: implementing the scholarship of teaching. New Directions for Teaching and Learning 75, 5–12. Cross, K. P. (2005). On college teaching. Research and Occasional Paper Series: CSHE, 15.05. Berkeley, CA: Center for Studies in Higher Education. University of California. Debevec, K., Shih, M., and Kashyap, V. (2006). Learning strategies and performance in a technology integrated classroom. Journal of Research on Technology in Education, 38 (3), 293–307. Duff, A., and McKinstry, S. (2007). Students’ approaches to learning. Issues in Accounting Education, 22 (2), 183–214. Eagan, K., Stolzenberg, E. B., Ramirez, J. J., Aragon, M. C., Suchard, M. R., and Hurtado, S. (2014). The American freshman: National norms fall 2014. Los Angeles, CA: Higher Education Research Institute, UCLA. Elias, R. Z. (2005). Students’ approach to study in introductory accounting courses. Journal of Education for Business, 80 (4), 194–199.

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Ellen Bartley Halabi, A. K., Tuovinen, J. E., and Farley, A. A. (2005). Empirical evidence on the relative efficiency of worked examples versus problem-solving exercises in accounting principles instruction. Issues in Accounting Education, 20 (1), 21–32. Hanson, E., and Phillips, F. (2006). Teaching financial accounting with analogies: Improving initial comprehension and enhancing subsequent learning. Issues in Accounting Education, 21 (1), 1–14. Huang, J., O’Shaughnessy, J., and Wagner, R. (2005). Prerequisite change and its effect on intermediate accounting performance. Journal of Education for Business, 80 (5), 283–288. Kena, G., Musu-Gillette, L., Robinson, J., Wang, X., Rathbun, A., Zhang, J., Wilkinson-Flicker, S., Barmer, A., and Dunlop Velez, E. (2015). The Condition of Education 2015 (NCES 2015– 144). Washington, D.C.: US Department of Education, National Center for Education Statistics. Retrieved August 26, 2015 from http://nces.ed.gov/pubsearch. Kovar, S. E., Ott, R. L., and Fisher, D. G. (2003). Personality preferences of accounting students: a longitudinal case study. Journal of Accounting Education, 21, 75–94. Laribee, S. F. (1994). The psychological types of college accounting students. Journal of Psychological Type, 28, 37–42. Lawrence, R., and Taylor, L. W. (2000). Student personality type versus grading procedures in intermediate accounting courses. Journal of Education for Business, 76 (1), 28–35. Lucas, U. (2002). Contradictions and uncertainties: lecturers’ conceptions of teaching introductory accounting. British Accounting Review, 34, 183–203. Lucas, U., and Meyer, J. H. F. (2004). Supporting student awareness: understanding student preconceptions of their subject matter within introductory courses. Innovations in Education and Teaching International, 41 (4), 459–471. Lucas, U., and Meyer, J. H. F. (2005). ‘Towards a mapping of the student world’: the identification of variation in students’ conceptions of, and motivations to learn, introductory accounting. The British Accounting Review, 37, 177–204. Malgwi, C. A. (2006). Discerning accounting and nonaccounting students’ perceptions in the first course in accounting as a proxy for separate course delivery. Global Perspectives on Accounting Education, 3, 67–91. Marks, R. B. (2000). Determinants of student evaluations of global measures of instructor and course value. Journal of Marketing Education, 22 (2), 108–119. McFarland, J., Hussar, B., de Brey, C., Snyder, T., Wang, X., Wilkinson-Flicker, S., Gebrekristos, S., Zhang, J., Rathbun, A., Barmer, A., Bullock Mann, F., and Hinz, S. (2017). The Condition of Education 2017 (NCES 2017–144). Washington, D.C.: US Department of Education, National Center for Education Statistics, Retrieved January 26, 2018 from https://nces.ed.gov/ pubsearch/pubsinfo.asp?pubid=2017144. Mezirow, J., and associates. (2000). Learning as transformation. Jossey-Bass, San Francisco. Phillips, F., and Vaidyanathan, G. (2004). Should case materials precede or follow lectures? Issues in Accounting Education, 19 (3), 305–319. Pincus, K. V. (1997). Is teaching debits and credits essential in elementary accounting? Issues in Accounting Education, 12 (2), 575–579.

Challenges and Opportunities for Teaching and Learning Pritchard, R. E., Potter, G. C., and Saccucci, M. S. (2004). The selection of a business major: Elements influencing student choice and implications for outcomes assessment. Journal of Education for Business, 79 (3), 152–156. Rao, A., and Higgins, L. (1999). First course in accounting from the user’s perspective: A case study of the use of a financial statement analysis project utilizing internet research. Journal of Accounting and Finance Research, 7 (2), 29–43. Stake, R.E. (2005). Qualitative case studies. In N. K. Denzin and Y. S. Lincoln (eds.), The Sage handbook of qualitative research (3rd ed.). Thousand Oaks, CA: Sage Publications. Turner, K. G., Lesseig, V. P., and Fulmer, J. G. (2006). Motivation in the first accounting course. The CPA Journal, 76 (5), 66–69. Ulrich, T. A. (2005). The relationship of business major to pedagogical strategies. Journal of Education for Business, 80 (5), 269–274. Watson, S. F., Apostolou, B., Hassell, J. M., and Webber, S. A. (2003). Accounting education literature review (2000–2002). Journal of Accounting Education, 21 (2003), 267–325.

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APPENDIX A: INTERVIEW PROTOCOLS Interview Protocol: Initial Participant Interview Can you tell me how you feel about taking accounting this semester? What are your expectations for the course? How you think you will perform in the course? Why do you think this? Have you ever taken accounting before? If so, what was your experience? Can you describe your impression of accounting or the accounting profession? Do you have any concerns about taking this course?

Interview Protocol: Second Participant Interview How is your accounting course going for you so far? What specific learning strategies are you using to prepare for and/or study for your accounting class? Is there anything inside or outside of the course that is affecting your experience in the course?

Interview Protocol: Final Participant Interview Tell me how your accounting course went. What was your final grade for the course? Are you satisfied with this grade? Why or why not? Do you think this grade reflects what you learned during the course? Why or why not? If final grade was different from what student expected: What do you think accounts for the difference? Did you make any changes in how you were preparing for class since we last met? What were the changes? How did they work for you? What advice would you give to students starting the course next semester? Are you required to take any additional accounting courses? If so, how do you feel about having to take them? Do you feel prepared to take them? Will you make any changes in how you prepare for class? What else that you would like me to know about your experiences in introductory accounting this semester?

Challenges and Opportunities for Teaching and Learning

APPENDIX B: LIST OF PRIMARY CODES Asking questions [8] Attitude [6] Career goals [10] Choice of major/minor [27] Classmates [15] Concerns [16] Continued study [22] Debits and credits [10] Difficulty level [25] Enjoyment [23] Exams[40]

Grades [45] Homework [75] Math [7] Memorization [10] Writing on board vs. PowerPoint [20] Novice learners [14] Other classes [42] Outcomes [40] Outside demands [13] Pace [8] Preconceptions of accounting [22]

Project [13] Quizzes [64] Some people just get it.[15] Study habits [25] Textbook [18] Three-hour class [21] Time Management [30] Tutors [15]

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APPENDIX C: LIST OF THEMES AND CORRESPONDING PRIMARY CODES Theme THEME #1A: I chose accounting because I like math/numbers and because of job opportunities; I did/didn’t really consider if it was a good match for me. THEME #1B: I chose a business major (minor) based on job opportunities. Although I know that I need accounting, I’m not looking forward to it.

Primary codes Career goals Choice of major/minor Preconceptions about accounting

Career goals Choice of major/minor Preconceptions about accounting Attitude Concerns THEME #2: I didn’t really know what to expect, Math but based on what I do know, I’m a little bit nervous Other classes about it. Preconceptions about accounting Prior GPA Classmates Exams THEME #3 For some students, accounting “just clicks,” the rest have to work really hard to learn this. Grades Some people just get it THEME #4: Homework was time-consuming, but it Homework really helped me learn accounting, both doing it and Textbook reviewing it in class. Time Management Grades Memorization THEME #5: For such a small part of the grade, the quizzes really stressed me out!! Quizzes Study habits Grades THEME #6: This was my first time taking account- Homework ing and that made it so much harder. Novice learners Project Asking questions THEME #7: I should have asked for help. Grades Tutors Outside demands Project THEME #8: Time management is always a challenge; the interim deadlines on the project helped Study habits me. Time Management Tutors Grades THEME #9: I’m satisfied with my grade, even Novice learner though it is lower than I hoped at the beginning. Outcomes (Continued)

Challenges and Opportunities for Teaching and Learning

APPENDIX C: (CONTINUED) Theme

THEME #10: Whoa! That was a tough course, but I really learned a lot.

THEME #11: I’ve learned that I do/do not want to continue in accounting.

Primary codes Classmates Debits and credits Difficulty level Exams Grades Memorization Writing on the board vs. Power Point Outcomes Pace Study habits Three hour class Career goals Continued study Enjoyment Outcomes

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APPENDIX D: LIST OF RESEARCH QUESTIONS AND CORRESPONDING THEMES Research Question

Theme THEME #1A: I chose accounting because I like math/numbers and because of job opportunities; I have to decide if it is a good match for me. THEME #1B: I chose a business major (minor) (1) How do students describe their based on job opportunities. Although I know that expectations as they enter the I need accounting, I’m not really looking forward introductory accounting course? to it. THEME #2: I didn’t really know what to expect, but based on what I do know, I’m a little bit nervous about it. THEME #3: For some students, accounting “just (2) How do students describe their clicks,” the rest have to work really hard to learn learning experiences during the course? this. THEME #4: Homework was time-consuming, but (3) What specific learning strategies do it really helped me learn accounting, both doing it students use during the course? and reviewing it in class. THEME #5: For such a small part of the grade, the quizzes really stressed me out!! THEME #6: This was my first time taking account(4) What other challenges or opportu- ing and that made it so much harder. nities do students face in their learning? THEME #7: I should have asked for help. THEME #8: Time management is always a challenge; the interim deadlines on the project helped me. THEME #9: I’m satisfied with my grade, even though it is lower than I hoped at the beginning. (5) How do students describe their THEME #10: Whoa! That was a tough course, but learning outcomes in this course? I really learned a lot. THEME #11: I’ve learned that I do/do not want a career in accounting.

CHAPTER 2

The Role of Community Colleges in Promoting Financial Literacy: A Proposed Model WILLIAM L. BLACK, PhD CPA Raritan Valley Community College

ABSTRACT

F

inancial impediments to success in college are a growing concern among college administrators, scholars, governmental agencies, and policymakers. Many deficiencies with regard to financial matters, such as poor budgeting skills, lack of knowledge of financial aid resources, working too many hours while enrolled in college, and poor credit management have contributed to low persistence among community college students. This paper proposes a model for community colleges to follow in addressing the problem of financial literacy. Elements of this model includes requiring students to take a personal finance course as part of their general education requirements, staffing advising/counseling departments with financial counselors, infusing financial education into freshman orientation programs, collaborating with local business to deliver financial workshops and seminars, engaging students to promote financial literacy, and developing college web sites to provide financial education to students.

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INTRODUCTION Financial impediments to success in college are a growing concern among college administrators, scholars, governmental agencies, and policymakers. College students today face increasing financial pressures as they endeavor to balance study, work, family, and planning for their futures. Lyons (2003) found that one in three students reported his/her financial situation was “likely” or “somewhat likely” to affect the ability to complete a college degree. This paper will examine some statistics regarding financial barriers to success faced by many community college students, and will discuss government initiatives to improve financial literacy among young Americans. Best practices at colleges and universities with regard to financial education will be discussed, and a model will be proposed for how community colleges might address the problem of financial literacy among its students.

GROWING FINANCIAL STRESSES DURING COLLEGE In a study performed by the Community College Survey of Student Engagement (CCSSE), 45% of community college students participating in the survey indicated that finances were critical to their continued enrollment in college (Cooper, 2010). As a result of the financial pressures many students face, 45% of students attending four-year colleges work more than 20 hours per week. Among those attending community colleges, 60% work more than 20 hours, with 25% working more than 35 hours per week (Harnisch, 2010). According to the Public Agenda ( Johnson and Ott, 2009), the leading cause of students leaving college is the inability to balance work with college study. The increasing cost of a college education combined with decreasing grant aid has forced many students to rely on employment to meet their college expenses. However, in their Institute of Higher Education report, Cunningham and Santiago (2008) point out that many students have an aversion to borrowing, quite often relying on employment income to cover college costs so as to avoid debt after graduation. Students at community colleges were found to be less likely to borrow than their counterparts at other institution types. Cunningham and Santiago also found that community college students who chose not to borrow to fund their education were more likely to leave college without a degree than those who did borrow. Per a National Center for Education statistics report (US Department of Education, 2008), an estimated two million students enrolled in college who were eligible for Pell Grants in 2007 did not apply for them. A

The Role of Community Colleges in Promoting Financial Literac

study by the Institute for College Access and Success (2009) found that twothirds of those taking out private loans did not exhaust more affordable and flexible federal financial aid first. It can be argued that a greater understanding of the appropriate ways to use debt to finance one’s education, versus relying on current income, may serve to increase graduation rates among community college students. Financial education initiatives at community colleges should endeavor to inform students and parents about the right balance of debt versus the benefits of a college education. There are some disturbing trends regarding inappropriate uses of debt among college students today. Recent studies have shown that the median credit card debt for college freshmen has tripled from 2004 to 2008, while graduating seniors carried an average of over $4,000 in credit card debt in 2008 (Harnisch, 2010). Many used their credit cards to charge tuition and other direct education expenses. Thirty percent of student credit card holders in 2008 put tuition on their credit cards, and 92% charged other direct education expenses such as text books, schools supplies, etc., instead of using less expensive financial aid to cover these expenses. Those who used credit cards to charge direct education expenses averaged $2,200 of education charges in 2009, almost double the level from 2004. Undergraduate students averaged 4.6 credit cards each in 2009, and only 17% paid their credit cards off each month (Sallie Mae, 2010). It is clear that students need to develop budgeting skills to properly plan their education costs. Gutter and Copur (2011) surveyed nearly 16,000 college students ages 18 and over from 15 college campuses in the United States and found that 52% did not budget their expenses, and 48% reported no savings. The percentage of students who “maxed out” on their credit cards was 13%, and 28% made late payments on credit cards. Only 31% paid off their credit card balances in full each month. Two-thirds of college seniors who graduated in 2010 carried student loan debt, with an average balance of $25,250, a 35% increase from 2004. An estimated 22% of this debt was composed of private loans (Reed, 2011) issued by private banks and lenders. Considered one of the riskiest forms of borrowing for college, most private loans have variable interest rates that are highest for those who are least able to pay off the loans. Furthermore, these loans lack the consumer protections and flexible payment options of federal loans. The combination of credit card debt and private borrowing to finance college puts college students at greater risk for financial problems after graduation. The Jump$tart Coalition for Personal Financial Literacy is a non-profit organization that consists of a coalition of over 150 major corporate, non-profit,

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government, academic, and other entities that share an interest in advancing financial literacy among students from early childhood through college. This organization started measuring financial literacy among students in 1997 and has since published results of biennial surveys where students are queried on the basic principles of personal finance. Results of the latest survey in 2008 showed that many college students lack basic knowledge in finance. The percentage of questions answered correctly by students in this survey is detailed in the table below. Based on the results of this survey, the Jump$tart report concludes that 75% of young students lack the basic skills needed to make good financial decisions (Mandell, 2008). Percentage of 2008 Jump$tart Survey Questions Answered Correctly High School Seniors College Students College Freshmen College Seniors

Percent 48.3 62.0 59.4 65.0

A GOVERNMENT CALL TO ACTION Recognizing the problem of financial literacy among the nation’s youth, federal and state government agencies have introduced a significant amount of legislation and initiatives to promote financial education and increase financial literacy. The United States Government Accountability Office (2004) defines financial literacy as “... the ability to make informed judgments and take effective actions regarding the current and future use and management of money.” The President’s Advisory Council on Financial Literacy (2008) defines financial education as: the process by which people improve their understanding of financial products, services and concepts, so they are empowered to make informed choices, avoid pitfalls, know where to go for help and take other actions to improve their present and long-term financial wellbeing (p. 35).

In 2003, Congress created the Financial Literacy and Education Commission, which serves as a central hub for over twenty federal agencies that promote financial education. In 2006, a national strategy was developed (Financial Literacy and Education Commission, 2006) that addressed specific problem

The Role of Community Colleges in Promoting Financial Literac

areas, including saving, budgeting, home ownership, consumer protection, and developing and maintaining credit. The Commission also identified targeted sectors for financial education, including seniors, unbanked and multicultural populations, K-12 and post-secondary students. With regard to post-secondary students, the strategy called on colleges and universities to find ways to raise financial literacy levels with the objective of helping students avoid financial hardship due to the mismanagement of credit and money. The national strategy provided a framework to raise financial literacy through suggested materials, delivery approaches, and dissemination channels. Also in 2003, the President’s Advisory Council on Financial Literacy was created. The council created a series of programs to promote financial literacy, entrepreneurism, and responsible consumer practices. Among its recommendations, the council called for mandating financial education for all K-12 students and creating a post-secondary honor roll to recognize colleges that are providing quality financial education to its students (Harnisch, 2010). In 2010, the Obama administration created the President’s Advisory Council on Financial Capability, whose mission is to create financial stability in the economy by helping Americans to understand financial matters and make informed financial decisions. One of the central themes of the Council is that financial education should take place in American schools. Of critical importance is for students to determine whether and how to pursue higher education and how to finance this investment (United States Department of Treasury, 2010). The Council has noted that while there are abundant financial literacy programs for K-12 and college students, there is little research on the effectiveness of these programs and their impact on financial behavior. At the state level, many states have mandated financial education as part of K-12 curriculum requirements. While 44 states currently have some form of personal finance content standards in place, only 15 states require a course in personal finance (Harnisch, 2010). Most research on the value of financial education has been at the K-12 level and has largely been inconclusive as to the effectiveness of financial education in improving consumer behavior. A study by Peng and Bartholomae (2007) showed no significant relationship between taking a finance course in high school and investment knowledge and savings behavior later in life, whereas participation in a personal finance course in college was shown to improve these measures. This is not surprising, as most young people make their first decisions regarding borrowing, budgeting, saving, and obtaining credit cards after graduating from high school. Having these “hands on” experiences in financial matters would serve to reinforce

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the learning of classroom content. In 2008, the President Advisory Council on Financial Literacy Annual Report (2008) recommended that additional research be conducted into the feasibility of requiring college students to take a course in financial literacy or pass a competency test as a condition of receiving government-backed student loans. In 2012, the Obama administration proposed requiring colleges to report how much students will need to pay for college on top of the financial aid they receive, what they will owe after graduation, and whether students who have graduated from their colleges are earning enough money to repay their loans. The intent of this initiative is to allow families to better understand how a college ranks against its competitors on important metrics like graduation rates, what a degree actually costs, and how much debt the student can expect to have after graduation. A one-page “shopping sheet” would be created under the initiative, where students can readily compare colleges on these metrics. To make the most of this data and to properly plan their finances after graduation, college students will need a solid understanding of debt and budgeting.

FINANCIAL EDUCATION: BEST PRACTICES AT US COLLEGES A number of colleges and universities have taken steps to promote financial literacy among its students by employing innovative approaches. Tidewater Community College in Norfolk, Virginia requires all students applying for financial aid to prepare a personal budget showing current income and expenses, along with an estimated future budget for the initial years after graduation. This future budget is to include plans on how the loan will be repaid. This requires students to research the potential salaries of their intended fields in order to develop a repayment plan ( Jacobs, 2011). Brigham Young University likewise requires students to file a financial plan with the financial aid office before their loan eligibility is certified and has an advising and counseling structure whereby academic planning and financial planning proceed on parallel tracks (Low, 2009). The University of Arizona has in place a student-run group named “Credit Wise Cats” whose mission is to educate other students about good spending habits and financial planning. This mission is achieved through group workshops and one-on-one meetings. Iowa State University has also instituted a student-run clinic for financial counseling and uses the internet extensively to promote financial literacy. E-mails with weekly financial tips are sent out to students, addressing topics such as obtaining credit, credit

The Role of Community Colleges in Promoting Financial Literac

cards, managing student loans, and investing, along with information about campus and community financial services and workshops. Over 40,000 people have signed up to receive these tips at the college during a three-year period (Oleson, 2004). At Raritan Valley College in New Jersey, a student organization named Students In Free Enterprise (SIFE) enlists qualified faculty and representatives from a local credit union to deliver seminars on budgeting, investing, and managing credit. They have also partnered with TIAA-CREF in their “Financially Empowering Gen Y Project”, where SIFE teams from across the United States develop creative, sustainable programs that encourage Gen Y members (typically considered those who were born in the 1980s and now range in age from 18 to 32) to take control of their financial well-being. Raritan Valley’s SIFE is among twenty-five competing teams tasked with combining basic economic concepts with an entrepreneurial approach to increase their peers’ financial aptitude in fun and innovative ways. The club conducts seminars covering topics that range from how credit is established and how to use a credit card, to budgeting basics. The Student Money Management Center at the University of North Texas also runs a web site for financial education and offers one-on-one counseling and group educational sessions targeted at freshmen, graduating seniors, and other groups. These educational sessions cover money management topics such as budgeting, apartment leases, credit cards, credit reports, college and living expenses, car buying, and student loan repayment strategies. The Center works closely with the financial aid office at the university and administers loan programs to help students with unanticipated expenses that threaten their continued enrollment in school (Low, 2009). Masuo et al. (2007) at the University of Hawaii at Manoa had a unique approach to designing a financial literacy program at their university. Initially, students were surveyed regarding the types of financial information they were interested in, and faculty and staff involved with financial education or counseling at the university were surveyed on their areas of interest along with their preferred presentation and delivery methods. They found that students were most interested in investing for the future, avoiding credit problems, financial security after graduation, and budgeting income and expenses. Faculty and staff were most interested in budgeting and avoiding credit problems, as well as student loan management and avoiding ID theft. Students and faculty/staff alike preferred to receive financial information as part of a financial aid interview, free food event, as part of extra credit in their classes, as part of the new

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student orientation program, or on a web site. The authors then went about identifying a team of faculty and staff, and developed programs where students and faculty/staff, based on their survey responses, were matched according to common interests. Financial workshops were developed for new student orientation, freshman seminars, and dormitory programs. Additionally, twelve business curricula were reviewed for relevance and quality of materials, and peer education programs were instituted. In evaluating their financial literacy program, the authors found that participating students gained new financial knowledge and demonstrated greater financial awareness than those students who did not participate. Westchester Community College in New York has created the Center for Financial and Economic Education through a donation from the JPMorgan Foundation. The Center offers financial literacy programs focused on financial planning, budgeting, saving, investing, and managing credit, which is directed at students, faculty, staff, secondary school teachers, and community residents. Southeast Community College in Nebraska also used outside funding through the Nebraska Financial Education Coalition, a group of nearly 100 Nebraska organizations working to promote financial literacy, to organize a “Money Smart Week” for over 340 community college students. Organizations within the coalition, along with college staff, held various events where financial topics were presented. These included a “Financial Aid Day” where counseling was provided to students on student loans, grants, scholarships, and other financial aid options. Sessions were held on the importance of checking and savings accounts, house and life insurance, and principles of investing. A “Budgeting for Food” workshop was held, where students learned how to plan meals to save time and money. The Internal Revenue Service and other community volunteers presented tax filing procedures as well as information on the free tax services available, and the student activities staff collaborated with a local credit union to offer a credit counseling session. Various games were held that covered financial education topics, including “Jeopardy,” “Financial Football,” and “Do You Think Like a Millionaire” (US Fed News Service, 2011). A number of colleges across the nation, including Southwestern Oregon Community College in Oregon, use a free online resource from the National Endowment for Financial Education called “CashCourse” to structure web sites that promote financial literacy. Approximately 146 colleges throughout the nation have created financial education web sites using the customizable “CashCourse” architecture (US Fed News Service, 2008).

The Role of Community Colleges in Promoting Financial Literac

A PROPOSED MODEL FOR COMMUNITY COLLEGES TO ADDRESS FINANCIAL LITERACY Harnisch (2010) posits that state colleges and universities, including community colleges, are in a good position to provide financial education leadership to campus communities. By providing financial literacy programs and services, state colleges can help students understand how to finance college and would serve to foster good spending habits. He also contends that state colleges can contribute to their community-based, public missions by preparing a new generation of financially literate individuals. As taxpayer-funded colleges with public purpose missions, state colleges can extend financial education not only to students, but to faculty, staff, and the community at large. In her literature review of financial-aid strategies that community colleges can employ to improve student retention and accelerate the completion of community college degrees, Cooper (2010) identified four strategies that should be considered: 1) provide more intensive financial aid counseling to ensure that students understand the sources of aid available to which they are entitled, 2) offering financial literacy programs to educate students on the importance of finances in making decisions, 3) offering financial incentives to students who complete their programs in a timely manner and earn good grades, and 4) offering emergency aid to those students who encounter financial problems while enrolled at their colleges. Drawing on the studies and best practices cited in this paper, along with this author’s personal observations, what follows is a proposed model for community colleges to follow in addressing the problem of financial literacy among community college students: 1. Community colleges were among the first to deliver personal finance courses, as many of their students were in their later 20s and early 30s who had postponed college and were seeking to learn the basics of personal finance (Blanton, 2011). As noted in Peng and Bartholomae’s (2007) study, personal finance courses are effective in influencing future financial behavior of graduates, more so than when delivered at the high school level. While academic personal finance courses are offered at most community colleges, there is little enrollment in these classes due to the fact that it is not required in any of the academic degrees offered and is not part of the general education requirements. Most personal finance classes are offered in the continuing ed-

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ucation (non-credit) departments of community colleges. While the President’s Advisory Council on Financial Literacy Annual Report (2008) recommended that additional research be conducted into the feasibility of requiring college students to take a course in financial literacy or pass a competency test as a condition of receiving government-backed student loans, community colleges should endeavor to make a course in personal finance a requirement for all students as part of the general education curricula. 2. While all community colleges have financial aid offices with advisors that help students navigate the many financial aid alternatives, many students do not fill out the required application (Free Application for Federal Student Aid, or FAFSA) for public funds, perhaps because they are unaware of financial aid opportunities or are hesitant to borrow. Furthermore, many students do not exhaust financial aid opportunities before taking out private loans, or they use current income to fund college, often leading to low persistence. Community colleges should strive to integrate financial counseling into services outside of the financial aid office. Financial counselors should be available in the general advising and counseling departments to address matters of poor student performance related to personal financial situations. Applications for admission should request that applicants indicate how they plan on funding their college education, and based on responses to these questions, e-mails should be sent directing students to the financial aid office or to financial advisors as appropriate. 3. Freshman orientation programs should incorporate a discussion on funding sources available for college, along with information on how to take advantage of resources within the college to make sound financial decisions. This information should likewise be shared with parents of students, and parents should be encouraged to discuss financial matters with the appropriate college staff. 4. Given their community-based mission, community colleges should reach out to local businesses, such as credit unions, banks, and CPAs, to collaborate on the delivery of financial education directed at students, faculty, staff, and the community at large. Colleges should also reach out to national organizations such as the IRS to present financial topics to the community. With the limited resources that most community colleges have, they should strive to obtain federal and

The Role of Community Colleges in Promoting Financial Literac

5.

6.

7.

8.

corporate funding to deliver financial seminars, workshops, and student events; similar to the best practices colleges cited previously. Efforts should be made to engage students in promoting financial literacy. This can be in the form of student organizations that provide peer financial counseling to fellow students, as is done in the University of Arizona and Iowa State. Student organizations, such as student government associations or business clubs, can also work with faculty and local businesses to deliver seminars and workshops in financial education, as is done at Raritan Valley Community College. As a condition for financial aid, students should be required to prepare personal budgets showing current income and expenses, along with estimated future budgets for the initial years after graduation, as is done in Tidewater Community College and Brigham Young. These future budgets should include plans on how their loans will be repaid. Financial aid counselors should be made available to help students with this process. Community colleges should develop websites that promote financial literacy. There are many free online resources to help students with financial aid matters, spending budgets, saving, and investing that can be linked into from these web sites. As is done in Iowa State, weekly e-mails with financial tips can be sent out to students to stimulate an interest in financial literacy. Free, customizable resources such as CashCourse can be used to structure web sites promoting financial education. A mechanism should be in place in community colleges to offer emergency aid to those students who encounter financial problems while enrolled at their colleges.

REFERENCES Blanton, K. (2011). Personal Finance Instruction at U.S. Colleges and Universities. Financial Security Project at Boston College. Retrieved from http://fsp.bc.edu/wp-content/uploads/2011/10/Personal-Finance-Instruction-on-U.S.-College-Campuses.pdf Cooper, M. A. (2010). Student Support Services at Community Colleges: A Strategy for Increasing Student Persistence and Attainment. Paper presented at the White House Summit on Community Colleges October 5, 2010. Retrieved from http://www.ed.gov/college-completion/ community-college-summit

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William L. Black Cunningham, A. F., Santiago, D. A. (2008). Student Aversion to Borrowing: Who Borrows and Who Doesn’t. A report by the Institute for Higher Education Policy and Excelencia in Education, December 2008. Retrieved from http://www.ihep.org/assets/files/publications/s-z/StudentAversiontoBorrowing.pdf Financial Literacy and Education Commission (2006). Taking ownership of the future: The national strategy for financial literacy 2006. Washington, D.C.: US Department of the Treasury. Gutter, M., and Copur, Z. (2011). Financial behaviors and financial well-being of college students: Evidence from a national survey. Journal of Family and Economic Issues, 32 (4), 699–714. Harnisch, T. L. (2010). Boosting Financial Literacy in America: A Role for State Colleges and Universities. Perspectives: American Association of State Colleges and Universities, Fall 2010. Retrieved from http://www.aascu.org/policy/publications/perspectives/. Jacobs, J. (2011). College 101: Financial Literacy. Community College Spotlight. Blog published by the Hechinger Report. Retrieved from http://communitycollegespotlight.org/content/ college-101-financial-literacy_6947/. Jump$tart Coalition for Personal Financial Literacy. Retrieved from http://www.jumpstart.org/ about-us.html. Kezar, A. (2010). The importance of financial literacy. About Campus, 14 (6), 15–21. Low, L. (2009). Financial Literacy and College Success at Minority-Serving Institutions. Paper presented at the 2009 IHEP Symposium, February 26, 2009. Lyons, A.C. (2003). Credit practices and financial education needs of Midwest college students. Champaign, IL: Department of Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign. Oleson, M. (2004). Using Technology to Provide Financial Education. Journal of Extension 42 (5). Retrieved from http://www.joe.org/joe/2004october/tt5.php. Mandell, L. (2008). The Financial Literacy of Young American Adults: Results of the 2008 National Jump$tart Coalition Survey of High School Seniors and College Students. Jump$tart Coalition for Personal Financial Literacy. Masuo, D. M., PhD., Kutara, P., Wall, R., and Cheang, M. (2007). Financial information project: Assessing the financial interests of college students. Journal of Family and Consumer Sciences, 99 (3), 29–36. Retrieved from http://search.proquest.com/docview/218179251 ?accountid=13314. Peng, T. C., Bartholomae, S., Fox, J. J., and Cravener, G. (2007). The impact of personal finance education delivered in high school and college courses. Journal of Family and Economic Issues, 28 (2), 265–284. President’s Advisory Council on Financial Literacy (2008). 2008 Annual Report to the President. Washington, D.C.: US Department of the Treasury. Johnson, J., Ott, A. N. (2009). With Their Whole Lives Ahead of Them: Myths and Realities About Why So Many Students Fail to Finish College. Public Agenda, 2009. Retrieved from http://www.publicagenda.org/files/pdf/theirwholelivesaheadofthem.pdf. Reed, M. (2011). Student Debt and the Class of 2008. The Project on Student Debt, December 2011. Retrieved from http://projectonstudentdebt.org/state_by_state-data.php.

The Role of Community Colleges in Promoting Financial Literac Sallie Mae (2010). How Undergraduate Students Use Credit Cards: Sallie Mae’s National Study of Usage Rates and Trends, 2009. Retrieved from https://news.salliemae.com/sites/salliemae. newshq.businesswire.com/files/doc_library/file/SallieMae_MajoringinMoney_2016.pdf./ news_info/newsreleases/041309.htm. The Institute for College Access and Success (2009). Statement on College Board’s Trend Report. Retrieved from http://www.ticas.org/files/pub/CB_statement_2009.pdf. US Department of Education, National Center for Education Statistics (2008). The Condition of Education 2008. Retrieved from http://nces.ed.gov/pubs2008/2008031.pdf. US Department of Treasury (2010). Key Themes for President’s Advisory Council on Financial Capability (PACFC). Retrieved from http://www.treasury.gov/resource-center/financialeducation/Documents/Key_Themes.pdf. US Fed News Service (2011). Southeast Community College Participates in Nebraska Money Smart Wee Activities. US Fed News Service Including US State News, December 8, 2011. US Fed News Service (2008). Southwestern Oregon Community College, National Endowment for Financial Education Partner to Educate Students on Finance. US Fed News Service Including US State News, September 26, 2008. US Government Accountability Office (2004). The Federal Government’s Role in Improving Financial Literacy US Government Accountability Office. Retrieved from http://www.gao.gov/new. items/d0593sp.pdf.

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CHAPTER 3

The Toolbox—an Innovation Connecting Marketing Education and Practice KEVIN E. MCEVOY, PhD Marketing Department, University of Connecticut

ABSTRACT

M

arketing students currently face two significant issues: remembering what they have learned after graduation and showcasing the knowledge and skills they do possess to other degree programs, potential employers, and other interested parties. This article presents the Toolbox, an innovative tool that offers a solution. The Toolbox is a personal library or portfolio of student completed work as well as collected resources. By creating, organizing, and presenting a Toolbox, students can maintain access to their educational experiences and provide evidence of their skills and experiences to others. This can create a bridge between marketing education and practice.

THE CURRENT NEED FOR AN INNOVATIVE TOOL The Association to Advance Collegiate Schools of Business currently accredits 777 business schools in 52 countries and territories (AACSB), which graduate

The Toolbox—an Innovation Connecting Marketing Education and Practic

thousands of MBAs and undergraduates every year—new marketing graduates among them. These graduates are typically seeking new employment, advancement in current employment, or new business opportunities. For those candidates seeking new employment or advancement, competition is intense. The ability to showcase what they know, the skills they have, and how they can apply such knowledge and skills for the employer are critical in order to beat the growing global competition (Kennedy, Lawton, and Walker, 2001) for positions. Some educators in fields such as arts and communications have been suggesting students create personal portfolios as a platform for sharing their work, and utilizing the internet as a distribution system for these “eportfolios” with reported success (Okoro, Washington, and Cardon, 2011). A second problem exists: forgetting material that has already been learned. Forgetting begins almost immediately, and most knowledge and skills may be lost just two years after graduation (Bacon and Stewart, 2006). Recapturing the learning that has been lost is inefficient, wasteful, and often simply impossible, since the resources needed to do so may only be available at universities and to currently enrolled students. This problem is exacerbated if the material is needed quickly in a professional setting, or perhaps during an interview. Having a personal portfolio can support students in maintaining and continuing to develop their knowledge base (Kruger, Holtzman, and Dagavarian, 2013).

INTRODUCING THE TOOLBOX When students become job candidates, they can both maintain access to their acquired knowledge and showcase what they know and the skills they have in a way that can be more specific and personal than grade point average, letters of reference, and resumes. Students of all levels (PhD, MBA, and Bachelor’s degrees) can demonstrate their abilities by collecting and providing concrete evidence of what they have already done, and what they have maintained from what they have studied. This collection can include a personal library of work completed—presentations, papers, spreadsheets, and creative work the students produced as well as saved materials produced by others. Using these libraries as their personal databases, they can create presentations to illustrate successes they have already had. These personal libraries and presentation materials combine to become the candidates’ personal Toolboxes. Marketing, and most business school curricula, focus on the delivery of course content by faculty and the acquisition of knowledge and skills by students. Students provide evidence of such acquisition in their papers, projects,

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and examinations. Typically, however, little is offered in the way of helping students provide evidence of their ability to make use of all that education. The development of the Toolbox by the student during the education process can provide a solution. The creation of a Toolbox is an opportunity for students to consider and to share work they have already completed, organized, structured, and maintained for their personal databases.

HOW THE TOOLBOX INNOVATION WORKS The Toolbox is a student-directed, created, maintained, and enhanced personal library and portfolio of resources and materials they have accumulated during their coursework and other learning experiences. Materials can include presentations both individual and team-based, research papers, databases, spreadsheets, creative projects, and other resources. These materials can originate in such course assignments as developing marketing plans, creating advertising campaigns, designing new products, managing sales forces, completing consumer and market research projects, drafting cost and price analyses, and any other coursework. Experiential learning exercises include internships; parttime, summer, and semester intersession jobs; and other activities. In addition to students’ own material, they also curate a collection of materials others have composed or developed. These include textbooks and professional books, published researched papers, business and government reports, magazine and newspaper articles, films, videos, photographs, and any other materials that add to the body of the Toolbox in an accessible, useable way. The Toolbox is a new innovation due to this combination of materials from various sources. A library is a curated collection of other people’s works. A portfolio is a collection of the individual creator’s works. The Toolbox is the user’s self-directed strategic combination of both, with the objective of providing not just information, history or record, but organized for utility and use. A visual of the Toolbox process appears in Exhibit 1. Students are provided the freedom to determine the organization and format of their personal Toolbox. The students themselves determine what material goes into the Toolbox and how they want to organize it. In determining format, they select for themselves whether they will use hard copies in folders or binder books or digital copies on hard drives, thumb drives, or personal websites. This flexibility can enhance student learning while developing their Toolboxes, providing students with elements of learner independence and self-directedness, which are important in the learning process (Boote 1998).

The Toolbox—an Innovation Connecting Marketing Education and Practic

This flexibility can also accommodate diverse student learning styles and learner preferences (Smith 2000), providing an enriched learning experience. This also provides enhanced practicality, since the students determine how best to use the Toolbox.

SHOWCASING THE TOOLBOX Near the end of the semester, students present samples of their Toolboxes to the entire class. These presentations are short, with the length of time per student determined by the number of students in the class. These presentations provide an opportunity for students to share pieces of what they have accumulated, and for the rest of the class to add materials they also might find useful. Such shared materials typically include recommended books, articles, websites, brochures, films, organization memberships, and a wide variety of other materials. Students often comment how useful they find the sharing after the Toolbox presentations end; one student observed that “It’s as if I was in a room full of researchers.” In addition to the value of the Toolbox exercise itself, students are graded on their presentations. These grades are based on organization and depth of material. The grade value to the Toolbox presentation is typically 10% of the entire course grade. For students in advanced marketing electives who have created Toolboxes in previous courses, expectations are higher since the basic Toolbox has already been created.

THE VALUE AND EFFECTIVENESS OF THE TOOLBOX INNOVATION Student are told that much, if not most, of what they learn will be forgotten soon after graduation. Recovering this knowledge is inefficient and time-consuming and in some cases may not be possible at all. In addition, it is a loss of the value of the student’s “sweat equity,” the value of their previous educational effort. The Toolbox can help here. Students are also reminded that the competition they will face for good professional positions is intense. In this competition, any knowledge, skills, and abilities they can demonstrate during the hiring process can give them a competitive advantage. Students are offered the opportunity to discuss and plan what they intend to take from their coursework as it relates to their career plans. At the start of the semester the Toolbox is explained and suggestions about what might be

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appropriate for inclusion are offered. Samples from the course instructor’s own Toolbox are modeled for the class. An abbreviated sample of one student’s Toolbox is included at the end of the article.

EVIDENCE OF THE TOOLBOX INNOVATION’S EFFECTIVENESS The effectiveness of the Toolbox has been demonstrated by reports from its users—students who have maintained and further developed their Toolboxes as their personal library and portfolio and for use in demonstrating their knowledge, skills, and abilities—especially to prospective employers. Data that appears here is only a sampling of results. All data collected was provided by the users to the author completely voluntarily and without request or suggestion. A business school graduate, class of 2008, now working in new product development at a major cable network, stated in October 2016 during a speech to new business students, “Every job I have gotten since I graduated from college I have gotten using my Toolbox.” Other students have reported the following results (student names have been omitted and company names are pseudonyms): Just wanted you to know that I received a confirmation today that I will be working at Global Beverage Company starting this Wednesday. Thank you for introducing me to the very handy Toolbox method. I pulled everything I needed for the interview and launched my arsenal.... I went in there confident and excited with Toolbox in hand. Thank you for teaching me and showing me how vital my tool box can be!!! As I told you, (thanks to your Toolbox) I recently started a job at National Supply Company. The Toolbox totally helped! They [a national sports team] were so impressed with it. I first interviewed with HR, and showed them, and they told me I was so organized and accomplished. I was so psyched to hear that, and was so proud of my Toolbox!!!! My Toolbox is utilized daily for my career here and keeps growing. This is my 4th promotion in 5 years, 2nd in 8 months!!! I have now been offered a 1-year assignment in London to help bring best practices to our UK Division! It has been a pleasure and quite an invaluable learning experience. I shall carry my Toolbox with me always :)

The Toolbox—an Innovation Connecting Marketing Education and Practic I am truly starting to see the benefits of the Toolbox. I’m not just storing stuff anymore, but have found myself using the material much more often. There are quite a few pieces from your course that I use literally every day in my field. The Toolbox exercise was probably the most useful as I have read 8 books and use 10–12 of the tools I observed in other peoples boxes. I was able to go into my Toolbox (digital folder) and find this to prepare for an upcoming career discussion with a new department.

The success of the Toolbox is based on its combination of characteristics: it is a self-directed process by the user; it contains both collected and selfcreated materials; it is organized for utility, not simply collection.

THE TOOLBOX INNOVATION’S FLEXIBILITY, ADAPTABILITY AND POTENTIAL LIMITATIONS The Toolbox is a highly adaptable method for marketing students to maintain their self-developed work and the collected work of others, and to further enhance and develop it. It has proven useful in providing students with a competitive edge in hiring. These benefits apply to students of all levels, from students completing their freshman year looking for internships and summer jobs through MBA graduates hoping to move to a higher-level professional position. The more education and work experience the student has, the richer and deeper the Toolbox will be, with a wider variety of materials. Any marketing subject area can be included in the Toolbox, and the more thoroughly integrated the Toolbox, the more useful the Toolbox will be. Brand management, marketing research, consumer behavior, integrated marketing communications, advertising, sales, and global marketing are all areas that have been addressed in Toolboxes. The Toolbox is versatile beyond marketing material as well. Students and practitioners of virtually any subject, inside and outside of business areas, can benefit from the Toolbox concept. In addition, material directly related to professional activates can be included, and can work very well when integrated with academic and scholarly materials. Limits can exist on what materials can be included in a Toolbox: students and practitioners are advised to adhere to all legal, professional, and confidentiality standards, and ownership rights when determining what they can include in their Toolbox. Even with any potential legal restrictions, the Toolbox innovation can be used to collect a vast amount of material. Along with its flexibility and adaptability, its high storage capacity makes Toolbox useful and worthwhile for marketing education and practice.

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SAMPLE OF PARTIAL STUDENT TOOLBOX COLLECTED BIBLIOGRAPHY Coleman, LiPuma, Segal and Morrill, Inc. Package Design and Brand Identity: 38 Case Studies of Strategic Imagery for the Marketplace. Rockport. UK. 1993. Genova, Jane. “Comebacks—Handling Ourselves on the Way Back Up.” FCBJ. Gobe, Marc. Emotional Branding: The New Paradigm for Connecting Brands to People. Allworth Press. NY. 2010. Greenwall, Bruce, and Judd Kahn. Competition Demystified: A Radically Simplified Approach to Business Strategy. Portfolio. NY. 2007. Levinson, Jay Conrad, Levinson, Amy, and Levinson, Jeannine. Guerilla Marketing: Easy and Inexpensive Strategies for Making Big Profits from Your Small Business, 4th ed. Houghton Mifflin. MA. 2007. McCarty, Andrew. 500 Social Media Marketing Tips: Essential Advice, Hints and Strategy for Business: Facebook, Twitter, Pinterest, Google+, YouTube, Instagram, LinkedIn, and More! CreateSpace Independent Publishing Platform. Amazon.com. 2013. Pulido, Alfonso, Stone, Dorian, and Strevel, John. “The Three Cs of Customer Satisfaction: Consistency, consistency, consistency.” McKinsey & Company. March 2014. Roman, Kenneth, Maas, Jane, and Nisenholtz, Martin. How to Advertise: Building Brands and Business in the New Marketing World. St. Martin’s Griffin. NY. 2005. Verklin, David, and Bernice Kanner. Watch This, Listen Up, Click Here: Inside the 300 Billion Dollar Business Behind the Media You Constantly Consume. John Wiley & Sons. NJ. 2007. “BDI/CDI Calculations.” Media Math. NTC Publishing. “Media Math.” Media Math. NTC Publishing. “Social Media Pocket Guide.” Spredfast. 2013. Aaker, David. 10 Guidelines for Your Brand Portfolio Strategy. Marketing News. January 2014. https://www.ama.org/publications/MarketingNews/Pages/10-guidelines-for-your-brandportfolio-strategy--.aspx. Aaker, David. Brands as Assets. Marketing News. March 28, 2014. AMA.org. AMA e-newsletter. How to Enable Employee Brand Ambassadors Through Social Media. February 25, 2014. http://www.AMA.org. Birkner, Christine. From Entitlement to Enlightenment. Marketing News. March 28, 2014. https://www.ama.org/publications/MarketingNews/Pages/From-Entitlement-to-Enlightenment.aspx. Drell, Lauren. Stitching Together Experiential Marketing and Social Media. Marketing Insight e-newsletter. March 31, 2014. https://www.ama.org/publications/eNewsletters /MarketingInsightsNewsletter/Pages/experiential-marketing-social-media.aspx James, Geoffery. 6 Ways Selling Will Change by 2024. March 31, 2014. http://www.inc.com /geoffrey-james/6-ways-selling-will-change-by-2024.html. Haxthausen, Ove, and Kumar, Pankaj. Measure to Manage. Marketing Insight. Fall 2013. https:// www.ama.org/publications/MarketingInsights/Pages/brand-equity-perceptions-customers-choice-salience-impact-positioning.aspx.

The Toolbox—an Innovation Connecting Marketing Education and Practic Kasolowsky, Naomi. Maintaining Customer Loyalty.Marketing Insight. January/February 2014. https://www.ama.org/publications/MarketingInsights/Pages/Maintaining-Customer-Loyalty.aspx. Krajicek, David. Big Data’s Next Step. Marketing Insight. January/February 2014. https://www. ama.org/publications/MarketingInsights/Pages/Big-Datas-Next-Step.aspx.

EXHIBIT 1 The Toolbox Model

Student with Career Goals

Collects and creates materials

Work Academic Experiences Experiences

Life Experiences

Materials Organized and Catalogued

Materials Ulized

REFERENCES Academy for the Advancement of Collegiate School so Business. Retrieved on October 16, 2016 from: http://www.aacsb.edu/accreditation/accredited-members/. Bacon, D. and Stewart, K. (2006). How Fast Do Students Forget What They Learn in Consumer Behavior? A Longitudinal Study. Journal of Marketing Education, 28 (3), 181–192. Boote, J. (1998). Learning to learn in vocational education and training: Are students and teachers ready for it? Australian and New Zealand Journal of Vocational Education Research, 6 (2), 59–86. Kennedy, E., Lawton, L., Walker, E. (2001). The case for using live cases: Shifting the paradigm in marketing education. Journal of Marketing Education, 23 (2), 145. Kruger, E., Holtzman, D., Dagavarian, D. (2013). Comprehensive Education Portfolio with a Career Focus. The Journal of Continuing Higher Education, 61 (1), 46–53, DOI: 10.1080/07377363.2013.759494. Okoro, E., Washington, M., Cardon, P. (2011). Eportfolios in business communication courses as tools for employment. Business Communication Quarterly, 74 (3), 347–351. Smith, P. (2000). Flexible delivery and apprentice training: preferences, problems and challenges. Journal of Vocational Education and Training, 52 (3), 483–503.

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CHAPTER 4

Women’s Journeys to the C-Suite and the Emotional Component of Success SABRA E. BROCK, PhD Touro College SHARON ROWLANDS, BA CEO, Web.com

ABSTRACT

T

he purpose of this study was to elicit authentic stories of women who have achieved high levels of organizational success and document their journeys and the emotions experienced. While significant press has been dedicated to the growing number of females achieving top organizational positions, the emotional component of their success has been little examined except anecdotally, and the story quickly moves to work/family balance issues. Also not very much has been said about those female business executives who are not household names, but who are quietly leading their organizations to success. Fifty senior female leaders participated in an in-depth electronic survey about their leadership journeys. These women came from the C-Suites of organizations across a broad range of sizes in different sectors including financial services, healthcare, media, consulting, and technology. Most were CEOs and based in the United States.

Women’s Journeys to the C-Suite and the Emotional Component of Success

The journey for most women to the C-Suite began with an early sense of self-confidence. Most (86%) felt they had made sacrifices, especially in family time. However, the emotional associations with high-level positions were generally positive: excitement, gratitude, and pride, although also there were times of feeling overwhelmed and frustrated.

INTRODUCTION Increasingly, women are rising to top leadership positions in business. Although much has been written, especially in the popular press, about a few household names such as Sheryl Sandberg, Marissa Mayers, and Meg Whitman, little is said about the hundreds of women leading less well-known organizations to quiet success. There is also a dearth of information about the emotions that a woman encounters on her way to the top. This research began in meeting with the WADOBEs, a group of highperforming women who get together once a year. These women are at the top of their organizations and gather to exchange stories and for mutual support, realizing that females have a somewhat different journey to the top than do men. The organization’s motto is “Want what you have. Do what you can. Be who you are.” Coincidentally the acronym of their motto spells “Wadobe,” a tribe in African history led by a woman. The defining characteristics of WADOBEs are being quietly successful, possessing strong emotional intelligence, and, with most, being the primary breadwinner with a supportive partner.

LITERATURE REVIEW Women at the head of businesses emerged more than a hundred years ago (Britanica Academic Online, 2016). Rose Knox expanded a gelatin company to become one of the United States’ outstanding businesswomen in the 1940s. The 1950s saw Josephine Bay running American Export Lines and Olive Beech at the top of Beechcraft Aircraft Corporation. Also, Josephine Holt headed AM Kidder in the 1950s. Mary Kay Ash started her very successful company in 1953. Even earlier there were successful startups by Lydia Pinkham (1875), Elizabeth Arden (1908), Helena Rubenstein (1917), and Estée Lauder (1946). The literature on female business leaders segments into several areas: the number and percentage (Bureau of Labor Statistics, 2016; Catalyst, 2016b; Lean In and McKinsey&Company, 2015, 2016; Peck, 2015; Worsham, 2010), their performance (Bureau of National Affairs, 2016; Gondhalekar and Dalmia, 2007; Kolev, 2012; Singhathepl and Pholphirul, 2015), leadership style (2013

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Wwd Ceo Summit, 2013; Branson, 2010; Chamorro-Premuzic, 2013; Fairchild, 2014; Hayer, 2015; Jordan, 2009; Morgan, 2014; Rhee and Sigler, 2015), demographics and personal history (Fitzsimmons, Callan, and Paulsen, 2014; Shaw and Leberman, 2015), and experiences of work/family issues (Moeller, 2012; Slaughter, 2015).

Rise in percentage of female CEOs The percentage of CEOs in large businesses that are women is still below 33%, but varies from study to study. Female CEOs accounted for 4% of the Standard & Poors 500 companies and 15% of the largest Australian organizations (Catalyst, 2016a). In the Fortune 1000 organizations, the percentages have gone from less than 1% in 1998 to close to 3% (Fairchild, 2014). The proportion of women in the CEO pipeline is reported as 17% in 2015 and 19% in 2016 (Lean In and McKinsey&Company, 2015, 2016). These findings may represent a change from the 1980s when Nicholson and West (1988) observed the tendency of most women not to choose the type of mainstream jobs that would lead to the C-Suite, also called the CEO pipeline in the more recent literature. Smaller organizations are more likely to have a female CEO than the very large ones, raising the percentage to 8% in worldwide companies with revenues over $500 million (Fairchild, 2014). The Bureau of Labor Statistics (2016) indicates that 27.9% of the 1517 CEOs in the United States are female. The percentage changes from industry to industry; for example, Worsham (2010) cites the percentage in hospitals as 24%. The leadership pipeline also varies from industry to industry with retail organizations having 29% females in the C-Suite, and healthcare and pharmaceuticals 24%. Low representation (13%) is found in both energy and basic materials as well as logistics, travel, infrastructure, and industrial manufacturing (Lean In and McKinsey&Company, 2015, 2016). Most corporate executives significantly overestimate the percent of CEOs of large businesses who are women, guessing 23% (Peck, 2015). Ironically, this number is closer to the percentage of female CEOs in all organizations than it is of the percentage in large companies. This overestimate may be due to the large amount of coverage given to the issue of the percentage of female CEOs in the popular media. The popular press coverage of female CEOs continues to increase with over 29,000 articles annually in 2015–2016. In contrast, the coverage of female CEOs in scholarly journals has declined more than 30% in the last year although it is still close to a thousand in a QuickSearch survey of one college library’s collection. A concise review of the changes in female presence in C-Suite as reflected by the press is given in Table 1.

Women’s Journeys to the C-Suite and the Emotional Component of Success Table 1.  Trends in Articles on Female CEOs 2016 2013–2016 2011–2016

Scholarly Press 862 3726 (1242 per annum) 6295 (1259 per annum)

Change –30.6% –1.3%

General Press Change 29,865 +2.7% 87,250 (29,083 per annum) +4.9% 138,560 (27,712 per annum)

Performance of female CEOs The performance of female CEOs is being debated. Palvia, Vähämaa, and Vähämaa (2015) found female bank CEOs were more conservative than their male counterparts. Gondhalekar and Dalmia (2007) showed no significant impact of CEO gender on the size, growth prospects, or profitability of 50 companies in the Russell 3000. In Thailand, Singhathepl & Pholphirul (2015) discovered a negative effect of female CEOs on both short-term and longterm financial performance. Kolev (2012) also reported a significant underperformance in shareholders’ returns in organizations with female CEOs. The average female CEO salary exceeds that of male CEOs in the top 100 companies, influenced by a few women who are heading very large companies, notably three of the Fortune 50 organizations (Bureau of National Affairs, 2016).

Demographics of female CEOs Some demographics of female CEOs in larger organizations have been documented (Fairchild, 2014). The most prevalent (39%) college degree among female CEOs in the Fortune 1000 is the MBA. Almost all female CEOs (93%) are married and most (84%) have children (Lean In and McKinsey&Company, 2015, 2016).

Leadership styles of female CEOs Leadership style in female CEOs is described as working through teams (2013 Wwd Ceo Summit: Transformers, 2013), and it is also reported that women hold back raising their hands for promotion unless they perceive they hold all the qualifications (Ibarra, Ely, and Kolb, 2013). Chamorro-Premuzic (2013) hypothesized that given the same level of competence, aspiring female leaders are less likely to display confidence than aspiring male leaders. Rhee and Sigler (2015) found that student ratings of female leaders who go against female stereotypes in movies are harsher than those of male leaders in corresponding positions, and the authors believe that more successful female mentors are required to break stereotypes.

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Traits predicting rise to CEO Fewer children and less education positively correlated with women at the head of large US companies (Hurley & Choudhary, 2016). Studying a sample of Australian CEOs, Fitzsimmons and Paulsen (2014) reported the father’s work role was different for male and female CEOs with male CEOs growing up in families where the father was a professional or tradesman and mothers not working outside the home. Female CEOs, on the other hand, had a father who was self-employed in a small business and a mother involved in that business. The female CEOs were likely to have a strong female teacher as a role model and get an early understanding of business from family discussions. Unlike the men, most of the female CEOs had significant disruptions as children, such as house moves and income disruptions, which, as they reported, only made for strength. These authors posited that this overcoming of adversity might be a key component of building confidence early, which males would more likely get from risky play and sports. The authors also reported that mentors are more important to women in portraying models of leadership. A number of researchers have studied the characteristics of women rising through the ranks, such as perseverance (Hayer, 2015), hard work and risk taking (Morgan, 2014), and emotional intelligence ( Jordan, 2009). Such features often predict the rise to the top in women’s careers.

Emotions in the C-Suite Despite attention given to the backgrounds and leadership characteristics of CEOs, Dinh, Lord, Gardner, Meuser, Liden, and Hu (2014) observed that emotions are ignored in studies of the path to leadership. However, some researchers have studied the role of emotions in various female journeys to leadership, Wright (1996) highlighting the role of high expectations of women managers in education and Letherby and Reynolds (2009) observing their emotions in travel. Greenglass (1993). Korabik, McDonald, and Rosin (1993), and Marshall (1993) studied the strategies of women in coping with workplace stress and the importance of social support. Piderit and Ashford (2003) examined how women managers speak up on gender equity. The issue of work/ life balance and sacrificing family time is prevalent (Branson, 2010; Slaughter, 2015), and Shaw and Leberman (2015) noted the work/life balance was the key challenge. Lean In and McKinsey&Company (2015, 2016) pointed to the stress perceived in top-level positions as being more of a damper to women than to men.

Women’s Journeys to the C-Suite and the Emotional Component of Success

Exhortations to lead without emotional displays have appeared (Stern, 2009), but increasingly, the need to explore the role of emotions in the workplace is being expressed (Ashforth and Humphrey, 1995; Gooty, Connelly, Griffith, and Gupta, 2010). The importance of emotions in understanding and predicting human behavior is well documented (Goleman, 1998; Spencer, Walby, and Hunt, 2012), and studies have been made of the role of emotions in educational leaders (Berkovich and Eyal, 2014). Taylor, Klein, Lewis, Gruenewald, Gurung, and Updegraff (2000) posited that women react with “tend and befriend” emotions as opposed to male “fight or flight” reaction in times of stress. However, little systematic report has been made of the emotions successful organizational women experience. Elsaid (2015) noted that female CEOs are underresearched, largely because there have been so few until recently. Furthermore, little research has focused on the emotional journey of women to the C-Suites of organizations that are not in the popular headlines.

RESEARCH QUESTIONS The following research questions were used for this study. RQ 1. What are the dominant positive and negative emotions that female organizational leaders express regarding the journey to the top? RQ 2. What patterns define the lives of women who have reached the tops of organizations? RQ 3. Looking back at a successful career, what do C-Suite women recommend be changed for future generations of female leaders? A copy of survey questions appears at the end of this article.

RESEARCH METHOD This research began with an in-depth interview of one female CEO. From that information base, an electronic survey was developed and pretested. It consisted of sixteen questions, six of which allowed for open-ended responses. A copy can be found at the end of this article. The survey was distributed through personal connections and requests to women identifying themselves as holding the top position in their organization in the LinkedIn database. Respondents had the opportunity not to identify themselves and their organizations; most (54%) gave the name of their organization.

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The study had been approved by the College’s Institutional Review Board. The questionnaire was distributed through a survey tool from December 2015 through January 2016. A total of fifty women responded. Most managed midsized global organizations that were headquartered in the United States, but England was also represented. Sectors represented included media/technology, healthcare, consumer goods, management consulting, and financial services. For a review of the respondents’ backgrounds, see Table 2. Table 2.  Sample demographics, based on 27 women who identified their organization Position

#

CEO

16

59%

Other C-Suite Positions

11

41%

No

24

89%

Yes

3

11%

New York City

11

41%

Other US City

14

52%

UK

2

7%

Media/technology

11

41%

Financial services

5

19%

Healthcare

3

11%

Consumer goods

2

7%

Management consulting

2

7%

Other

4

15%

Fortune 500 Organization?

Location

Sector

After analysis of the quantitative data, the answers to the open-ended questions were examined to identify themes. Qualitative responses were analyzed, looking for similarity in answers to elicit commonalities.

FINDINGS Answering Research Question 1 required examining the dominant positive and negative emotions that these female organizational leaders expressed regarding the journey to the top.

Women’s Journeys to the C-Suite and the Emotional Component of Success

The Emotional Component of Success Positive emotions dominated despite sacrifices and negative emotions. The respondents expressed excitement (82%), gratitude (62%), and pride (58%), although there are also moments of feeling overwhelmed (48%) and frustrated (44%). For complete range of responses, see Figure 1.

Figure 1.  Five Words Best Describing My Journey to Success

Many of these female leaders expressed excitement is as seeing a job well done. “I love to work. I love to fix things. I love to watch my work fixing things help an organization and its people realize great success,” responded the manager of a New York information services company.

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Most (86%) of the respondents felt they had made sacrifices with over 50% citing less time with family and a few even giving up the opportunity to have more than one child. Another common theme was the neglect of self, whether it was health or the inability to invest time in other interests such as charities or friends. Despite these sacrifices, there was gratitude, as one female leader expressed, “I see sacrifice as a part of every balanced life. I am fortunate to have (thus far) been in positions where I have vocalized my priorities early and they have been taken (relatively) seriously by my superiors…. I am very grateful for my path at this stage but very conscientious of the fact that it will continue to evolve.” The downside often centered on fitting into a male and competitive culture, expressed for example as: “[N]ot feeling that my skin was thick enough, dealing with male emotions and communications,” said a director at a New Jersey pharmaceutical. “Being questioned constantly. Undercut,” responded a CEO of a New York software organization. Some of the frustrations related to gender bias, especially in early career: “Being referred to as ‘young woman’ despite being older than male colleagues. Hard to fit into the cigar smoking clique of men,” said the CEO of a digital media agency. Often though, these negative emotions resulted in increased motivation: “I think there have been times when the expectation of me was less because I’m a woman. Rather than be defeated by that attitude, it’s always motivated me to over-perform to debunk the biases,” said another female leader.

Life Patterns Answers to Research Question 2, describing patterns of shared characteristics of female organization leaders, showed consistent themes in their lives. For most, the path to the top was set early. The majority (54%) said that as a child they expected to would have a career and to be a leader of some sort. The turning point to the C-suite occurred relatively early, for most respondents (86%) before their 40th birthday, usually in their 30s (64%), but also 20s (22%). Most (65%) were asked to take on a senior role, but the others directly applied for the job. Almost all used the behavior more commonly thought of as male when applying for a job for which they did not have the required experience but believed they had the potential to do it. They attributed success to team building (29%), hard work (27%), persistence and resilience (27%), and risk-taking (19%). The head of an English business school expressed team building as “Being human, understanding the organization and having the

Women’s Journeys to the C-Suite and the Emotional Component of Success

ability to form and deepen relationships based around value proposition and value creation.” Many referenced their work ethic. The executive chair of an information services company said she “worked really, really hard.” “Hard work, drive, stamina,” reported the CEO of a New York-based media company when asked about the key to her success. The importance of persistence was expressed by a C-Suite leader of a software company as, “Determination to get the job done,” or, as a healthcare executive said, “(I) persevere even when it feels impossible, lead the team through difficult times and keep focused on true north.” The general manager of a healthcare company stressed her willingness to take risks: “I am willing to take risks in my career (take jobs that are challenging and/or work at companies that are being disrupted). I am good at going into difficult situations and putting businesses on the right track.” There were also differences expressed. For example, one respondent pointed out that women of color faced specifically difficult problems. As the CEO of a Washington-based consulting firm said, “There is another aspect to female leadership when you consider the difference between women of color and other women in the business world.” Mentors were unlikely to be female. Although most respondents (82%) had at least one mentor, mentoring relationships became the key success factor to relatively few (6%). Only 9% of the respondents had a sole female mentor, while 53% had a male mentor and 37% had both male and female mentors. Formal training is not an important piece of the puzzle for these women, with 90% of the group indicating they had learned on the job and other 10% citing some form of executive training or graduate school. A chairperson of a New York financial services company said about mentors, “I was never offered one or put on a formal program. I have chosen to get myself mentors in the last ten years however.” A general manager of a Colorado healthcare organization noted, “Having a great female mentor is wonderful, understanding that you can be female in a male dominated world and be successful, not letting your female insecurities allow you to make up worse situations then exist, finding your inner confidence is key.” Over 40% described their dominant leadership style as command and control, while 60% described their leadership style as empathetic and nonhierarchical, traits commonly associated with female leaders. The dominant theme was being able to employ a command and control style where it was needed, but the foundation style was collaborative. Most expressed using multiple leadership styles. For example a director at a wholesaler headquartered in

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the Midwest United States said, “Depends on the day and the role needed at the time. I’d also list inclusive soliciting ideas from staff to ensure they feel like they contribute and have ownership.” Most (82%) of the respondents experienced some form of gender bias along their journey with the most common one being disrespected and treated differently from men and not being viewed as capable because of family responsibilities. Close to 20% had experienced some form of sexual and disparaging activity that had made them feel very uncomfortable. For example, a managing director of an information services company reported, “Working in maledominated organizations and dealing with a multitude of pre-conceived notions around what I was / was not available to participate in or capable of doing because I am a woman and later because I have a family.” Almost all (80%) of the participants felt the rise to success in their companies would have been easier for a man, although 56% believed there had been advantages to being a woman such as strong relationship skills, being less threatening, and standing out more.

Recommendations for new female leaders In answer to Research Question 3, the most relevant answers to assist the next generation of female leaders were about developing early confidence and helping create more support of women by women. Looking back, a significant portion (24%) of these very successful women would have liked to have more confidence earlier. An information services director said, “Waking up earlier in life with the knowledge that worry and fear of failure is pretty pointless in life and work would have helped.” The general manager of a healthcare organization located in Denver said, “I sometimes struggled with the decision to want to be in leadership. Friends, family and others would sometimes question my loyalty to my family and myself (selling out for the money). I think having more confidence in my ability to stay balanced and focused on what was important to me, if I could have been more confident on this early on would have made this road easier. My relationship and closeness with my family has stayed intact and in many cases is better than many of my friends who were stay at home moms.… [I]f I had known then that it would all be ok—would have been easier.” “While I believed in myself at an early age, it took me longer than I hoped to trust my talents,” said a healthcare CEO. A CIO said, “I would not have been so fearful early in my career—and I would have asked more for what I wanted. I’ve learned it never hurts to ask for what you want!”

Women’s Journeys to the C-Suite and the Emotional Component of Success

When asked directly about improvements needed for the next generation of female leaders, these C-Suite women mirrored the literature. Specifically, they stressed the importance of creating more female-friendly CEO-track jobs, especially for young women. Also noted were more female mentors and role models (22%) and women supporting women (20%) as a foundation for emerging leaders. “Creating opportunities for other females to lead,” responded the head of a UK business school. And, as an owner of a healthcare business said, “Support and sponsorship are essential to success to all budding leaders in the junior executive ranks, in particular to women.” There is a need for continued dialog and effort to destroy the underlying bias to promoting women: “I think we need to continue this conversation and focus on expanding the dialogue around many of the questions asked in this survey. I think including men in the process who are also in senior leadership roles would benefit both sides of the conversation and continue to progress the conversation, create understanding and generate opportunities to grow,” said an owner of a healthcare organization. As a last word, one executive summarized, “Female leadership is living an exhausting life balancing on a razor’s edge of being smart, but not too smart, tough, but not a bitch, confident, but not full of yourself, vocal but not too opinionated, ambitious but not aggressive, agreeable but not weak, and the list goes on and on, it feels like I am constantly apologizing, qualifying every statement or opinion to soften its impact for fear of being judged by both men and women. It’s exhausting.”

DISCUSSION AND RECOMMENDATIONS The survey base was women who had risen to the top during the late twentieth century and the early part of the twenty-first century. Women starting their rise now may experience a different pathway, but it is likely that some of the emotions and sacrifices observed here would still be present. The results of this survey build on prior research but also provide dimension on the positive and negative emotions C-Suite women have had on their journey to the top. In addition the results bring into sharp focus how early in an executive’s life the path to leadership can start. The survey results put the role of mentors into perspective as important, but not the only factor that will make the journey to the top more attractive or compelling for young women. Most C-Suite women realized early on they were on a path to leadership, and they had managed to build the confidence that they could handle career success.

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The following actions can be taken to ease the path of future female leaders. 1. Future female leaders would benefit from comprehensive promotion of the positive emotional payback of a top job for a woman as well as some of the negative ones. Recent studies in the United States, United Kingdom, and Germany (Delaney, 2016; Hewett and Marshall, 2014) show that close to three quarters of women without power do not see an opportunity to flourish with it. More stories of actual female CEOs need to be told. This recommendation is directed more to what happens within organizations than a request for media coverage, although that is also helpful. Most organizations have cultures created by men for men, as one study respondent observed, making pathways to leadership for women obscure. Culture change is a long process, measured in years (Dawson, 2010; Kotter, 1996), and requires input from many sources. Programs that allow direct contact with high-achieving women, including mentorships, can show aspiring female leaders the value (and the price) of top jobs as well as pathways to achieve them. 2. More programs are required that would build confidence in girls and young women, especially for those eligible for and expressing interest in executive positions. A confidence gap between girls and boys has been documented (Ornstein, 2000), and it is not clear that girls growing up in the twenty-first century have been able to catch up with boys (Brzezinski, 2010; Kay and Shipman, 2014; Sandberg and Scovell, 2013). Future research needs to expand the sample to other countries and cultures besides those in English-speaking first-world societies. Minority women are likely to have additional issues that women from majority groups do not experience. Men’s voices also need to be heard on the topic.

REFERENCES 2013 Wwd Ceo Summit: Transformers (2013), 206.89. Retrieved from http://search.proquest. com/docview/1447241999?pq-origsite=summon. Ashforth, B. E., and Humphrey, R. H. (1995). Emotion in the workplace: A reappraisal. Human Relations, 48, 97–124. Berkovich, I., and Eyal, O. (2014). Educational leaders and emotions: An international review of empirical evidence 1992–2012. Review of Educational Research, 85 (1), 129–167.

Women’s Journeys to the C-Suite and the Emotional Component of Success Branson, D. M. (2010). The Last Male Bastion: Gender and the CEO Suite in America’s Public Companies. New York, NY: Routledge. Britanica Academic Online (2016). Biographies. Retrieved from http://academic.eb. Bureau of Labor Statistics (2016). Labor Statistics from the Current Population Survey, Washington, D.C.: US Government. Bureau of National Affairs (2016). Report on Salary Surveys. Arlington, VA: Bureau of National Affairs. Brzensinski, M. (2010). Knowing Your Value: Women, Money, and Getting What You’re Worth. New York, NY: Weinstein Books. Catalyst (2016a). Quick Take: Statistical Overview of Women in the Workplace. New York: Catalyst. Retrieved from http://www.catalyst.org/knowledge/statistical-overview-women-workforce. Catalyst (2016b). Women CEOs of the S&P 500. Retrieved from http://www.catalyst.org/ knowledge/women-ceos-sp-500. Chamorro-Premuzic, T. (2013). Why do so many incompetent men become leaders? Retrieved from https://hrb.org/2013/08/why-do-so-many-incompetent-men?utmconte...6bb&utmmedium=social&utm-source-twitter.com&utm-campaign-buffer. Dawson, C. S. (2010). Leading Culture Change: What Every CEO Needs to Know. Stanford, CA: Stanford Business Books. Delaney, K. (2016). Do women want to be CEO? Or is their goal thwarted by incongruous perceptions? Retrieved from http://theglasshammer.com/2016/08/17/do-women-want-to-beceo-or-is-their-goal-thwarted-by-incongruous-perceptions/. Dinh, J. E., Lord, R. G., Gardner, W. C., Meuser, J. D., Liden, R. C, and Hu, J. (2014). Leadership theory and research in the new millennium: Current theoretical trends and changing perspectives. The Leadership Quarterly, 25, 36–72. Elsaid, E. (2015). Comparing Outgoing Female CEOs with prior CEO experience to outgoing female CEOs with no prior CEO experience. The Journal of Applied Business Research, 31 (3), 809–820. Fairchild, C. (2014). Women CEOs in the Fortune 1000: By the numbers. Retrieved from http:// fortune.com/2014/07/08/women-ceos-fortune-500-1000/. Fitzsimmons, T. W., Callan, V. J., and Paulsen, N. (2014). Gender disparity in the C-suite: Do male and female CEOs differ in how they reached the top? The Leadership Quarterly, 25, 245–266. Goleman, D. (1998). Working with Emotional Intelligence. New York, NY: Bantam Books. Gondhalekar, V., and Dalmia (2007). Examining the stock market response: A comparison of male and female CEOs. Int Adv Econ Res, 13, 395–396. Gooty, J., Connelly, S., Griffith J., and Gupta, A. (2010). Leadership, affect and emotions: A state of the science review. The Leadership Quarterly, 21, 979–1004. Greenglass, E. R. (1993). Social support and coping of employed women. In S. E. Kahn and B. C. Long (eds.), Women, Work, and Coping: A Multidisciplinary Approach, 154–169. Montreal: Canadian Centre for Policy Alternatives. Hayer, S. K. (2015). A Qualitative Inquiry of Asian Indian Women’s Journey to Leadership. Irvine, CA: Brandman University.

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Sabra E. Brock and Sharon Rowlands Hewlett, S. A., and Marshall, M. (2014), Women Want Five Things, New York, NY: Center for Talent Innovation. Hurley, D., and Choudhary, A. (2016), Factors influencing attainment of CEO position for women. Gender in Management, 31 (4), 250–265. Ibarra, H., Ely, R., and Kolb, D. (2013), Women rising: The unseen barriers. Harvard Business Review, September, 61–66. Jordan, C. D. (2009). An Examination of Emotional Intelligence and Leadership Competencies among Black and White Female Middle Managers. Phoenix, AZ: University of Phoenix. Kay, K., and Shipman, C. (2014). The Confidence Code: The Science and Art of Self-assurance— What Women Should Know. New York, NY: HarperBusiness. Kolev, G. I. (2012). Underperformance by female CEOs: A more powerful test. Economic Letters, 117, 436–440. Korabik, K., McDonald, L. M., and Rosin, H. M. (1993). Stress, Coping, and Social Support among Women Managers. In S. E. Kahn and B. C. Long (eds.), Women, Work, and Coping: A Multidisciplinary Approach, 133–153. Montreal: Canadian Centre for Policy Alternatives. Kotter, J. (1996). Leading Change. Boston, MA: Harvard Business Review Press. Lean In and McKinsey&Company (2015, 2016). Women in the Workplace. New York, NY: Lean In and McKinsey&Company. Letherby, G., and Reynolds, G. (eds.) (2009). Gendered Journeys, Mobile Emotions. Farnham, UK: Ashgate. Marshall, J. (1993). Patterns of cultural awareness: Coping strategies for women managers. In S. E. Kahn, and B. C. Long (eds.), Women, Work, and Coping: A Multidisciplinary Approach, 90–110. Montreal: Canadian Centre for Policy Alternatives. Moeller, S. (2012). Sacrificing to “have it all”: Four extraordinary women explain how to balance work and family. HE BLOG. Retrieved from http://www.huffingtonpost.com/susan-moeller/ann-marie-slaughter_b_1625458.htm. Morgan, S. (2014). A phenomenological study of the use of psychological capital in the success of the executive woman’s journey. Minneapolis, MN: Capella University. Nicholson, N., and West, M. A. (1988). Managerial Job Change: Men and Women in Transition. Cambridge, MA: Cambridge University Press. Orenstein, P. (2000). Schoolgirls: Young Women, Self-esteem, and the Confidence Gap. New York, NY: Anchor Books. Palvia, A., Vähämaa, E., and Vähämaa, S. (2015). Are female CEOs and chairwomen more conservative and risk averse? Evidence from the banking industry during the financial crisis. Journal of Business Ethics, 131, 577–594. Peck, E. (2015). Do You Realize How Few Women CEOs Exist? Retrieved from http://www.huffingtonpost.com/2015/07/13/weber-shandwick-female-ceo_n_7771608.html. Piderit, S. K., and Ashford, S. J. (2003). Breaking silence: Tactical choices women managers make in speaking up about gender-equity issues. Journal of Management Studies, 40 (6), 1477–1503. Rhee, K. S., and Sigler, T. H. (2015). Untangling the relationship between gender and leadership. Gender in Management: An International Journal, 30 (2), 109–134.

Women’s Journeys to the C-Suite and the Emotional Component of Success Sandberg, S., and Scovell, N. (2013). Lean In: Women, work, and the Will to Lead. New York, NY: Alfred A. Knopf. Shaw, S., and Leberman, S. (2015). Using the kaleidoscope career model to analyze female CEOs’ experiences in sport organizations. Gender in Management: An International Journal, 30 (6), 500–515. Singhathepl, T., and Pholphirul, P. (2015). Female CEOs, firm performance, and firm development: Evidence from Thai manufacturers. Gender, Technology and Development, 9 (3), 320– 345. Slaughter, A. (2015), Unfinished Business: Women Men Work Family. Toronto: Random House. Spencer, D., Walby, K., and Hunt, A. (2012). Emotions Matter: A Relational Approach to Emotions. Toronto: University of Toronto Press. Stern, G. M. (2009). Triumphing without tears at male firms: Author urges female execs to curb their emotions. Investor’s Business Daily, 28 December, A06. Taylor, S. E., Klein, L. C., Lewis, T. P., Gruenewald, T. L. Gurung, R. R., and Updegraff, J. A. (2000). Biobehavioral responses to stress in females: Tend-and-befriend, not fight-or-flight, Psychological Review, 107 (3), 411–429. Worsham, S. S. (2010). Exploring the Lived Experiences of Women Behavioral Healthcare Executives: Journey to the CEO Suite. Prescott Valley, AZ: Northcentral University. Wright, E.M. (1996). Dancing on the Ceiling: A Study of Women Managers in Education. London: Paul Chapman Publishing.

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APPENDIX: INSTRUMENT 1. Would you prefer that we treat your individual responses confidentially or do we have your permission to identify you and your organization? 2. As a child did you envisage yourself in a leadership position like you are today? 3. Which best describes how you got your first senior management position. Tick one. a. I applied for a senior position and got it. b. I was asked to take on a senior role. 4. How do you think you acquired the skills necessary to lead an organization? a. I gained skills during education process, e.g., graduate school b. I did executive training. c. I learned on the job. 5. Did you have a mentor? If yes, male or female? 6. Have you ever applied for a job for which you did not have all the experiences but you felt you had the potential? 7. At what age was the turning point in your career? a. 20s b. 30s c. 40s d. 50s 8. Have you ever experienced gender bias? If yes, provide details. 9. What type of leader would your organization describe you as? Tick all that is relevant. a. Command and control b. Non-hierarchical c. Empathetic d. Other 10. What are the key factors you put down to your success? 11. Reflecting on your leadership journey, have there been sacrifices you have made? 11. If you had been male, do you think your road would have been easier? 12. Did you get advantages that you attribute to your being female? 13. What one change would have made it easier for you to be more successful?

Women’s Journeys to the C-Suite and the Emotional Component of Success

14. Please identify 5 words that you have experienced the most during your journey to becoming successful. a. Fear b. Anger c. Surprise d. Gratitude e. Hope f. Relief g. Excitement h. Feeling overwhelmed i. Pride j. Inadequacy k. Jealousy l. Discouragement m. Disappointment n. Frustration o. Other 15. What else would you like to add on the topic of female leadership?

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CHAPTER 5

Developing Information Technology Fluency in College Students: An Investigation of Learning Environments and Learner Characteristics1 NANCY B. SARDONE, PhD Georgian Court University

ABSTRACT

T

he confluence of powerful technologies of computers and network connectivity has brought explosive growth to the field of Information Technology



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Developing Information Technology Fluency in College Students

(IT). The problem presented in this study is whether the type of learning environment where IT concepts are taught to undergraduates has a relationship to the development of IT fluency and course satisfaction. The literature suggested that, if learning environments based on constructivist learning strategies were used, students would achieve IT fluency as well as those who studied in a traditional setting but they might be more satisfied. This paper is organized as follows. First, the problem is introduced followed by a review of the definition of IT fluency, then the paper moves to discuss learning environments and other associated factors relevant to this causal-comparative analysis. Next, the research design of the study is discussed, to include the four modes of inquiry used and the research questions that guided inquiry. A detailed data analysis follows, findings are presented, and the conclusion highlights the most important findings. Recommendations are geared to instructors in higher education business/technology programs interested in designing instruction in conjunction with constructivist learning environments.

INTRODUCTION The definition of information technology (IT) fluency has evolved over the past 25 years and continues to evolve, as we become a society increasingly dependent on information technology. Years ago, IT fluency was associated with the ability to write a computer program using COBOL or Assembly Language (Bartholomew, 2004), often in pursuit of a computer science degree. In 1983, with Microsoft’s announcement of their Windows operating system and graphical user interface, the definition of IT fluency became synonymous with software-skills ability (Board, 1999; Microsoft, 2005). While the demands associated with IT knowledge that are placed on college graduates are greater than they were even five years ago (Terrell, 2007), many in business technology programs in higher education still continue to define IT fluency as the ability to use computer software (Kaminski, Switzer, and Gloeckner, 2009; Kesten and Lambrecht, 2010). According to Kesten and Lambrecht (2010), part of the issue is that information technology as a field of study is not unique to business and requires preparation at a variety of levels. Kaminski et al. (2009) point out that a software-skills approach to IT fluency is too slim, and students do not retain software skill knowledge and/ or sequential processes when the IT curriculum is so narrowly defined. Earlier studies echo these findings (Bartholomew, 2004; Chen and Ray, 2004). Organizations need individuals with higher-order IT competencies since they depend on IT as a conduit to innovation, transformation, and competi-

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tion in a global society (Friedman, 2005; Gilpin, 2001; Moncarz, 2002; Terrell, 2007): “The preparedness and skill levels of its workforce are critical factors in the ability of the United States to stay competitive in the 21st century” (Klein, Cavanagh, Kay, and Meisinger, 2006, p. 12). As such, higher education needs to do a better job of equipping students as productive and knowledgeable technology workers, not only when entering the labor market, but to provide adaptability within the labor market (US Department of Labor, 1999). Perhaps, the lack of shared understanding of what it means to be IT-fluent has limited IT course curriculum development in higher education. A revised and more current definition still encompasses software proficiency, but expands it to include demonstrated knowledge of computer operations, networks, online resources, digital media, and programming (National Research Council [NRC], 1999; Snyder, 2003). IT competency continues to rank among the top applied skills sought in entry-level workers (Klein et al., 2006; Zhao and Alexander, 2002) as rapid technology deployment and dependency continues to drive up the worldwide need for a skilled workforce. Individuals possessing high-level IT skills and conceptual knowledge are favored in the hiring process as their ability to learn new technologies lessens the amount of training they will need (Klein et al., 2006; Zhao and Alexander, 2002). Armed with such competencies, workers would be able to grow their IT skills and knowledge over time while remaining an asset to their organization.

LITERATURE REVIEW IT Fluency An understanding that focuses on learning to learn IT is in stark contrast to a software-skills approach to IT fluency, which focuses on usage of technology’s tools. Studies that suggest software use represents IT fluency can result in false assumptions. Current studies evaluating the responses of Generation Y indicate that they are a powerful demographic group described as in a hurry to use grown-up tools such as computers, software, and the Internet (Montgomery, 2007). They have become highly effective at influencing their families’ consumer decisions, partly due to the shift from authoritarian to more permissive parenting styles. The Kaiser Family Foundation (2009) examines media usage among a nationally representative sample of youths, reporting that children ages 8 to 18 are exposed to almost 11 hours of media in a typical day, including more than 4 hours spent watching television content. A large survey reported

Developing Information Technology Fluency in College Students

by Speak Up (2009) found that young people are innovative users of technology and ultra-communicators, learn technology tasks at home with family support, demand up-to-date technology tools at school, and are frustrated with their teachers’ lack of technology innovativeness. The Pew Internet & American Life Project indicates that 76% of respondents, ages 18–29, use the Internet for school research, followed by games, email, and instant messaging (Fox, Anderson, & Rainie, 2005). The EduCause Center for Applied Research (ECAR) surveyed 27,846 undergraduates from 103 higher education institutions and reported they used their computer for an average of 18 hours per week to conduct school, work, and recreational activities (Borrenson-Caruso and Salaway, 2007). Yet, under the revised IT fluency definition, current college students’ conceptual knowledge of computer technology is in question. Three studies provide evidence of conceptual knowledge deficiencies among college students. Northwest Missouri State University reported that of the 191 students who took an IT proficiency exam, only 2% mastered it at an 80% rate (Hardy, Heeler, and Brooks, 2006). At a large Midwestern university, a survey of 91 students revealed that their own perception of their IT fluency was far greater than their actual levels (Wilkerson, 2006). 800 Quinnipiac University freshmen report they learned technology tasks at home with family support, and the researchers conclude that familial education may equip students to accomplish immediate goals, but it may not be sufficient to be successful in college and beyond (Hoffman & Vance, 2004). Based on their ability to influence their families’ consumer decisions regarding IT tools, demand for up-to-date technology tools, and desire to be taught using innovative techniques involving technology, one could conclude that the 1.7 million high school graduates who enroll in college every year come to the institution prepared with the technical skills, concepts, and capabilities needed for success in college and beyond (Blymier, Rockman, and Williamson, 2005). However, a huge difference exists between using a computer and understanding how it functions, which is important to the development of the higher-order thinking processes of sustained abstract reasoning and critical thinking needed to become IT-fluent (NRC, 1999; Snyder, 2003). Concepts taught in an IT course under the revised definition include computer organization and hardware, systems software, application software, communications and networks, and the history and social impact of living and working in an IT-based world. Table 1 provides a listing of more detailed topics taught in the course under study.

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Nancy B. Sardone Table 1.  Course Topics General Topic Area Computer Organization and Hardware Hardware Systems Software Application Software Communications and Networks History and Social Impact

Specific Topic Area Processing Components, Primary Storage, Peripherals, Architectures, Data Representation Operating Systems, Utilities, User Interfaces Word Processing, Desktop Publishing, Spreadsheets, Multimedia World Wide Web, Personal Communications, Network Access, Network Architecture, Data Communications History, Social Issues, Safety and Security, Careers

Researchers point out that an extended IT curriculum is required from early on: “Science and math are the universal language of technology. However, unless our kids grow up knowing that universal language, they will not be able to compete” in a global context (Friedman, 2005, p. 272). As a nation, US students continue to rank lower, on average, than their international peers in both math and science, out of 30 developed nations (Cavanagh, 2007). As IT is intertwined with math and science knowledge, the question as to how to effectively develop IT fluency in light of poor math and science skills becomes paramount. One solution can be the adoption of constructivist learning strategies. The literature suggested that if learning environments based on constructivist learning strategies were used, students would achieve IT fluency on a level with those who studied in the traditional environment, but course satisfaction would be higher than that of traditionally educated students. Therefore, the purpose of this research study was to examine the relationship between traditional and constructivist learning environments to IT fluency and course satisfaction in a course in which students were learning to become IT-fluent under the revised definition.

Learning Environment The theoretical framework of this study centers on conservative constructivism, the theory of how people learn that considers the engagement of learners in meaningful experiences as the essence of experiential learning (Forcier and Descy, 2002; Kolb, 1985; Wulf, 2005). Constructivist theory was chosen as the framework for this study due to its humanistic, engaging, and reflective tenets that are not commonplace in IT-related courses as they tend to attract students who are more oriented to traditional methods of instruction used in learning computer programming (Kolb, 1985; Lui, Kwan, Poon, and Cheung, 2004; Naps et al., 2002; Natvig and Line, 2004; Wulf, 2005).

Developing Information Technology Fluency in College Students

The term “conservative” describes the degree of constructivism manifested in the type of instructional methods chosen by the instructor, the frequency of their use, and the assessment of associated products. Constructivist learning theory does not dismiss the active role of the teacher or the value of expert knowledge, nor does it devalue grades. In this study, student products were graded and final course grades awarded. Constructivism is a recent development in cognitive psychology, influenced by the works of Bruner, Piaget, and Vygotsky (Kauchak and Eggen, 2003). It shifts learning from a passive transfer of information and collection of facts to active problem-solving and discovery. The type of environment that supports this learning theory is one where the instructor provides interactive, collaborative, and explorative learning activities through which students formulate and test their ideas, draw conclusions and inferences, pool and convey knowledge collaboratively. Importantly, constructivism focuses on the central role that learners play in constructing knowledge (Smaldino, Russell, Heinich, and Molenda, 2005). In contrast, the transmission model theory of learning suggests that students will learn facts and concepts and come to understand by absorbing the content of their instructors’ explanations or by reading content explanations/ definitions from a text and answering related questions. In this model, guided repetitive practice in a systematic and highly prescribed fashion through didactic lecture, teacher presentations, and lecture/discussion methods leads the student to mastery (North Central Regional Educational Laboratory, 1995). Most often, lessons taught using the transmission model are intended to direct the predetermined sequence of instruction (Maddux, Johnson, and Willis, 2001). The contrast between these two models has a long history in education, stemming from debates about progressive education. Current interest in learning models steeped in constructivist theory can be traced to the public and professional dialogues (Barr and Tagg, 1995; Cross, 1986) over alternative approaches to education reform that followed the publication of the Nation at Risk report (National Commission on Excellence in Education, 1983). A dynamic shift began to occur in education in the early 1990s with the call for a more literate workforce, able to make critical judgments and decisions. Curricula were reformed, foregrounding instruction that would make the students more able to apply critical thinking skills in the study of content areas. In response to the reform, a paradigm shift began to occur in higher education from a focus on providing instruction to a focus on producing learning. As such, two different learning environments appeared—traditional, using a transmission model and constructivist, using an active learning model of education

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(Ravitz, Becker, and Wong, 2000). The materials from, and student outcomes in these two environments were evaluated in this study. Studies in IT-related courses evaluating the influence of learning environments on academic achievement report that a focus on the learners typically brings favorable results. To explore which factors create the learning environment, five studies using different research methods were compared (survey and correlation, phenomena, observation, content analysis, and experiment), which helped triangulate the impact of learning environments on academic achievement and satisfaction. The results of these five studies indicate that the better the quality of the student-teacher interactions occurring in a facilitative and constructivist environment, the higher the satisfaction, confidence, and academic achievement of the student (Colbeck, Cabrera, and Terenzini, 2001; Demetriadis, Triantafillou, and Pombortsis, 2003; Gonzales, 2006; Lui et al., 2004; Whittington, 2004). However, there remains the possibility that students’ replies considered not only learning environments but also their associated methods, which may have influenced learning. In essence, studies leave open the question as to whether variables other than learning environment could affect IT fluency and satisfaction in a given learning environment.

Instructional Methods Instructional methods used by teachers in traditional and constructivist-learning environments share the general attributes of context, construction, and collaboration ( Jonassen as cited in Maddux, Johnson, and Willis, 2001) but differ in their centeredness. Traditional environments tend to be teacher-centered in design while constructivist environments tend to be student-centered. To get an idea of the instructional methods used in the learning environments under study, see Table 2 later in this paper. Contextual attributes include instructional methods that serve as mental bridges for learning. The purpose is to model the intention of the instruction for students, thereby allowing them to observe and reflect through the sharing of thoughts and ideas that provide for the consideration of alternate perspectives (Michael and Modell, 2003). One contextual instructional method is simulation, descriptions of events or conditions that often allow the user to change variables to see the impact of that change (Maddux et al., 2001). Simulations include computer animations, computer games, exercises, and assorted learning media that simulate learning experiences for students. Contextual methods were evaluated in a few studies mostly involving computer programming indicated mixed results.

Developing Information Technology Fluency in College Students

Two studies reported that creating animations helped students better understand concepts taught (Smith and Escott, 2004; Stasko, 1997), while another reported no statistically significant improvement when animations were used as teaching tools (Naps et al., 2002). In another study, computer game use was admitted favorable due to feedback providing instant gratification (Natvig and Line, 2004). Constructivist methods serve to build knowledge through worked examples such as writing, discussing, and reflection as a self-evaluation of progress toward conceptual understanding (Andrusyszyn and Davie, 2001). Research studies evaluated that involved construction strategies of writing, discussing, and reflection revealed positive results (Bhagyavati, Kurkuvsky, and Whitehead, 2005; Dugan and Polanski, 2006; Syrjala, 1996) due to the methods that allowed the sharing of experiences, which led to growth through refection of learned content. Collaboration methods serve to develop negotiation skills by establishing and interacting with peer groups (Maddux et al., 2001). The research studies evaluated revealed that group work helps students build awareness of self and others, citing listening skills, social skills, time management, and organizational skills as the top most improved skills (Backhouse, 2005; Ong, 2000; Whittington, 2004) developed through collaborative instructional methods. In summary, the studies discussed in the previous section indicated that the instructional methods used produced one or more of the following results via self-report: better understanding of concepts taught, increased motivation to learn, increased course participation, improved attitudinal disposition, and increased awareness of the self and how one learns. Although it is clear that students perceived these instructional methods as positive, it is not evident if the methods of instruction correlated with academic achievement. It is important to note that the results indicated in these studies may overestimate what students think they learned, as novel instructional approaches and self-report tools may be influencing factors. To check this hunch, the investigators in two of the nine studies measured student perceptions against instructor observations, confirming the stated results (Backhouse, 2005; Bhagyavati et al., 2005). Since positive findings were reported, it seems to be a given that undergraduates prefer to use active learning techniques in their college classrooms.

College Student Learning Preferences The 1.7 million high school graduates currently entering higher education have learning preferences of trial-and-error, similar to the way they grew up playing games on a Nintendo system and the like, and favor tactile and kinesthetic learning

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activities (Davis, 1999; Snyder, 2003). They represent a learning culture surrounded by digital tools—computers, software, the Internet, videogames, digital music players, video cameras, instant messaging, and cell phones, which are normally used daily for home and school (Kaiser Family Foundation, 2009; Speak Up, 2009). Although the paradigm shift to instructional methods that befit the learning preferences of today’s undergraduates began many years ago (Barr and Tagg, 1995; Cross, 2001), lecture is still the most widely used teaching method in undergraduate classrooms (Bok, 2005; “Faculty Survey of Student Engagement,” 2009). This method of teaching is still widely used, even when it is reported that academic success and failure depends not on student characteristics or teaching effectiveness alone, but on the interactions between the students and the learning environments, and the match between presented materials and how students process them (Abrantes, Seabra, and Lages, 2007; Drysdale, Ross, and Schulz, 2001; Young, Klemz, and Murphy, 2003). Further, student interest is realized by the interactions they have with their instructors, in an environment that provides an opportunity to ask questions, express ideas, and have open discussions in class. The key aspect to these interactions is instructor responsiveness (Abrantes et al., 2007). In a lecture-based classroom, student-teacher interactions are often limited. Use of classroom interaction parallels Chickering and Gamson’s (1987) framework, which outlines seven engagement indicators predicted to influence the quality of undergraduate students’ learning and their educational experiences. One of the principles most relevant to this study is the use of active learning techniques, which suggest that instructors use instructional methods that are effective, relevant, and satisfactory to motivate students to obtain better learning results.

Learner Characteristics The literature reports four factors known to affect students’ academic achievement in IT-related courses besides instructional methods. They are mathematical background, mathematical ability, cumulative grade point average, and learning style; these are referred to as learner characteristics. Discrete mathematics or calculus constitutes a significant factor in academic achievement in computing courses (Pioro, 2006; Wilson and Shrock, 2001). In the current study, mathematical background is defined as completing Calculus or Discrete courses. Studies reporting the mathematical ability of students, defined by the final grade on a high school math exam, were the top variable predicting academic

Developing Information Technology Fluency in College Students

achievement (Bennedsen and Caspersen, 2005). In the current study, mathematical ability was reported as math SAT score, a quantitative score received on the standardized mathematical SAT aptitude exam taken as a high school student, with a maximum possible total of 800 points. Cumulative grade point average (CGPA) is defined as the average grade earned by a student, determined by dividing the grade points earned by the number of credits attempted. It was the single largest factor in predicting the total points earned in a course that introduced fundamental technical aspects of personal computers (Kruck and Lending, 2003), and it correlated with academic achievement in an introductory computer end-user technology course (Chenoweth, 2005). Learning style refers to the ways in which thought is structured within an individual. Their behavioral consistency is a result of this structure (Goldstein and Blackman, as cited in Moldafsky and Kwon, 1994). Most learning style theorists place learning preferences in distinct dimensions or modes. To measure attributes, self-reported learning style instruments are most often used, such as Kolb’s inventory, which offers four different styles: accommodating, assimilating, converging, and diverging. There is a reported linkage between college-level learners with dominance in the assimilating and converging learning styles and academic achievement in IT-type courses using various iterations of Kolb’s classification. Results indicated that undergraduate students with a penchant toward the abstract conceptualization mode (found in Kolb’s assimilating and converging learning styles) performed better in the introductory computer science courses than students with other learning style preferences (Chamillard and Karolick, 1999; Chamillard and Sward, 2005; Goold and Rimmer, 2000; Hudak and Anderson, 1990; Thomas, Ratcliffe, Woodsbury, and Jarman, 2002). However, we still do not know enough about the relationship among all the learner characteristics in terms of how they interact with learning environment to influence academic achievement and satisfaction in IT-related courses. This was an important consideration in the current study whose main premise was that all types of learners may learn IT concepts better and experience higher levels of satisfaction when taught in constructivist environments.

RESEARCH QUESTIONS 1. What is the relationship between learner characteristics (math background, math ability, grade point average, and Kolb’s four learning styles: accommodating, assimilating, converging, and diverging) and IT fluency?

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2. What is the relationship between learner characteristics and course satisfaction? 3. What is the relationship between learning environment and IT fluency, after checking for any effects associated with learner characteristics? 4. What is the relationship between learning environment and course satisfaction, after controlling for any effects associated with learner characteristics? 5. How do learning environment and learner characteristics interact to explain IT fluency? 6. How do learning environment and learner characteristics interact to explain course satisfaction?

RESEARCH DESIGN This causal-comparative study explored the relationships between the independent variable of learning environment to the dependent variables of IT fluency and satisfaction of students in two non-randomized groups. In addition, further exploration determined whether any differences found between the two groups were explained by another difference that existed, specifically, the moderating variables of math background, math ability, cumulative grade point average, and/or learning styles. As is the case in causal-comparative research, the investigator did not attempt to control or manipulate any variables (Creswell, 2002). Instead, statistics were used to control for factors and to examine the combination of those factors that affected outcomes, specifically analysis of covariance.

Participants 294 undergraduates at a mid-size university in the New York metropolitan area, who had completed an initial computer course, received an email invitation to participate. Institutional consent for conducting the study was obtained. Modes of Inquiry Data describing students’ experiences and scores were collected using four instruments: (i) Kolb Learning Styles Inventory, (ii) Evaluation of Teaching Effectiveness, (iii) Departmental Final Exam, and (iv) Learner Characteristics. Numerous learning style inventories are available and were considered for use in this study. The candidates were Kolb’s Learning Style Inventory (Kolb

Developing Information Technology Fluency in College Students

& Kolb, 2005), Canfield’s Learning Style Inventory (1980), Dunn Learning Styles Model (Dunn, 1990), Myers-Briggs’ Type Inventory (Myers & McCaulley, 1985), and Felder-Soloman Index of Learning Styles (Felder & Soloman, 1991). After evaluating the aforementioned inventories, the Kolb’s Learning Style Inventory (KLSI 3.1) was chosen for applicability to research purpose and its recency and use on other studies. Kolb’s inventory is the most widely used learning styles model. It measures cognitive traits, which then categorizes learners as accommodators, assimilators, convergers, and divergers (Kolb, 1985). Kolb identified four types of learning modes and four learning styles, where learning style is the combination of two specific learning modes and is designed to help individuals identify the way they learn from experience. Kolb’s instrument contains twelve items that ask respondents to rank-order the four sentence endings in a way that best described their learning style. One sentence ending in each item corresponds to one of the four learning modes—concrete experience, reflective observation, abstract conceptualization, or active experimentation. Each of these modes is combined with another to form one specific learning style. Assimilating combines the modes of abstract conceptualization and reflective observation; accommodating combines the modes of concrete experimentation and active experimentation; converging combines the modes of abstract conceptualization and active experimentation; and diverging combines the modes of concrete experimentation and reflective observation. The four scales of Kolb’s Learning Style Inventory (KLSI 3.1) show good internal consistency reliability with Cronbach’s alpha coefficients for the four scales ranging from .77 to .84 and test-retest reliability greater than 0.9 in all cases (Kolb & Kolb, 2005; Stangor, 1998). The second instrument, Evaluation of Teaching Effectiveness, measures course satisfaction as experienced by students in a given course (Serva and Fuller, 1999). Eight constructs of the teaching dimension were included in this instrument: class organization, active learning, media use, grading fairness, workload, student perceived performance, instructor relationship with students, and instructor knowledge of the material (Appendix A). This particular instrument was selected for use because it included two new constructs, active learning and effective media use, which were important to the study. This instrument is a Likert scale, consisting of a series of items that indicate the degree of agreement or disagreement with the measured issue, each with a set of responses that indicate respondent opinion (Stangor, 1998). The Evaluation of Teaching Effectiveness Scale contained twenty-eight items, each a seven-point

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response continuum representing agreement, ranging from “strongly disagree” to “strongly agree.” The authors granted the researcher permission to use the instrument. The dimensions of the Evaluation of Teaching Effectiveness show fair internal consistency reliability using an Analysis of Covariance Structural method with coefficients ranging from 0.54 to 0.89 (Serva and Fuller, 1999). Convergent validity of this instrument measuring the extent of agreement between two different measures of a theoretical construct was determined according to statistical factor loading guidelines (Stevens, 1986). In addition, this instrument satisfied the statistical test for discriminant validity, which tests the null hypothesis that two constructs measure the same theoretical concept. The third instrument, a departmental final exam designed to measure IT fluency, was provided by Thomson Prometric, specifically, the Dantes Subject Standardized Test (2005), Introduction to Computing. Topics on the exam matched 80% of the course content. Three full-time faculty who taught the course, including the researcher, adapted the exam. The topics taught in the course, as well as what topics were assessed on this exam, are listed in Table 1. In the final version, the departmental exam consisted of fifty objective, single-best-answer, multiple-choice questions. This multiple choice assessment format was chosen based on the assertions that converging and assimilating learners have a performance advantage when this type of format is used (Kolb, 1985; Newland and Woelfl, 1992). The idea was that if students other than those with converging and assimilating learning styles scored higher on the final exam than those with these preferences, then the final exam scores may have been the result of factors other than learning styles. The departmental exam was administered to all students enrolled in the course. Each participant earned a score after taking the final exam. This score was taken as a dependent variable, IT fluency. The norming process for the Dantes Introduction to Computing test was completed by 550 students from higher-education institutions of various sizes ranging from large state universities to small private and community colleges. Scores ranged from 20 to 80; with a mean of 50; and a standard deviation of 10. The Kuder-Richardson 20 (KR-20) internal consistency reliability coefficient for this exam was 0.91. The fourth and final instrument used to collect data was the Learner Characteristics questionnaire (Appendix B). These questions pertained to students’ mathematical background, mathematical ability, and cumulative grade point average. Mathematical background was indicated with a “yes” or a “no” answer when asked whether the student had completed a calculus and/or

Developing Information Technology Fluency in College Students

discrete math course. Mathematical ability was indicated by the student as their SAT mathematical score. Last, students were asked to provide their cumulative grade point average (CGPA). Each of these was a moderating variable.

Procedures The researcher invited 294 undergraduates who had completed a required fundamental computer course to participate in this study. The email message informed students of the voluntary nature of the study and their right to withdraw at any point. The email message asked students to authorize the release of their final exam score to the researcher. The email message contained the survey attachments. Students who opted to participate in the research study completed: (1) the Kolb Learning Style Inventory, (2) the Evaluation of Teaching Effectiveness Scale, and (3) Learner Characteristics questionnaire. The surveys were then emailed back to the researcher. Follow-up via email took place after two weeks for each group. By the end of twelve weeks, 124 responses had been received. The respondents were compensated with a $10.00 gift card redeemable at the campus bookstore and offered a chance to win an iPod MP3 digital music player ($199 value) upon conclusion of the data collection process.

Data Analysis The independent variable, learning environment at two levels (traditional and constructivist), was a dichotomous categorical variable. Two of the moderating variables, learning styles (of which there were four different styles) and mathematical background (calculus and discrete math) were also dichotomous categorical variables. The other moderating variables of mathematical ability (SAT math score) and cumulative grade point average (CGPA) were continuous variables as were the two dependent variables, IT fluency and course satisfaction. Data describing students’ experiences and scores were collected using the four instruments. The Kolb Learning Styles Inventory had items that needed to be tallied and coded according to a key provided by The Hay Group, provider of the instrument. Learning styles were coded as (1) accommodating, (2) assimilating, (3) converging, and (4) diverging. Each participant received one of these codes based on their answers. The second instrument, Evaluation of Teaching Effectiveness Scale, had items that needed reverse coding. It was determined that the total score of the scale was 196. Each survey was tallied by adding the scores on each of the 28 items together to get one composite score per survey. Composite score on this instrument was one of the dependent variables, course

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satisfaction. For the third instrument, Departmental Final Exam, scores were obtained from course instructors after receiving permission from participants. The exam score was the dependent variable, IT fluency. The last instrument, Learner Characteristics questionnaire, had two items that needed recoding. Mathematical background indicating whether a student had courses in calculus and/or discrete mathematics were coded (1) for “yes” and (0) for “no.” Each of the statistical analyses was performed using predictive analytic software, SPSS for Windows (v15), with a minimum α of .05. An analysis of the ratio of cases to independent variables was performed, adhering to the suggested minimum requirement: N ≥ 50 + 8m, (where m is the number of IVs) (Tabachnick & Fidell, 2007). This assumed a medium-size relationship between the IVs and the DVs, α = .05 and β = .20. Based on this assumption, a sample size of 122 was sought: [122 = 50 + 8*9], where 9 was the number of IVs to include (1) learning environment, (2) moderating variables of math background, (1) SAT math score, (1) CGPA, and (4) learning styles. This was confirmed via an a priori power analysis for ANOVA using the software program G*POWER, where a sample size of 120 was recommended (Faul & Erdfelder, 1992). To assure the quality of the collected data, a data screening process was completed. This began with a frequency procedure establishing mean, standard deviation, and variance to explore and address any issues of missing data, outliers, normality of distribution, homogeneity of variance, and homogeneity of regression slopes using the SPSS Explore function. Due to the existence of asymmetric suspicious outliers, four cases were eliminated from the sample, improving the distribution significantly, thus reducing the sample to 120 cases; 53 students in the traditional and 67 students in the constructivist-learning environment. Q-Q plots revealed normal distributions for both of the dependent variables. To confirm that students in the traditional learning environment and the constructivist learning environment were comparable, independent samples t-tests were conducted (p = .05 level of confidence). These tests compared the two groups on potentially relevant variables of learning styles, cumulative grade point average, math background (discrete math and/or calculus), and mathematical ability (SAT math score). Data on these variables were collected from the Learner Characteristics questionnaire and the Kolb Learning Styles Inventory. There were no significant differences between the students in the two learning environments with respect to learning styles, cumulative grade point average, discrete math, and SAT math score. There was a significant difference between the two learning environments regarding the variable calculus, where

Developing Information Technology Fluency in College Students

more students in the traditional environment (M=.51; SD=.505) had a background in calculus than students in the constructivist learning environment (M=.27; SD=.447) (p=.007). To test for the existence of mean differences in IT fluency based on instructor, a one-way analysis of variance (ANOVA) technique was administered. Results indicated no statistically significant difference existed among the four instructors in relationship to IT fluency, F(3, 116) = 1.075, p = .363. To test the time of day the course met for mean differences in IT fluency, another one-way analysis of variance (ANOVA) test was conducted. The results indicated that no statistically significant difference existed between the time of day the section met and IT fluency, F(1, 118) = .066, p = .797. To determine if a relationship existed between the two dependent variables, IT fluency and course satisfaction, a scatter plot was created. The visual impression confirmed that the dependent variables, IT fluency and course satisfaction, were independent of one another; meaning that a score on one variable did not predict the score on the other variable. Therefore, any further analyses combining these two variables were not warranted. This was important to determine prior to running the data analysis because if the two dependent variables were related, a different statistical analysis would have been performed; specifically, a multivariate analysis of covariance (MANCOVA) technique. Research data needed to satisfy certain statistical assumptions before the analysis of covariance (ANCOVA) could be tested were confirmed. A preliminary ANCOVA was conducted to test for homogeneity of variance and homogeneity of regression slopes for both of the dependent variables to determine if significant interaction(s) between the covariates and the factors was present. Levene’s Test for equal variances indicated that variances between groups were fairly equivalent for the dependent variable, IT fluency, F(1, 118) = .098, p = .755. Levene’s Test for equal variances indicated that variances between groups were fairly equivalent for the dependent variable, course satisfaction, F(1, 119) = 2.449, p = .120. The test of the homogeneity of the regression slopes indicated no significant interactions between the factors and the covariates for effect on IT fluency or for effect on course satisfaction. To determine whether a relationship existed between the independent and dependent variables in this study, an ANCOVA statistical technique was used. Another ANCOVA was then further performed to determine if any differences found between the groups was explained by another variable(s); specifically, the moderating variables of math background, math ability, cumulative grade point average, and/or learning styles. This technique (ANCOVA) was

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chosen because it merged numerous statistical tests into one: analysis of variance, covariance, and linear regression. Since known predictors of IT fluency were included in the data set, the ANCOVA tested whether certain factors had an effect after removing the variance for which the quantitative predictors (covariates) accounted. Also, the ANCOVA technique allowed for the creation and analysis of any interactions between pairings of independent and moderating variables (Mertler and Vannatta, 2002). Interactions were created as a cross-product of the independent variable (learning environment) and the predictor variables. This determined the specific amount of variance that any of the moderating variables accounted for, beyond what had been previously explained.

FINDINGS Research Question One: “What was the relationship between learner characteristics (math background, math ability, cumulative grade point average, and Kolb’s four learning styles: accommodating, assimilating, converging, and diverging) and IT fluency?” To answer this research question, an analysis of covariance (ANCOVA) was performed to fit a full model that included all learner characteristics to determine if a relationship existed between any of these variables and the dependent variable, IT fluency. The statistical significance of all eight variables was tested by the F ratio. The ANCOVA result indicated a significant main effect for cumulative grade point average, F(1,112) = 23.912, p < .000, partial η squared .176 and a significant main effect for SAT math, F(1, 112) = 5.908, p = .017, partial η squared .050. CGPA was higher in the constructivist group (M = 3.40; SD = .473) than the traditional (M = 3.27; SD = .522) and SAT Math was higher in the constructivist group (M = 541.19; SD = 80.74) than the traditional (M = 530; SD = 64.98). However, the results of the full model were contrary to the learning styles literature, where assimilating learning style is a well-founded predictor of academic achievement in IT-related courses. To take a closer look at this particular variable, a further reduced model was tested by the F ratio. The ANCOVA result indicated a significant main effect for cumulative grade point average, F(1,116) = 22.6, p < .000, partial η squared .163; a significant main effect for SAT math, F(1, 116) = 9.601, p = .002, partial η squared .076; and a significant main effect for assimilating learning style, F(1, 116) = 3.949, p = .049, partial η squared .033. In the reduced model, learning style was found to have a relationship with IT fluency, where students with assimilating learning style studying in

Developing Information Technology Fluency in College Students

the traditional environment scored higher on the final exam than other students in the traditional environment. Yet, the final exam scores for students in the traditional environment (M = .21; SD = .409) were not statistically significant as compared to the constructivist group environment (M = .18; SD = .386). It is important to note that the type of assessment used to measure IT fluency was a single-best-answer, multiple-choice exam, in which converging and assimilating learners have a performance advantage (Kolb, 1985; Newland and Woelfl, 1992). According to the research literature, with such a format the traditional group should have demonstrated statistically higher performance compared to students in the constructivist group, but this did not happen. Research Question Two: “What was the relationship between learner characteristics (math background, math ability, cumulative grade point average, and four learning styles) and course satisfaction?” To answer this research question, an ANCOVA was performed to fit a full model including all eight moderating variables associated with learner characteristics to determine if a relationship existed between these variables and the dependent variable, course satisfaction. The statistical significance of the eight variables was tested by the F ratio. ANCOVA result for the full model indicated a significant main effect for cumulative grade point average, F(1, 112) = 5.239, p = .024, partial η squared .045 and accommodating learning style, F(1, 112) = 4.939, p = .028, partial η squared .042. CGPA was higher in the constructivist group (M = 3.40; SD = .473) than the traditional (M = 3.27; SD = .522) and accommodating learning style slightly higher in the traditional group (M = .38; SD = .489) than the constructivist (M = .36; SD = .483). The relationship between cumulative grade point average and course satisfaction is supported in the literature and confirmed in this study, where statistically significant course satisfaction was found in the constructivist environment (M = 170.66; SD = 11.27) compared to the traditional environment (M = 164.61; SD = 13.80), p = .009. Research Question Three: “What was the relationship between learning environment and IT fluency, after controlling for any effects associated with learner characteristics?” To answer this research question, an ANCOVA was performed, adding the independent variable, learning environment, to the reduced model to determine if a relationship existed between the independent variable (learning environment) and the dependent variable (IT fluency) while controlling for known main effects (cumulative grade point average, SAT math, and assimilating learning style). ANCOVA result indicated no statistically significant relationship for any factors, as follows: learning environment and cumulative grade point average F(1,112) = 2.505, p = .116, partial

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η squared .022; learning environment and SAT Math F(1,112) = .869, p = .353, partial η squared .008; also, learning environment and assimilating learning style F(1,112) = .112, p = .738, partial η squared .001. Although IT fluency did not vary significantly with learning environment after controlling for the known effects, the learner characteristic factors of SAT math, assimilating learning style, and specifically, cumulative grade point average, may have outweighed any additional effects. Research Question Four: “What was the relationship between learning environment and course satisfaction, after controlling for any effects associated with learner characteristics?” To answer this research question, an ANCOVA was performed, adding the independent variable, learning environment, to the reduced model to determine if a relationship existed between the independent variable (learning environment) and the dependent variable (course satisfaction) while controlling for known main effects (cumulative grade point average and accommodating learning style). ANCOVA result indicated no statistically significant relationship for any factors, as follows: course satisfaction and cumulative grade point average F(1,114) = .023, p = .879, partial η squared .000; also, course satisfaction and accommodating learning style F(1,114) = .034, p = .853, partial η squared .000. Although course satisfaction did not vary significantly with learning environment after controlling for the known effects, it may have been the learner characteristic factors of accommodating learning style, and specifically, cumulative grade point average, outweighed any additional effects. Research Question Five: “How did learning environment and learner characteristics interact to explain IT fluency?” To answer this research question, an ANCOVA was performed, adding the interaction variables (each of the significant learner characteristics by learning environment) to the existing model to determine if a relationship occurred between the interaction variables and the dependent variable, IT fluency. The statistical significance of the independent variable was tested by the F ratio. ANCOVA result indicated no statistically significant interaction effect, F(1,112) = .159, p = .691, partial η squared .001. Research Question Six: “How did learning environment and learner characteristics interact to explain course satisfaction?” To answer this research question, an ANCOVA was performed, adding the interaction variables (each of the significant learner characteristics by learning environment) to the existing model to determine if a relationship occurred between the interaction variables and the dependent variable, course satisfaction. The statistical significance of the independent variable was tested by the F ratio. ANCOVA result indicated

Developing Information Technology Fluency in College Students

no statistically significant interaction effect, F(1,114) = .032, p = .858, partial η squared .000. To determine the type of activities that were designed for each learning environment, an analysis of instructors’ syllabi was completed. Attention was given to the type and frequency with which instructor practice matched the general attributes of instructional strategies: contextual, construction, and collaboration. Table 2 lists the types of activities used in the instructors’ practice, created to determine if differences existed in the teaching materials among the two study groups: traditional and constructivist. Differences were found in each of the three categories. In the contextual category, instructors who taught in the constructivist environment provided more opportunities for learning course content through student presentations, digital learning game play, and peer feedback than in the traditional environment. The traditional environment had a greater frequency of quizzes, lectures, and use of the direct instruction method of teaching. In the construction category, students had the opportunity to develop their online portfolio, write reflectively, and engage in both class discussions and media resources as a way to build their knowledge in the constructivist environment while the traditional environment asked students to perform more structured activities such as writing a research paper and responding to a provided ethical case study. Lastly, the number and type of collaboration activities varied by learning environment. The constructivist environment provided greater amounts of group work and problem-solving activities than the traditional environment, although this environment did provide the opportunity to work in pairs. To determine if the noted differences were statistically significant, an Independent Sample t-test compared participants’ responses on the Evaluation of Teaching Effectiveness scale, grouped by learning environment. The eight constructs of the teaching dimension included in this instrument were class organization, active learning, media use, grading fairness, workload, student perceived performance, instructor relationship with students, and instructor knowledge of the material. Differences were found on items within the dimensions of active learning, class organization, media use, workload, and student perceived performance. Statistically significant differences were found on items associated with the active learning dimension in terms of instructional methods used. On the item “instructor promoted discussion,” the means differed significantly at the p < .001 level (2-tailed), where students in the constructivist environment scored higher (M = 6.67; SD = .561) than the traditional group (M = 6.06;

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SD = 1.099). The next finding was that on the item “instructor raised challenging questions,” the means differed significantly at the p < .001 level, (2-tailed), where instructors in the constructivist environment scored higher (M = 6.13; SD = .796) than instructors in the traditional group (M = 5.08; SD = 1.385). Table 2.  Course Syllabi—Analysis of Strategies Used in Two Learning Environments

Instructor Number Contextual Strategies Virtual Simulations (Games, Exercises, Media, Computer Use) Lecture > 20 min Construction Strategies Peer Feedback Online Portfolio Development Research Paper Class Discussions Reflective Journals Case Study Collaboration Strategies Group Work Assessment Strategies Student Presentations Quizzes Final Exam

Constructivist Traditional Environment Environment 1 2 3 4 X

X

X X

X X

X X

X X

X

X

X

X

X

X

X

X

X

X

X

X

X (5) X (8) X X

Statistically significant differences were found on an item associated with the class organization dimension. Students in the constructivist learning environment (M = 6.37; SD = .648) reported a greater understanding of the course objectives than students in the traditional environment (M = 6.02; SD = .888), where the means differed on the item “course objectives were clearly defined,” statistically significant at p = .013 (2-tailed). On the media use dimension, the Independent Samples t-test indicated that the means on the item “instructor used media effectively,” differed significantly at the p = .040 (2-tailed), where instructors in the constructivist group (M = 6.78; SD = .487) scored higher than instructors in the traditional group (M = 6.51; SD = .823). Significant differences were also found on the item “media used helped make the course interesting” where the mean in the constructivist group (M = 6.27; SD = .863) was statistically significantly higher than the mean in the traditional group (M = 5.64; SD = 1.210), p = .002 (2-tailed).

Developing Information Technology Fluency in College Students

On the student perceived performance dimension, statistically significant mean differences (p = .031; 2-tailed) were found on the item “I learned a lot from the course,” where the mean in the constructivist learning environment (M = 6.09; SD = .917) was higher than the mean in the traditional group (M = 5.62; SD = 1.319). Interestingly, although the perceived amount of learning and clarity of expectations were significant in the constructivist group, the workload, another dimension, differed in the two environments. Items “course covered too much material” (p = .008, 2-tailed) and “assignments were too difficult” (p = .034, 2-tailed) were statistically higher in the constructivist environment. The item “course covered too much material” was higher (M = 3.85; SD = 1.672) than the traditional group (M = 3.02; SD = 1.704) and item “assignments were too difficult” was higher in the constructivist group (M = 2.07; SD = 1.172) compared to the traditional group (M = 1.68; SD = .850). These findings exposed learning differences in the two environments and indicated how these differences, tied to instructional methods and materials used in college classrooms, may have affected IT fluency. These findings are similar to prior research studies that suggested students learn more in environments where instructional methods are congruent with their preferences such as using active learning techniques.

CONCLUSIONS The major conclusion that can be drawn based on the findings of this study are constructivist—learning environments where active learning strategies are used negate the influence of preferred learning style. In addition, students are challenged by rigorous academic curricula and favor certain instructional methods and strategies, deeming them as significant to their learning. Finding One: There was no statistical difference in IT fluency based on the environment (traditional or constructivist), in which students studied. However, in the constructivist group, no relationship was found between an individual’s preferred learning style and IT fluency, meaning that active learning strategies negate the influence of preferred learning style. This is in contrast to the traditional learning environment, where students who had assimilating leaning style preferences performed better than other students who studied in the same environment. This finding indicates that active learning strategies found in constructivist environments meet the learning preferences of all students. Finding Two: Specific instructional methods and processes were perceived as more appealing to students studying in the constructivist environment.

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Therefore, it is suggested that the constructivist methods used were motivating, engaging, and fit the ways in which these students wanted to learn and interact with their instructor. Examples of the active learning methods used were student presentations, simulations and game play, peer feedback, development of online portfolios, use of media resources, reflective writing exercises, engagement in class discussions, and group work. The specific instructional strategies used by the instructors in the constructivist environment included (i) raising challenging questions for students, (ii) promoting discussion, (iii) using varied media effectively, and (iv) providing challenging assignments. There were some weaknesses in the research methodology used in this study. First, there was a decisive gap between the time participants completed the course and the time when asked to answer the survey questions, which is in line with the reflection literature. However, the amount of time given to each participant was not even. Some participants had two years, while others had six months to think about what they learned in the course. The correct amount or effects of an uneven amount of time provided to people to engage in reflective activities is, at present, not found in the reflection literature. Second, this was a sample of convenience in a university setting and students were required to enroll in the computer course. The generalizability of this study is limited insofar as the learning style inventory, course satisfaction survey, and learner characteristics are all self-report measures. Moreover, participants were enrolled at a mid-sized university in the New York metropolitan area that supports learning through information technology initiatives.

RECOMMENDATIONS The following recommendations are geared to two audiences: (i) instructors in higher education technology programs interested in designing instruction in conjunction with constructivist learning environments, and (ii) researchers. It is recommended that college instructors in business/technology programs consider using constructivist environments as they produce both high exam scores and high levels of course satisfaction and negate any learning style biases. Deployment of constructivist learning environments based on active learning strategies are advised in an effort for students to become IT-fluent and, thus, provide a foundation for adaptability within the labor market. An ITfluent student would have the skills, concepts, and intellectual capabilities related to information in terms of its representation, structure, organization, processing, transmission, distribution, and the technologies involved in the

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interactive execution of those activities—computers, networks, and software. IT fluency learned in a constructivist environment may increase the number of students attracted to math and science fields. Active methods of instruction engage students to the point where they are often unaware of how much they are learning at the time due to deep immersion in learning tasks. Yet, once students are asked to reflect, realization of the depth and breadth of their learning occurs. Since reflective thinking does not necessarily occur as part of natural undergraduate development, it is recommended that instructors model the reflective process and provide assignments that elicit self-evaluative responses. Within the constructivist environment, it is advised that the following active learning methods of instruction be used: student presentations, simulations and game play, peer feedback, development of online portfolios, use of media resources, reflective writing exercises, engagement in class discussions, and group work. The specific instructional strategies suggested for use in the constructivist environment include (i) raising challenging questions for students, (ii) promoting discussion, (iii) using varied media effectively, and (iv) providing challenging assignments deemed relevant for learning. An example of a learning activity designed for a constructivist environment would involve learning how digital data is represented and processed. First, students would watch a simulation teaching that computers only understand machine language and yet, input is made using “human language” via input devices like a computer keyboard. Students would watch and learn how letters on a computer keyboard are translated into data bits (binary code), which travel along a data bus on a computer motherboard. Then, actual laptop motherboards would be provided to students working in small groups. Students would be provided with a challenging task, such as determine the IPOS cycle (Input-Processing-Output-Storage) by identifying the data path from input device to processor to output device to storage device. Further, use of the Kolb Learning Styles Inventory is encouraged as it provides a starting point for curricular design. Results provide instructors with a window into their students’ individual and aggregate learning preferences and its use conveys a message of caring, creating the first of many student-teacher interactions advised for use in constructivist environments. A pre/postdesign is recommended for future research measuring students’ pre-course knowledge of IT concepts to determine if differences in IT fluency and course satisfaction at the end of the course are related to learning environment. Also, a qualitative study is advised; perhaps a case study following participants throughout a semester to gauge their level of conceptual IT knowledge.

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This may provide insight as to how they solve real-life IT problems and how learning style and learning environment are related to contextual problemsolving. In addition, other conceptual frameworks might provide an idea as to how motivated today’s students are to learn about IT concepts at the college level. The literature points to students as high technology users with low conceptual knowledge. As such, students may not be aware of how little they know about IT and when faced with the unfamiliar, they may lack motivation to learn. As a psychological construct, computer self-efficacy is believed to play a critical role in self-motivation, especially when a certain level of motivation is necessary to initiate coping with unfamiliar tasks. Therefore, it is recommended that students’ computer self-efficacy as a measure of motivation be determined pre-treatment to see if this variable affects IT fluency and/or course satisfaction.

REFERENCES Abrantes, J., Seabra, C., and Lages, L. (2007). Pedagogical affect, student interest, and learning performance. Journal of Business Research, 60 (9), 960–964. Andrusyszyn, M., and Davie, L. (2001). Facilitating reflection through interactive journal writing in an on-line graduate course: A qualitative study. Journal of Distance Education. Retrieved from http://cade.athabascau.ca/vol12.1/andrusyszyndavie.html. Backhouse, J. (2005). Learning individual group skills for software analysis and design in Africa. In Association of Computing Machinery. Proceedings of the SIGITE, 107–112. Newark, NJ. Barr, R., and Tagg, J. (1995). From teaching to learning—A new paradigm for undergraduate education. Change, 27 (6), 12–25. Bartholomew, K. (2004). Computer literacy: Is the emperor still exposed after all these years? Journal of Computing Sciences in Colleges, 20 (1), 323–331. Bennedsen, J., and Caspersen, M. (2005). An investigation of potential success factors for an introductory model-driven programming course. In Association of Computing Machinery, Proceedings of the 2005 International Workshop on Computing Education Research, ICER, 155–163. Bhagyavati, Kurkovsky, S., and Whitehead, C. (2005). Using asynchronous discussions to enhance student participation in CS courses. In Association of Computing Machinery, Technical Symposium on Computer Science Education, Proceedings of the 36th SIGCSE Technical Symposium on Computer Science Education, 111–115. Blymier, B., Rockman, I., and Williamson, D. (2005). Assessing students information and communication technology (ICT) skills: A new approach for higher education. Paper presented at Western Regional Conference, April 26–28, 2005. San Francisco, CA. Bok, D. (2005). Are colleges failing? Higher ed needs new lesson plans. The Boston Globe online, December 18. Retrieved from http://www.boston.com/news/globe/editorial_opinion/ oped/articles/2005/12/18/are_colleges_failing/?page=1.

Developing Information Technology Fluency in College Students Borrenson-Caruso, J., and Salaway, G. (2006). EduCause study of undergraduate students and information technology (ECAR), September. Retrieved from http://www.educause.edu /ers0706. Canfield, A. (1980). Learning styles inventory manual. Ann Arbor, MI: Humanics Media. Cavanagh, S. (2007). U.S. students fall short in math and science. Education Week online, December 18. http://www.edweek.org/ew/articles/2007/12/04/14pisa_web.h27.html?tmp= 1842637310. Chamillard, A., and Karolick, D. (1999). Using learning style data in an introductory computer science course. Association of Computing Machinery. Proceedings of the Thirtieth SIGCSE Technical Symposium on Computer Science Education, 31 (1), 291–295. Chamillard, A., and Sward, R. (2005). Exploring student learning: Learning styles across the curriculum. Association of Computing Machinery. Proceedings of the 10th annual SIGCSE Conference on Innovation and Technology in Computer Science Education, ITiCSE, 241–245. Chen, C., and Ray, C. (2004). The systematic approach in teaching database applications: Is there transfer when solving realistic business problems? Information Technology, Learning, and Performance Journal, 22 (1), 9–21. Chenoweth, J. (2005). Analyzing traditional factors for success in an introductory end-user technologies course. Information Technology, Learning, and Performance Journal, 22 (3), 21–29. Chickering, A., and Gamson, Z. (1987). Seven principles for good practice in undergraduate education. AAHE Bulletin, 39 (7), 3–7. Colbeck, C., Cabrera, A., and Terenzini, P. (2001). Learning professional confidence: Linking teaching practices, students’ self-perception, and gender. The Review of Higher Education, 24 (2), 173–191. Computer Science and Telecommunications Board (1999). Being fluent with information technology. Washington, D.C.: National Academies Press. Creswell, J. (2002). Educational research. Upper Saddle River, NJ: Merrill Prentice Hall. Cross, K. P. (1986). A proposal to improve teaching, or what ‘taking teaching seriously’ should mean. American Association for Higher Education Bulletin, 39 (1), 9–14. Cross, K. P. (2001). Leading edge efforts to improve teaching and learning. Change, July/August, 31–37. Dantes Subject Standardized Test (2005). Thomson Prometric. Retrieved from http://www.getcollegecredit.com/index.html#. Davis, P. (1999). How undergraduates learn computer skills: Results of a survey and focus group. THE Journal, 26 (9), 68–72. Demetriadis, S., Triantfillou, E., and Pombortsis, A. (2003). A phenomenographic study of students’ attitudes toward the use of multiple media for learning. Association of Computing Machinery. Proceedings of the 8th Annual Conference on Innovation and Technology in Computer Science Education, 35 (3), 183–187. Drysdale, M., Ross, J., & Schulz, R. (2001) Cognitive learning styles and academic performance in 19 first year university courses: successful students versus students at risk. Journal of Education for Students Placed at Risk, 6 (3), 271–289.

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Nancy B. Sardone Dugan, R., and Polanski, V. (2006). Writing for computer science: A taxonomy of writing tasks and general advice. Journal of Computing Sciences in Colleges, 21 (6), 191–203. Dunn, R. (1990). Understanding the Dunn and Dunn learning styles model and the need for individual diagnosis and prescription. Journal of Reading, Writing, and Learning Disabilities International, 6 (3), 223–47. Faculty survey of student engagement. (2009). Bloomington, IN: Indiana University Press. Faul, F., and Erdfelder, E. (1992). G*POWER: Apriori, post-hoc, and compromise power analyses for MS- DOS [Computer Program]. Bonn, FRG: Bonn University, Dept. of Psychology. Felder, R. M., and Soloman, B. A. (1991). Index of learning styles. Retrieved from http://www. ncsu.edu/felder-public/ILSpage.html. Forcier, R., and Descy, D. (2002). The computer as an educational tool: Productivity and problemsolving. Upper Saddle River, NJ: Merrill Prentice Hall. Fox, S., Anderson, J., and Rainie, L. (2005). The future of the internet survey. Pew Internet and American Life Project. Retrieved from http://www.pewinternet.org/pdfs/PIP_Future_of_Internet.pdf. Friedman, T. (2005). The world is flat. New York: Farrar, Straus and Giroux.Gilpin, R. (2001). Global political economy: Understanding the international economic order. Princeton, NJ: Princeton University Press. Gonzales, G. (2006). A systematic approach to active and cooperative learning in CS1 and its effects on CS2. Association of Computing Machinery, Proceedings of the 37th SIGCSE Technical Symposium on Computer Science Education, 133–137. Goold, A., and Rimmer, R. (2000). Factors affecting performance in first-year computing. Association of Computing Machinery. SIGCSE Bulletin, 32 (2), 39–43. Hardy, C., Heeler, P., and Brooks, D. (2006). Are high school graduates technologically ready for post-secondary education? Journal of Computing Sciences in Colleges, 21 (4), 52–60. Hoffman, M., and Vance, D. (2004). Computer literacy: What students know and from whom they learned it. Association of Computing Machinery. Proceedings from 36th SIGCSE Technical Symposium on Computer Science Education, 37 (1), 356–360. Hudak, M., and Anderson, D. (1990). Formal operations and learning style predict success in statistics and computer science courses. Teaching of Psychology, 17 (4), 231–234. Kaiser Family Foundation (2009). Generation M2: Media in the Lives of 8- to 18-Year Olds. Retrieved from http://slides.kff.org/chart.aspx?ch=1351 Kaminski, K., Switzer, J., and Gloeckner, G. (2009). Workforce readiness: A study of university students’ fluency with information technology. Computers & Education, 53, 228–233. Kauchak, D., and Eggen, P. (2003). Learning and teaching: Research-based methods. Boston, MA: Allyn and Bacon. Kesten, C., and Lambrecht, J. (2010). Future direction for business education: A Delphi study. Delta Pi Epsilon Journal, 52 (2), 57–76. Klein, D., Cavanagh, R., Kay, K., and Meisinger, S. (2006). Are they ready to work? Employers’ perspectives on the basic knowledge and applied skills of new entrants into the 21st century US workforce. Retrieved from http://www.21stcenturyskills.org/documents/FINAL_REPORT_PDF0929-06.pdf.

Developing Information Technology Fluency in College Students Kolb, D. (1985). Experiential learning: Experience as the sources of learning and development. Upper Saddle River, NJ: Merrill Prentice Hall. Kolb, A. and Kolb, D. (2005). The Kolb learning style inventory—Version 3.1 2005 technical specifications. Retrieved from http://www.hayresourcesdirect.haygroup.com/%20Learning_SelfDevelopment/Assessments_surveys/%20Learning_Style_Inventory/lsipercent20techpercent20manual.pdf. Kruck, S., and Lending, D. (2003). Predicting academic performance in an introductory college-level IS course. Information Technology, Learning, and Performance Journal, 21 (2), 9–15. Lui, A., Kwan, R., Poon, M., and Cheung, Y. (2004). Saving weak programming students: Applying constructivism in a first programming course. Association of Computing Machinery SIGCSE Bulletin, 36 (2), 72–76. Maddux, C., Johnson, D., and Willis, J. (2001). Educational computing: Learning with tomorrow’s technologies. Boston, MA: Allyn & Bacon. Mertler, C., and Vanatta, R. (2002). Advanced and multivariate statistical methods. Los Angeles: Pyrczak Publishing. Michael, J., an Modell, H. (2003). Active learning in secondary and college science classrooms. Mahwah, NJ: Lawrence Erlbaum Publishers. Microsoft (2005). Microsoft Windows history: Windows desktop timeline. Retrieved from http:// www.microsoft.com/windows/WinHistoryProGraphic.mspx. Moldafsky, N., and Kwon, I. (1994). Attributes affecting computer-aided decision making in a literature survey. Computers in Human Behavior, 10 (3), 299–323. Moncarz, R. (2002). Training for techies: Career preparation in information technology. Occupational Out- look Quarterly, Fall, 38–45. Retrieved from www.bls.gov/opub/ooq/2002/fall/ art04.pdf. Montgomery, K. (2007). Generation digital. Cambridge, MA: The MIT Press. Myers, I., and McCaulley, M. (1985). Manual: A guide to the development and use of the MyersBriggs type indicator (2nd ed.). Palo Alto, CA: Consulting Psychologists Press. Naps, T., Rößling, G., Almstrum, V., Dann, W., Fleischer, R., Hundhausen, C., Korhonen, A., Malmi, L., McNally, M., Rodger, S., and Velázquez-Iturbide, J. (2002). ITiCSE working group report: Exploring the role of visualization and engagement in computer science education. Association of Computing Machinery. SIGCSE Bulletin, 35 (2), 131–152. National Commission on Excellence in Education (1983). A nation at risk: An imperative for educational reform. Retrieved from http://www.ed.gov/pubs/NatAtRisk/index.html. Natvig, L., and Line, S. (2004). Age of computers: Game-based teaching of computer fundamentals. Annual Joint Conference Integrating Technology into Computer Science Education, Association of Computing Machinery, Proceedings of the 9th annual SIGCSE Conference on Innovation and Technology in Computer Science Education, 107–111. Newland, J., and Woelfl, N. (1992). Learning style inventory and academic performance of students in general pathology. Bulletin of Pathology Education, 17, 77–81. North Central Regional Educational Laboratory (1995) Creating high-achieving learning environments. Retrieved from http://www.ncrel.org/sdrs/areas/issues/educatrs/leadrshp/le400.htm.

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Nancy B. Sardone Ong, R. (2000). The role of reflection in student learning: A study of its effectiveness in complementing problem-based learning environments. Retrieved from http://discovery.rp. edu.sg/home/ced/research/papers/role_of_reflection_in_student_learning.pdf. Pioro, B. (2006). Introductory computer programming: Gender, major, discrete mathematics, and calculus. Journal of Computing Sciences in Colleges, 21 (5), 123–129. Ravitz, J., Becker, H. and Wong, Y. (2000). Constructivist-compatible beliefs and practices among U.S. teachers. Irvine, CA: University of California Center for Research on Information Technology and Organizations. Retrieved from http://www.crito.uci.edu/TLC/FINDINGS/ REPORT4/. Serva, M., and Fuller, M. (1999). The role of media use and active learning in higher education: The development of an instrument to determine the dimensions of teaching. Proceeding of the 20th International Conference on Information Systems, Atlanta, GA: Association for Information Systems, 386–399. Smaldino, S., Russell, J., Heinich, R., and Molenda, M. (2005). Instructional technology and media for learning. Upper Saddle River, NJ: Merrill Prentice Hall. Smith, G., and Escott, E. (2004). Using animations to support teaching of general computing concepts. Association of Computing Machinery, Proceedings of the Sixth Australian Computing Education Conference 2004, Dunedin, New Zealand, 270–275. Snyder, L. (2003). Fluency with information technology: Skills, concepts and capabilities. Boston, MA: Addison Wesley. SpeakUp (2009). Creating our future: Students speak up about their vision for 21st century learning. National Findings on Speak Up 2009. Retrieved from http://www.tomorrow.org /speakup/pdfs/SU09NationalFindingsStudents&Parents.pdf. Stasko, J. (1997). Using student-built algorithm animations as learning aids. Association of Computing Machinery. Proceedings of the SIGCSE’97, 25–29. Stangor, C. (1998). Research methods for the behavioral sciences. Boston, MA: Houghton Mifflin Harcourt. Stevens, J. (1986). Applied multivariate statistics for the social sciences, Hillsdale, NJ: Lawrence Erlbaum Associates. Syrjala, L. (1996). The teacher as a researcher. In E. Hujala (ed.), Childhood education: International perspectives. Oulu, Finland: Association for Childhood Education International, Oulu University. Tabachnick, B., and Fidell, L. (2007). Using multivariate statistics (5th ed.). Boston, MA: Allyn and Bacon. Terrell, N. (2007). STEM occupations: High tech jobs for a high-tech economy. Occupational Outlook Quarterly, Spring, 26–33. Retrieved from http://www.bls.gov/opub/ooq/2007/ spring/art04.pdf. Thomas, L., Ratcliffe, M., Woodsbury, J., and Jarman, E. (2002). Learning styles and performance in the introductory programming sequence. Association of Computing Machinery, Proceedings of the 33rd SIGCSE Technical Symposium on Computer Science Education, 33–37.

Developing Information Technology Fluency in College Students US Department of Labor. (1999). Futurework: Trends and challenges for work in the 21st century. A report of the US Department of Labor, US Government Respository. Retrieved from http:// dol.gov/dol/asp/public/futurework. Whittington, K. (2004). Infusing active learning into introductory programming courses. Journal of Computing Sciences in Colleges, 19 (5), 249–259. Wilkerson, K. (2006). Students’ computer literacy: Perception versus reality. Delta Pi Epsilon Journal, 48 (2), 108–120. Wilson, B., and Shrock, S. (2001). Contributing to success in an introductory computer science course: A study of twelve factors. Association of Computing Machinery, SIGCSE Bulletin, Proceedings of the thirty-second SIGCSE Technical Symposium on Computer Science Education, 33 (1), 184–188. Wulf, T. (2005). Constructivist approaches for teaching computer programming. Association of Computing Machinery. Proceedings of the SIGITE, 245–248. Young, M., Klemz, B., and Murphy, J. (2003). Enhancing learning outcomes: The effects of instructional technology, learning styles, instructional methods, and student behavior. Journal of Marketing Education, 25 (2), 130–142. Zhao, J., and Alexander, M. (2002). Information technology skills recommended for business students by fortune 500 executives. The Delta Pi Epsilon Journal, 44 (3), 175–189.

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APPENDIX A. Evaluation of Teaching Effectiveness Scale 1—“Strongly Disagree”; 2—“Disagree”; 3—“Disagree Somewhat”; 4—“Neither Agree Nor Disagree”; 5—“Agree Somewhat”; 6—“Agree”; 7—“Strongly Agree”.   1.   2.   3.   4.   5.   6.   7.   8.   9. 10. 11.

The course was well organized. The instructor promoted discussion in class. The instructor used media effectively. The exam questions were clear and unambiguous. The instructor was helpful and supportive. I was satisfied with this course. This course covered too much material. The instructor struggled with the course material. I learned a lot from this course. The course objectives were clearly defined. Instead of just listening to lectures, I was actively engaged in the learning process. 12. The media used in this course helped me learn. 13. The instructor provided help when asked. 14. I had adequate time to complete course work. 15. I didn’t learn much from this course. 16. The instructor returned graded assignments within a reasonable period. 17. The instructor was difficult to get along with. 18. The instructor is an expert in his/her field. 19. The course schedule changed so much that I was never sure what we were doing in class. 20. Assignments were unreasonably difficult. 21. The instructor treated students with respect. 22. Media were used in this course to effectively communicate course concepts. 23. The grading in this course was fair. 24. I was more of a participant in class than an observer. 25. The instructor was very knowledgeable. 26. The course was disorganized. 27. The media used in this course helped make the course interesting. 28. The instructor raised challenging questions for discussion in class.

Developing Information Technology Fluency in College Students

B. Learner Characteristics 1. 2. 3. 4.

Please fill in your SAT mathematical score: Number of mathematics courses taken to date: Titles of mathematics courses taken to date: Please fill in your cumulative grade point average (CGPA):

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CHAPTER 6

Toward More Practical Measurement of Teamwork Skills SABRA E. BROCK, PhD Touro College PETER J. MCALINEY, PhD Montclair State University CHUNHUI MA, PhD New York University

ABSTRACT

P

urpose—Given the growing importance of diverse international teams, there is a need to take a fresh look at how well instruments commonly used to calibrate teamwork skills reflect the reality of today’s workplace across cultures. Given the number of teamwork skills instruments that have been available for many decades, the question was, why still are so many workplace teams not successful? Design/methodology/approach—This practitioner exploration identified insights from a small group of experienced Indian managers on what makes a successful team. It compares these insights to the dimensions identified in one readily available practitioner developed teamwork skills instrument and to those characteristics identified in the literature.

Toward More Practical Measurement of Teamwork Skills

Findings—The match was less than perfect between the criteria these experienced managers used to predict team success and the combination of the dimensions in the literature and what the tool measured. Analysis indicated these managers felt that successful teams indeed required good communication among members (as identified in the literature), but they added the specificity that the element of communication characterized as effective listening was a key contributor to team success. Additionally, they did not just exhibit effective conflict resolution techniques (as identified in the literature), but also relied upon debate, discussion, flexibility, trust, and cohesiveness. The findings also suggested the importance of understanding each other’s strengths and weaknesses and of giving credit, which were not included on the instrument used. Originality/value—Given the growing importance of diverse international teams and the continued high failure rate of many teams, there is a need to take a fresh look at evaluating insights of successful team members using the additional lenses of culture, technology-enhanced communications, and distributed work approaches. These insights should be compared to those skills that have been historically measured by instruments commonly used to calibrate teamwork skills and described in the literature. If the measuring tools are accurate, why do so many teams fail? If instruments are to be useful in guiding improvement of teamwork skills, they need to calibrate the specific skills that differentiate success from failure in the today’s real world.

INTRODUCTION Teamwork has become the norm of today’s workplace, and teamwork skills are often cited as key criteria for hiring (Kelton, 2015). Team success is even more complex as teams have become more international and diverse, in their composition (Derven, 2016; Kerber and Buono, 2004). Researchers and practitioners working in multiple cultures and industries are striving to identify the characteristics of high performing team members in order to increase the productivity of this important resource (Derven, 2016). However, despite decades of studying teamwork skills, many workplace teams are not successful (Kelton, 2015). There are myriad reasons that can be attributed to this, but one reason may be the difficulty of identifying specific skill gaps that, once found, can be addressed by training (Andrews, 2001; Kerber and Buono, 2004). To check the usefulness of available measuring tools for the workplace, we searched for a nocost, industry-agnostic instrument to identify gaps in teamwork skills. Despite an abundance of instruments available, finding one that had face validity was dif-

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ficult. Only one, developed by an Australian practitioner, was found described in the literature (Brock, 2013). This practitioner exploration examined the fit of that instrument and key teamwork skills in the literature to the experiences of a group of successful Indian managers.

TEAMS POPULAR, YES, BUT USEFUL? Teamwork skills are frequently required by employers (Dixon et al., 2010; Riebe et al., 2010). Training resources are being applied to enable development of team skills and by extension a more productive workforce (Lencioni, 2003). Despite the popularity of teams, 70% of workers say they have been on a dysfunctional team (Kelton, 2015). Lencioni (2003) cites five factors causal to dysfuntionality: absence of trust, fear of conflict, lack of commitment, avoidance of accountability, and inattention to results. A minority of teams do succeed and reports of team achievements range from sales teams in India (Sen, 2010), to teams in science (Disis and Slattery, 2010; Lotrecchiano, 2013), to academic teams in business (Kennedy and Dull, 2008; Riebe et al., 2010) and healthcare teams (Aarnio et al., 2010; Brock, 2013; Guthrie et al., 2006; Ofstad and Brunner, 2013). Hinsz (2014) suggests more carefully defined expectations of teams such that their best use is in information pooling and sharing, error correction, meta-knowledge, and reliability. He also counsels that teams are not always the best solution, realizing they are slow to action and experience coordination losses. Gratten (2007) purposes four factors for success: cooperative mindset, spanning boundaries, igniting purpose, and productive capacity. Teamwork can be defined as the “work done by several associates with each doing a part but all subordinating personal prominence to the efficiency of the whole” (Merriman-Webster, 2016). This definition is further refined by Levi (2007) and Hackman (2002).

EXISTING INSTRUMENTS TO MEASURE TEAM CHARACTERISTICS There are a number of commercial instruments to assess teamwork skills that are available for purchase. One of the more popular commercialized instruments is the Teamwork-KSA test developed by Stevens and Campion (1994). This instrument evolved from research into how to develop a selection test for staffing work teams. Having reviewed extensive literature on teams and groups, they identified knowledge, skills, and abilities (KSAs) for effective teamwork into five dimensions of teamwork characteristics: conflict resolution, collaborative

Toward More Practical Measurement of Teamwork Skills

problem solving, communication, goal setting and performance management, and planning and task coordination. Using standard test construction techniques, the test contained thirty-five multiple-choice items on hypothetical teamwork situations. They validated their instrument in a singular cultural setting with two studies using supervisors and peer ratings of job performance as the criteria. Their two studies (1994, 1999) showed that the Teamwork-KSA test correlated with the ratings of team performance. However, a key unexpected finding was the large correlation with employment aptitude tests, suggesting that the Teamwork Test has a significant general mental ability component. For this and other reasons, though widely used, the instrument’s validity has been disputed (O’Neill et al., 2012). There are other self-administered proprietary instruments (available at a cost) often used for measuring aspects of team skills (Brown, 2012; Furnham and Crump, 2007; Wiley, 1994). These include: • Acumen Team Skills. A multi-rater, 360-degree instrument that provides feedback on an individual’s team membership, contribution, and participation skills that can be used to guide personal growth and skill development (Guest and Blucher, 2016). • Myers-Briggs Type Indicator (MBTI). The MBTI applies the theory of psychological types described by Carl Jung to how individuals interact in teams. Through the categorization of an individual’s preferred behavior into four dimensions, seemingly random variation in behavior can be explained due to basic differences in the ways individuals prefer to use their perception and judgment along these four dimensions (Myers & Briggs Foundation, 2016). • Fundamental Interpersonal Relations Orientation (FIRO). Based on social need theory that all living things seek equilibrium between their basic needs and getting those needs met, the FIRO instrument help individuals understand these interpersonal needs and how these needs influence their communication style and behavior. This recognition can in turn improve their personal relationships as members of a team and enhance their professional performance (CPP, 2016a). • Thomas-Kilmann Conflict Mode (TKI). The TKI instrument evaluates an individual’s typical behavior in conflict situations along two dimensions: assertiveness and cooperativeness. Five different conflicthandling modes, or styles—competing, collaborating, compromising, avoiding, and accommodating—are identified for use in team settings (CPP, 2016b).

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There are also discipline-specific instruments for measuring team skills, but their focus on one specialized field limit their usefulness when trying to generalize beyond their field. For example, within the health care industry, Havyer et al. (2016) identify sixty-four instruments to identify team skills. Practitionerdeveloped instruments also exist, but have no published validation (Brock, 2013). Compendiums of reproducible team skills instruments are available (Parker, 1998; Harris, 1995), but the literature does not identify a free, easily administered and interpreted instrument that has been validated across different types of teams and in multiple workplace disciplines and cultures. One such instrument that met this criterion—free, easy to administer, with face validity (Gravetter and Forzano, 2012)—was developed by an Australian practitioner and cited in Brock, 2013. It is a practitioner’s instrument, used in teaching team skills in Australia and the United States (Brock, 2013). We administered this practitioner-developed instrument to a group of experienced managers. The intent was to augment the results it generated with their open-ended reflections about characteristics of successful and dysfunctional teams. The instrument had been developed in Australia, and so, a western framework (Australian) was applied to a population exposed to both western (British-colonized) and eastern (Indian) cultures. The full instrument can be found at the end of this article. Middle managers in a large Indian energy company were asked to respond on a five-point scale as to how frequently they express fifteen different behaviors in a particular group or team: • • • • • • • • • • • • • • •

I offer information and opinions; I summarize what is happening in the group; When there is a problem I try to identify what is happening; I start the group working; I suggest directions the group can take; I listen actively; I give positive feedback to other members of the group; I compromise; I help relieve tension; I talk; I ensure that meeting times and places are arranged; I try to observe what is happening in the group; I try to help solve problems; I take responsibility for ensuring that tasks are completed; I like the group to be having a good time.

Toward More Practical Measurement of Teamwork Skills

The teamwork characteristics identified on this instrument were used as a stimulus for discussion on gaps between the teamwork skills experienced as the characteristics of a successful team in the workplace to those identified in this instrument and in the literature. The research questions were the following. • What differences are there in lived experiences of successful team members from what is covered in the literature and existing instruments? • If there are differences, what are they?

EXPLORATORY RESEARCH METHOD A small, exploratory study was undertaken on February 27, 2015, at the corporate training facility of a large Indian energy company, among a group of sixteen middle managers. The participants typically had served on three to seven teams, the smallest comprising five and the largest—twenty-five members. They had experiences on both successful and unsuccessful teams. All were male, typical of middle managers in this organization, and had been selected for a full-day course at the corporate training center. The session was conducted in English although table discussions were largely in Hindi. Initially the group was asked open-ended questions to describe the factors important in a “great” team and also the ones that make for a “terrible” team. Definitions of “great” and “terrible” were not provided in detail, as an important aspect of the learning from this study would be inferred from how the participants characterized their team experiences along these two dimensions. They were given the opportunity to discuss their individual answers in teams of four before writing their individual answers on a white board. The facilitator, who was American, then presented research on dysfunctional team characteristics (Leoncini, 2003) and team stages (Tuckman, 1965). Each participant was asked to complete the “Team Work Skills Questionnaire” developed at the University of South Australia and previously used by Brock (2013) to measure teamwork skills of working professionals and continuing education teams. Participants on average fell into the self-scored rating of being at least an “effective team person.” This result was not surprising as all participants had served on successful teams as well as unsuccessful ones. After they completed the questionnaire, participants were asked which of the fifteen attributes in the questionnaire was most critical, second most critical, and third most critical to effective teamwork in their experience. They recorded these answers on different color post-its and displayed them on a wall

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of the classroom. The same process was followed for the one characteristic “most lacking” and the one “absolutely not important” to ineffective teamwork. After analysis of the numbered data, the answers to the open ended questions were examined to elucidate the numbers. Qualitative responses were analyzed thematically, looking for similarity in answers to elicit commonalities.

RESULTS When asked open-ended queries to articulate the important skills for a “real” team, these experienced managers elaborated on good communication as characterized by discussion, debate, and feedback with credit openly given. Members of a great team trust each other and show collaboration, flexibility, and openness with faith in the ability of the team to meet its target. The team strengths are aligned to goals, those goals are communicated, and then followed up on. The leadership is accepted by team members and is dynamic as well as collaborative. “Terrible” teams were characterized by lack of communication, alignment, trust, and leadership. Members have their own agendas and egos clash. Looking at the participant feedback on the fifteen dimensions of the questionnaire, rankings showed differences among the team characteristics (see Table 1). Table 1.  Ranging of Team Characteristics according to the Participants’ Feedback Most valued Active listening Trying to help solve problems

Least Valued Talking Offering information and opinions

Most Lacking Active listening

Taking responsibility for ensuring tasks completed Giving positive feedback

CONCLUSIONS AND RECOMMENDATIONS Compared to the instrument used and other instruments in the literature, the open-ended responses of what makes for a good team reinforced the five Stevens and Campion dimensions of communication, collaborative problem solving, conflict resolution, goal-setting and performance management. The managers’ highlighting of listening as key to successful teamwork puts new emphasis on which part of the communication team skill is most valued by practitioners.

Toward More Practical Measurement of Teamwork Skills

The need for debate and discussion as well as flexibility, trust and cohesiveness was an expansion beyond the need for simple resolution of conflict in the instrument used and the Stevens and Campion instrument. The need for surfacing debate and conflict as well as resolving it aligns with the Tuckman inclusion of conflict as an important stage in teamwork. The importance of building an environment of trust may be highly correlated with the ability to raise honest debate and well-intended conflict. These factors may represent an added dimension for an instrument measuring teamwork skills. Other possible additions may be the concept of understanding each other’s strengths and weaknesses as well as giving credit to each other.

NEXT STEPS This exploratory study sheds light on the currently perceived key elements in both successful and unsuccessful teams and points out the need to further investigate the match of freely available team skills instruments to real-world experience of what differentiates success from failure in workplace teams. Expansion of research to other cultures and other industries is necessary. Other free and available team instruments besides the one used also need to be evaluated to see if they more closely match the experiences of seasoned managers, who have participated in both successful and unsuccessful teams. There is also an apparent gap in knowledge about how organizations use the measurement of teamwork skills to improve the success rate of teams (Casse and Banahan, 2011). Proprietary vendors may publish results to this effect in order to sell their products and services. There may be a need to begin the process of building an instrument based on workplace experience in the twentyfirst century (Casse and Banahan, 2011). Such instrument would allow more effective team member selection and provide the ability to identify skill gaps better, so that effective training could be developed and delivered and progress measured.

REFERENCES Aarnio, M., Nieminen, J., Pyorala, E., and Lindblo-Ylanne, S. (2010). Motivating medical students to learn teamwork skills. Medical Teacher, 199–204. Andrews, A. L. (2001). Virtual teams and technology: The relationship between training and team effectiveness. Retrieved from http://search.proquest.com/docview/304715890 ?accountid= 12536 (accessed June 20, 2016).

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Sabra E. Brock et al. Brock, S. (2013). What research tells us about team projects in post-secondary business classrooms. In S. Brock, At the Intersection of Education, Marketing, and Transformation, 110–115. New York: Academic Press. Brown, J. G. (2012). Empowering students to create and claim value through the ThomasKilmann conflict mode instrument. Negotiation Journal, 28 (1). Casse, P., and Banahan, E. (2011). 21st century team skills. Training Journal, September, 11–16. CPP (2016a). Fundamental Interpersonal Relations OrientationTM. Retrieved from https:// www.cpp.com/products/firo-b/index.aspx (accessed October 10, 2016). CPP (2016b), Thomas-Kilmann Conflict Mode Instrument. Retrieved from https://www.cpp. com/products/tki/index.aspx (accessed October 10, 2016). Derven, M. (2016). Four drivers to enhance global virtual teams. Industrial and Commercial Training, 48 (1), 1–8. Retrieved from http://search.proquest.com/docview/1748737365?accountid=12536 (accessed June 20, 2016). Disis, M. L., and Slattery, J. T. (2010). The road we must take: Multidisciplinary team science. Science Translational Medicine, 2 (22), 1–4. Dixon, J., Belnap, C., Albrecht, C., and Lee, K. (2010). The importance of soft skills. Corporate Finance Review, 14 (6), 35–38. Retrieved from http://search.proquet.com /docview/751644804 (accessed May 22, 2012). Furnham, A., and Crump, J. (2007). Relationship between the MBTI and FIRO-B in a large British sample. Psychological Reports, 101 (3), part I. Gratton, L (ed.) (2007). Hot Spots: Why Some Teams, Workplaces, and Organizations Buzz with Energy—and Others Don’t. San Francisco, CA: Berrett-Koehler Publishers. Gravetter, F. J., and Forzano, L. B. (2012). Research Methods for the Behavioral Sciences. Belmont, CA: Wadsworth. Guest, C. W., and Blucher, S. (2016). Acumen Team Skills. Retrieved from http://www.humansynergistics.com/uk/products/team-development/acumen-team-skills (accessed October 10, 2016). Guthrie, J., Dance, P., Cubillo, C., McDonald, D., Tongs, J., Brideson, T., and Bammer, G. (2006), Working in partnership: Skills transfer in developing a cross cultural research team. Journal of Community Psychology, 34 (5), 515–522. Hackman, J. R. (2002). Leading teams: setting the stage for great performances. Boston, MA: Harvard Business School Press. Harris, P. R. (1995), Twenty Reproducible Instruments for the New Work Culture. Amherst, MA: HRD Press. Havyer, R. D., Nelson, D. R., Wingo, M. T., Comfere, N. I., Halvorsen, A. J., McDonald, F. S., and Reed, D. A. (2016). Addressing the Interprofessional Collaboration Competencies of the Association of American Medical Colleges: A Systematic Review of Assessment Instruments in Undergraduate Medical Education. Academic Medicine, 91 (6), 865–88. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/26703415 (accessed June 21, 2016). Hinsz, V. (2014). Teams as technology: strengths, weaknesses, and trade-offs in cognitive task performance. Team Performance Management, 21 (5/6), 218–230.

Toward More Practical Measurement of Teamwork Skills Kelton (2013). University of Phoenix survey reveals nearly seven-in-ten workers have been part of dysfunctional teams. Retrieved from http://www.phoenix.edu/new/releases/2013/01 (accessed February 11, 2015). Kennedy, F. A., and Dull, R. B. (2008). Transferable team skills for accounting students. Accounting Education: an International Journal, 27 (2), 213–224. Kerber, K. W., and Buono, A. F. (2004). Leadership challenges in global virtual teams: Lessons from the field. S.A.M. Advanced Management Journal, 69 (4), 4–10. Retrieved from http:// search.proquest.com/docview/231240197?accountid=12536 (accessed June 20, 2016). Lencioni, P. (2003). The five dysfunctions of a team: A leadership fable. San Francisco, CA: Jossey-Bass. Levi, D. (2001). Group dynamics for teams. Thousand Oaks, CA: Sage Publications. Lotrecchiano, G. (2013). A dynamical approach toward understanding mechanisms of team science: Change, kinship, tension, and heritage in a transdisciplinary team. Clinical and Translational Science, 6 (4), 267–278. Merriman-Webster (2016). Merriam-Webster’s Learner’s Dictionary. Retrieved from http:// www.meriam-webster.com (accessed November 20, 2016). Myers & Briggs Foundation (2016). MBTI® Basics. Retrieved from http://www.myersbriggs.org (accessed October 10, 2016). Ofstad, W., and Brunner, L. (2013). Team-Based Learning in Pharmacy Education. American Journal of Pharmaceutical Education, 77 (4), 1–11. O’Neill, T. A., Goffin, R. D., and Gellatly, I. R. (2012). The knowledge, skill, and ability requirements for teamwork: revisiting the Teamwork-KSA Test’s validity. International Journal of Selection and Assessment, 20 (1), 36–52. Parker, G. M. (1998), 25 Instruments for Team Building. Amherst, MA: HRD Press. Riebe, L., Reopen, D., Santarelli, B., and Marchioro, G. (2010). Teamwork: effectively teaching an employability skill. Education & Training, 52 (6/7), 528–539. Sen, A. (2010). Hindustan Petroleum’s structural analysis of current reality. Reflections, 6, 8–10. Stevens, M. J., and Campion, M. A. (1994). The knowledge, skill, and ability requirements for teamwork: Implications for human resource management. Journal of Management, 20, 503–530. Stevens, M. J., and Campion, M. A. (1999). Staffing work teams: Development and validation of a selection test for teamwork settings. Journal of Management, 25 (2), 207–228. Tuckman, B. W. (1965). Developmental sequence in small groups. Psychological Bulletin, 63, 384–399. Wiley, D. L. (1994). Developing managers in the former Soviet Union. International Studies of Management & Organizations, 24 (4), 64–82.

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University of South Australia: “Working in teams” online workshop. Handout: Teamwork skills questionnaire. My Name __________________________________ Working in teams

TEAM WORK SKILLS QUESTIONNAIRE1 Visualise a particular group or team you have worked in. Answer the following about how you responded within that group. There are no wrong or right ans­ wers and some answers you may need to guess at. A scoring table is set out below the questions for you to score your effectiveness as a team member. 1. I offer information and opinions. a. Very frequently b. Frequently

c. Sometimes d. Rarely e. Never

2. I summarise what is happening in the group. a. Very frequently b. Frequently c. Sometimes d. Rarely e. Never 3. When there is a problem I try to identify what is happening. a. Very frequently b. Frequently c. Sometimes d. Rarely e. Never 4. I start the group workings. a. Very frequently b. Frequently

c. Sometimes d. Rarely e. Never

5. I suggest directions the group can take. a. Very frequently b. Frequently c. Sometimes d. Rarely e. Never 6. I listen actively.

a. Very frequently

b. Frequently

c. Sometimes

d. Rarely e. Never



1 Questions 1–15 and scoring table source from “Working in teams” online workshop created by University of South Australia. Accessed January 2, 2012.

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7. I give positive feedback to other members of the group. a. Very frequently b. Frequently c. Sometimes d. Rarely e. Never 8. I compromise. a. Very frequently b. Frequently

c. Sometimes d. Rarely e. Never

9. I help relieve tension. a. Very frequently b. Frequently

c. Sometimes d. Rarely e. Never

10. I talk. a. Very frequently b. Frequently

c. Sometimes d. Rarely e. Never

11. I ensure that meeting times and places are arranged. a. Very frequently b. Frequently c. Sometimes d. Rarely e. Never 12. I try to observe what is happening in the group. a. Very frequently b. Frequently c. Sometimes d. Rarely e. Never 13. I try to help solve problems. a. Very frequently b. Frequently

c. Sometimes d. Rarely e. Never

14. I take responsibility for ensuring that tasks are completed. a. Very frequently b. Frequently c. Sometimes d. Rarely e. Never 15. I like the group to be having a good time. a. Very frequently b. Frequently c. Sometimes d. Rarely e. Never

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SCORING Score by awarding yourself the number of points shown in the Table on the following page. Put the score in the score column. Add the numbers together in the score column to discover your total score.

SCORING TABLE Question 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.

a 1 1 1 2 0 3 3 2 1 0 2 3 2 2 1

b 2 2 2 2 1 3 3 3 2 0 3 3 3 2 1

c 3 3 3 3 3 2 2 3 3 3 3 2 3 3 2

d 2 2 2 1 1 1 1 1 1 2 1 1 1 1 1

e 1 1 1 0 0 0 0 0 0 0 1 0 0 0 1 Total

Score

RESULTS If you have scored between 40 and 45 you are a very effective team person. If you have scored between 35 and 40 you are an effective team person. If you have scored under 35 it would be useful if you work on some of your team skills.

CHAPTER 7

The Impact of Group Support Systems on Corporate Teams’ Stages of Development MARGARETTA J. CAOUETTE, PhD Pace University BRIDGET N. O’CONNOR, PhD New York University

T

hrough this quasi-experimental field study, we investigated the impact of group support systems (GSS) on the development of two comparable corporate teams solving actual business problems. Tuckman’s stages of development were the lens through which we viewed the team-building process. Tuckman maintained that teams go through a developmental schemata of forming, storming, norming, performing, and adjourning, and suggested that the way teams develop has a direct impact on both their task and social outcomes. Literature related to GSS and group processes, group characteristics, and task complexity provided the bases for the questions offered. In this field study, meeting sessions were audio-taped, transcribed, and used to paint a picture of the meeting process; to better understand what happened, we interviewed participants. Findings indicate that the two teams developed quite differently and that GSS impacted all stages, but most noticeably, the storming stage. The commitment of the teams to the assigned task, group composition, and leadership were identified as moderating factors.

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INTRODUCTION Cooperative, consensus management in the form of work teams, ad hoc committees, quality circles, and self-managing work groups are replacing traditional hierarchical decision-making processes. Collaborative work strategies, or what Weisbord (1987) called whole-systems thinking, and what Peters (1987) called the consensus team approach, appear to have a distinct advantage over traditional, top-down management strategies. Teams inevitably get better results than a collection of individuals (Katzenbach and Smith, 1993). Because team members share resources and pool information (Driskell and Salas, 1992), coordinated teams experience greater productivity, use resources more effectively, and solve problems better than individuals (Parker, 1991). Teams are creative and innovative because they encourage organizational community spirit, which, in turn, unleashes the power of creative problem solving (Weisbord, 1987). Expanding on teams in the international workplace, O’Hara-Deveraux and Johansen (1994) asserted that teams are the basic business unit of the global economy. As more employees are becoming involved in whole systems and teams, the need for tools that support group processes is increasing. Such technologies are referred to genetically as groupware, with emphasis on the “group” as the human side is always more important than the “ware” (O’Hara-Deveraux and Johansen, 1994), or group support systems (GSS). GSS go by a variety of different names: group decision support systems (GDSS), computer support for cooperative work (CSCW), electronic meetings systems (EMS), or collaborative technology (CT). While Level 1 GSS include messaging, screen viewing, agendas, and voting‚ Level 2 GSS, such as Ventana Corporation’s GroupSystems V, include statistical features designed to help groups solve complex, unstructured problems. Level 3 Systems, currently being developed, include such tools as an automated counselor and Robert’s Rules of Order (Hsu and Lockwood, 1993). Level 2 GSS electronically support group processes by adding structure to group communication and processes. Teams using Level 2 GSS follow patterns similar to traditional group meetings with several distinctions. For example, when brainstorming, participants anonymously and simultaneously enter their ideas into networked computers in a shared, common work space equipped with a public screen for group viewing. The common work space also supports other group processes such as group writing, idea organizing, and voting. The system can perform data manipulation and statistical

The Impact of Group Support System

analysis as well as provide hardcopy printouts of the exact textual discussions (Vogel, 1990). Evidence exists that GSS tools have the potential to reduce conflict and improve satisfaction with outcomes. For example, GSS tools may support communication and participation among members, reduce domination by overpowering individuals, allow for individual differences, and lessen time wasting (Mosvich and Nelson, 1987; Mantei, 1991; Nunamaker, n.d.). Even in an investigation of a Level 1 system, members of the group using the GSS reported less individual domination and more confidence in immediate outcomes (McClernon and Swanson, 1995). Research and experience with decision making, however, indicate that effective decision making involves more than the benefits related to increasing user satisfaction with those decisions. Effective decision making may be dependent on a group’s ability to work as a team. Therefore, the process that groups go through in becoming a productive, functional team is an important issue to explore in organizations that rely on high-level GSS as a group communication and decision support tool.

PRIOR RESEARCH Much GSS research has been dominated by laboratory studies done in sametime-same-place settings made up of student populations solving structured problems. These studies have usually compared computer-augmented groups to non-computer-augmented groups and generally focused on several topics. These topics include technical issues such as facilities and software engineeringredesign (including system tools) and on outcomes described as perception of decision quality, the number of alternatives generated, the speed of decision making, and participant satisfaction. The broad questions have centered on whether computers and communication technology offer ways to aid groups (Adelman, 1984; Chidambaram, 1989; Connolly, Jessup, and Valacich, 1990; Dennis, 1991; Jessup, Connolly, and Galegher, 1990; Steeb and Johnston, 1981). As GSS has begun to find its way into organizational use, however, research has expanded to include field studies that have examined various group characteristics, specific tasks, or certain group processes as well as observing the fundamental adoption and assimilation of GSS in organizational settings (Dennis et al., 1990; Jarvenpaa, Rao, and Huber, 1988; Nunamaker et al., 1989). At the same time, distinctions among various groupware categories— GDSS, EMS, GSS, CT, and others—have begun to blend together as each

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type of system increasingly supports requirements of the other (Vogel, 1990). Possibly due to highly confidential organizational issues, few GSS field studies have reached publication (Eden, 1992), and we know of none that are based on a quasi-experimental design. Those that have been published discuss GSS as related to its efficiency, effectiveness, and participant satisfaction, not to the process of team development (Dennis et al., 1990; Jarvenpaa, Rao, and Huber, 1988; Nunamaker et al., 1989). Therefore, to develop a focus for an understanding of the impact of GSS on group processes, we relied on Tuckman’s stages of group development and reviewed the literature related to two distinct variables that are closely linked to group decision making—group characteristics and task complexity. This literature provides the framework for describing the assumptions and developing the questions that guided this exploratory investigation of how actual business teams develop with and without GSS support.

Stages of Group Development: Conceptual Framework To produce a generalizable model of the evolution of group life, Tuckman (1965) synthesized fifty-five studies of groups. His purpose was to uncover and classify themes common to all groups. Participants in the studies were therapy groups, human relations training or T-groups, and natural and laboratory-task groups. His original findings uncovered four developmental stages (forming, storming, norming, and performing) shared by all groups. Twelve years later, Tuckman and Jensen (1977) expanded the earlier group development model to include a fifth stage—adjourning—based on additional studies of group behavior. Tuckman’s theory says that teams attend to social and task realms or outcomes (the social outcome is “how” people feel about themselves, the meeting process, and the meeting task; the task outcome is the “what” or the content that people attempt to accomplish in a meeting environment) and go through five distinct stages of development. Stage I (forming) in the social realm involves testing what roles and interpersonal behaviors within the group are acceptable as well as building team trust and confidence. On the task side, members orient themselves to the assignment at hand. Stage II (storming) involves intragroup conflict and leadership struggles on the social side; the task realm requires emotional readying for the task demands. Stage III (norming) includes the emergence of group cohesion and harmony. The group begins to develop into a functioning unit. The task side exhibits open dialog among members, sharing of information,

The Impact of Group Support System

and generating alternative options and choices. Stage IV (performing) shows members actively involved in roles leading to problem solving. The team, now a pragmatic work unit, is engaged in intellectual activities progressing toward successful solutions or task completion. Stage V (adjourning) brings closure to the process as well as the group—the work is done and the group disbands. Table 1.  Kormanski and Mozenter Team Building Model1 Group Development Tuckman Task Behavior Stages Forming Orientation Storming Resistance Norming Communication Performing Problem solving Adjourning Termination

Relationship Behavior Dependency Hostility Cohesion Interdependence Disengagement

General Theme Awareness Conflict Cooperation Productivity Separation

Team Building Task Outcome Relationship Outcome Commitment Acceptance Clarification Belonging Involvement Support Achievement Pride Recognition Satisfaction

In 1987, Kormanski and Mozenter (1991) merged the concept of team building with Tuckman’s model of group development. For each of the five stages of Tuckman’s model, Kormanski and Mozenter designated a general theme followed by specific task and relationship team-building outcomes. Table 1 shows the Kormanski and Mozenter model, which provided the basis for coding of transcripts of the meetings and subsequent interview data.

GSS and Group Processes Jessup and Valacich (1993) called for the remodeling of a number of traditional group theories to fit the needs of groups supported by technology in the workplace. One traditional assumption is that tensions are often caused by internal group dynamics, and because of a fixed amount of resources, team members have a natural tendency to compete with one another. They asserted that this tension can be neutralized by providing participants with overlapping ways of sharing information with colleagues, especially through the use of GSS ( Jessup and Valacich, 1993). GSS can enhance group processes—all five stages—in a variety of ways. GSS can reduce, if not eliminate, the amount of communications needed to clarify procedural decisions, thereby speeding the forming process. Research has shown that the structure GSS provides actually reduces storming-conflict (Chidambaram, Bostrom, and Wynne, 1991; Weisband, 1992), especially

1 From Kormanski and Mozenter, 1991, p. 231. Reprinted with permission.

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in diverse groups (Chidambaram, and Kautz, 1993). Particularly in solving complex tasks, groups tend to spend a lot of time norming (Poole and Roth, 1989). Because GSS publicly displays outputs of meetings, individuals can better concentrate on what the content is rather than on who contributed it ( Jensen and Chilberg, 1991). Satisfaction with group processes has also been linked to the law of requisite variety ( Jensen and Chilberg, 1991), which infers that the more complex the problem, the more the contribution of all members supports effective problem solving—performing. Because use of the tools can help bring closure to tasks, the adjourning stage is supported. A need for heightened sensitivity to group dynamics has been called for, especially in the anonymous GSS environment (Dailavaile, Esposito, and Lang, 1992). We know meeting facilitation can reduce disorganized activity, and GSS can impose a structure on group processes (Broome and Keever, 1989). In fact, the role of facilitation on the success of team development has been identified as an important control variable—facilitated teams tend to be more productive than nonfacilitated teams (McClernon and Swanson, 1995). However, evidence exists that although GSS does not interfere with the development process, the anonymity factor sometimes serves to heighten, rather than reduce, differences, and increases conflict-storming (Broome and Keever, 1989). Other findings, such as those of a longitudinal laboratory experiment where students worked on business case analyses that involved strategic decisions, showed that GSS-supported groups were initially not as good as their manual counterparts at managing conflict, but by the end of the experiment, they handled conflict better (Chidambaram, Bostrom, and Wynne, 1991). The impact of an appointed leader versus a leaderless group has been investigated, with no definitive conclusions (George et al., 1990). Therefore, the following question appears. Question 1: If forming, storming, norming, performing, and adjourning are the important development stages that teams cycle through toward problem solving, do the stages still occur in the same order and intensity when teams are augmented with GSS? In particular, does the use of GSS allow teams to handle conflict better?

GSS and Group Characteristics Although it is well accepted that group characteristics—who is on the team— impacts group processes (Gist et al., 1987; Hackman, 1991). GSS research

The Impact of Group Support System

shows a general theme of the technology usually neutralizing the impact of group composition. Sometimes GSS characteristics, such as anonymity (Connolly, Jessup, and Valacich, 1990), are credited with breaking down communications barriers (Dennis, 1991). A note of caution was offered by Rao and An (1995), who suggested that teams with multiple experts have a stronger potential for conflict. Additionally, Dubrovsky et al. (1991) found that status effects were equalized in groups using technology. Similarly, in one longitudinal field study, groups using GSS changed over time—a willingness grew on the part of original members to include employees from differing managerial levels, departments, or both (Martz, Vogel, and Nunamaker, Jr., 1992). Other studies have shown that the greater the extent to which computer technologies are routinely used in other work situations, the greater the satisfaction with the GSS-supported meeting (O’Connor and Bronner, 1994). As a group develops and works together, it creates its own unique way of doing things. In general, teams that get off to a good start tend to improve and perform; those that get into trouble early on, spiral toward failure (Hackman, 1991). Therefore, the following question appears. Question 2: Working on the same problem, with and without GSS support, how do group characteristics impact team development?

GSS and Task Complexity GSS research is also replete with the findings that the greater the complexity of the task with regard to its importance and scope, the more research participants tend to rate high satisfaction with their experiences and with subsequent social and task outcomes (Adelman, 1984; Dennis et al., 1990). Groups using GSS have felt they generated better ideas than groups using only oral communications (Valacich, Paranka, George, and Nunamaker, 2019). In cases where team members have first anonymously entered recommendations and evaluations, which were then followed by conventional group discussion, the use of GSS tools has frequently resulted in higher quality decisions (Dorando, O’Donnell, Esposito, Gregory, and Lynn, 1994) generated in shorter time frames (Grohowski, McGoff, Vogel, Martz, and Nunamaker, Jr., 1990; Watson, DeSanctis, and Poole, 1988). However, other experimental studies have shown that in addition to high user satisfaction with outcomes, the use of GSS with tasks of varying levels of complexity has actually increased the time that a group spends on a specific task (Steeb and Johnston, 1981; Gallupe and

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McKeen, 1990; Chen, 1993), implying that no matter how complex the task, teams perceive the task to be worth their effort. Therefore, the following question arises. Question 3: Does the complexity of the task impact team members’ perceptions of the value of GSS in supporting team development?

The Research Method This quasi-experimental field study centered on equivalent small groups of executives who were solving actual problems, one strategic—a macro plan—and one more detailed—a micro plan. We looked at the impact of GSS on the team development of these corporate decision makers who routinely used information technologies in their jobs and who had historically been involved in business teams as the primary form of organizational structure (and who expect to work as teams in the future). This is one of the first quasi-experimental studies to investigate the effect of GSS on expert corporate teams in a nontechnological business solving authentic tasks. Information systems researchers have argued the need to triangulate data sources (Simon, 1989). In this study, transcripts of actual meetings and printouts of the GSS-supported meetings were used to describe what happened. Interviews were used to help understand the experiences of those involved. A key assumption is that reality is constructed by individuals within their social worlds (Simon, 1989), within their own local contexts (Miles and Huberman, 1984). Further, qualitative data are likely to lead to unexpected discoveries (Simon, 1989; Miles and Huberman, 1984). The study described here involves a purposeful site—a corporate environment for which GSS was intended— and a specific Level 2 GSS (Ventana Corporation’s GroupSystems V) technology. Information systems researchers have also recommended that we look at groups with a past and a future—nonzero history groups (Chidambaram and Kautz, 1993) and Study GSS and teams as they work in a real organizational context (DeSanctis et al., 1993). This professional work group came from a common social environment and was well suited to take advantage of tools to support collaborative work. Qualitative data have been called attractive because one can preserve chronological flow, assess local causality, and derive fruitful explanations (Miles and Huberman, 1984). The key data analysis techniques involved coding data from all three data sources: meeting transcripts, outputs, and interviews.

The Impact of Group Support System

The Site The site for this study was a specialized financial-guarantee insurance company based in New York City that agreed to participate anonymously. The company issues financial guarantees between partners worldwide, including securities, corporate obligations, borrowed money, and other financial commitments. The firm holds triple-A ratings from major rating agencies illustrating the company’s financial strength and dependability. Such ratings are normally given to massive organizations with long histories. This company, on the other hand, is small (approximately 100 employees) and is only 5 years old. Senior-level management identified productivity leading to increased profitability as an organizational canon, and productivity appears evident throughout the company. Many of the company’s employees (officers and staff members alike) are investors in the firm, and most of the officers receive annual performance bonuses based on productivity. These rewards provide additional incentives for effective teamwork leading to productive outcomes. Teamwork is the primary form of management decision making and organizational structure. Transactions are the deals the company makes; financial arrangements to borrow money, issue securities, or evidence indebtedness between parties. The teams make business decisions in as little as one or two meetings (duration of one or two hours), or as long as a year, depending on the task at hand.

The Teams and Their Tasks Two eight-member teams (referred to as Team A and Team B) participated in this investigation. The organization’s team coordinator, following company procedures, assigned team members to each team based on each member’s interest, expertise, availability, and training—wanting to learn or willing to teach. The team coordinator reported a conscious effort to ensure that members of both teams were comparable in expertise, status, tenure, and interest in participation in this study. The teams solved two business problems unique to the company. As shown in Appendix A, each team solved the same problem at the same time; one team used GSS and the other did not. Each team had an opportunity to use the GSS. In Session 1, the morning session, the team coordinator gave the two teams the same macro, global task. Their mission was to identify any segment of the company where productivity gains could be realized. Additionally, they were requested to rank the identified segments in order of importance. In Session 2, the afternoon

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session, the team coordinator gave the same teams another task, a micro task. This time they were asked to make detailed recommendations for implementing their Session 1 ideas, including a cost-benefit analysis of their recommendations. At the beginning of each session, the coordinator gave the appointed team leader a hardcopy document describing the problem that was to be solved and asked him or her to record the time when each meeting began and ended. In the first session (morning), solving Task 1, Team A was in the GSS room and Team B in the traditional room. In the second session (afternoon), solving Task 2, the teams were switched: Team B was in the GSS room and Team A in the traditional room (see Appendix A).

GSS-Supported Meeting Room Versus the Traditional Conference Room The GSS-supported team met with a trained technographer face-to-face in a U-shaped conference room equipped with networked microcomputers connected to a file server equipped with Ventana Corporation’s GroupSystems V. The file server was linked to a public screen displaying all members’ input and output. Each team member had a computer for entering data. All deliberations were publicly viewed on the large screen. The system recorded all data generated and later printed it out. The company conference room is where traditional meetings normally take place. This room was equipped with a large communal table and chairs; pens, paper, and Post-it® notes were the only tools used.

Results and Discussion Tuckman’s premise (1965) is that whereas various group compositions as well as the problems to be solved are different, all purposeful groups follow a pattern of developmental sequence from immaturity to maturity through five stages of development as they move to task completion. Furthermore, the way a group develops has a direct impact on the group’s outcomes. Following is a discussion of what was found framed around the research questions.

Question 1 Question 1: If forming, storming, norming, performing, and adjourning are the important development stages teams cycle through toward problem solving, do the stages still occur in the same order and intensity when teams are augmented with GSS? In particular, does the use of GSS allow teams to handle conflict better?

The Impact of Group Support System

All four meeting sessions were audio-taped and transcribed. Additional descriptors of the meeting were the hardcopy, verbatim system output of the two GSS-supported meetings. A coding sheet (see Appendix B), based on the Kormanski and Mozenter Model (Kormanski and Mozenter, 1991), as represented in Table 1, was used to analyze both sets of documents. To facilitate analysis and identify stages of development, the documents were time marked in 15-minute intervals and then coded. Two separate raters looked for words, sentences, patterns, and/or general overall themes identifying the particular stage each team was in during each interval. Raters noted these stages in the margins of all transcripts. Specific words or sentences in the transcripts that matched or fit the corresponding stages were underlined and noted. Once coded, each team’s development stages were mapped onto a line graph that showed each team’s stages of development over a time line. We also calculated the amount of time spent in each stage of development as well as the total time taken for task completion.

TASK 1 (COMPARING TEAM A TO TEAM B) In solving Task 1, Figures 1 and 2 show that both teams went through all five stages of team development and, in fact, were in the performing and adjourning stages the same number of times. Team A spent 3 hours 26 minutes on the task, and Team B spent 2 hours 26 minutes. As the figures show, when supported by GSS, Team A spent less time in the forming stage than Team B (10 minutes versus 20 minutes), completed their storming stage early in the meeting and, consistent with the literature related to solving complex tasks, spent the bulk of their meeting in the norming stage, interspersed with six periods of productivity (performing) before adjourning. Perhaps indicative of their commitment to the task, Team A worked through their break and worked longer than Team B. However, what is more apparent is that Team A was in the storming stage only twice and for 10 minutes compared to Team B, which took a break (in the middle of a storming stage) and spent a total of 51 minutes in the storming stage.

TASK 2 (COMPARING TEAM A TO TEAM B) As expected, both teams took less time to solve Task 2 (the micro task) than Task 1 (the macro task). In the traditional room, Team A spent 1 hour 15 minutes on the second task; with GSS, Team B spent 1 hour 8 minutes on the second task. Although the task complexity may have been a mitigating factor (the task was less complex), the differences, both in the stages of development that the teams

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1 12:26 12:20 12:15 12:10 12:00 11:45 11:30 11:15 11:00 10:45 10:30 10:15 10:10 10:00 9:50 9:45 9:35 9:30 9:20 9:15 9:10 9:00 8:45

0

Stages

Total Time (Min.) In Each Stage 10 10 110 75 1

Forming Storming Norming Performing Adjourning

Total minutes = 206 (3 hrs., 26 min.)

Figure 1.  Team A using group support systems on Task 1 (macro). Meeting time frame matched to stages of group development. Adjourning 5 Performing 4 Norming

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Storming

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Forming

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B R E A K

11:45 11:40 11:35 11:32 11:30 11:15 11:05 11:00 10:58 10:55 10:50 10:48 10:46 10:45 10:30 10:15 10:05 10:00 9:58 9:55 9:50 9:48 9:45 9:40 9:35 9:30 9:15

0

Stages Forming Storming Norming Performing Adjourning

Total Time (Min.) In Each Stage 20 51 37 37 1 Total minutes = 146 (2 hrs., 26 min.)

Figure 2.  Team B meeting without group support systems on Task 1 (macro). Meeting time frame matched to stages of group development.

The Impact of Group Support System

went through and the time spent in each stage, were profound. As Figures 3 and 4 show, without GSS, Team A was in the storming stage considerably more than Team B (62 minutes versus 5 minutes), and was in the norming stage less (8 minutes versus 15 minutes) and never reached the final stages of performing and adjourning. Team B was in the storming stage less; they were in the norming and performing stage more (45 minutes versus 8 minutes) before adjourning.

COMPARING TEAM A TO ITSELF (GSS MEETING TO TRADITIONAL MEETING) As Figure 1 shows, when supported by GSS, Team A went through all five stages of development, spending most of its time shifting between the norming and performing stages (with two intervals of the storming stage early in the meeting) before finishing at the adjourning stage. Without GSS, however, as Figure 3 shows, Team A worked less, went from the forming into the storming stage, fluctuated between the two stages of storming and norming, and never reached the performing or adjourning stage. Therefore, Team A did not progress through the same stages at the same speed; in fact, without GSS, they did not reach the last two stages of team development. In the afternoon session, after having had a productive morning, the team may have simply been tired; however, they continued to be very active. Moreover, the same group that had gotten along well in the morning and had been productive with GSS could not get along and were not as productive in the afternoon without GSS.

COMPARING TEAM B TO ITSELF (TRADITIONAL MEETING VERSUS GSS MEETING) As Figure 2 shows, in solving the macro task and without GSS, Team B went through all five stages of development, but frequently shifted between the storming, norming, and performing stages before adjourning. In the afternoon session, however, Team B spent considerably less time in the storming stage and shifted less frequently between the stages. The use of GSS appears to have made the process smoother.

COMPARING TEAM A TO TEAM B ON TASK 2 Although Team A when using GSS went through all stages of group development on Task 1, it did not reach the final stages of performing and adjourning

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1 3:15

3:00

2:50

2:45

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Stages

2:23

2:20

2:15

2:10

2:05

2:00

0

Total Time (Min.) In Each Stage 5 62 8 0 0

Forming Storming Norming Performing Adjourning

Total minutes = 75 (1 hr., 15 min.)

Figure 3.  Team A meeting without group support systems on Task 2 (micro). Meeting time frame matched to stages of group development. Adjourning 5 Performing 4 Norming

3

Storming

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Forming

1 3:15

3:00

2:48

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Forming Storming Norming Performing Adjourning

2:25

Stages

2:20

2:18

2:15

2:00

0

Total Time (Min.) In Each Stage 15 5 15 30 3 Total minutes = 68 (1 hr., 8 min.)

Figure 4.  Team B meeting without group support systems on Task 1 (macro). Meeting time frame matched to stages of group development.

The Impact of Group Support System

on Task 2. Team B with GSS on Task 2, went through all stages of development and spent less time in the storming stage, more time in the norming stage, cycled up through the performing stage, and then adjourned.

Questions 2 and 3 Although data related to Question 1 attempt to describe what actually happened, to obtain a better understanding of why the teams worked the way they did, we considered it vital to determine perceptions of the meetings from the individual members themselves. Therefore, answers to Questions 2 and 3 are grouped together for discussion here because they come from the same set of interview data.

Question 2 Question 2: Working on the same problem, but with and without GSS support, do group characteristics impact perceived group development?

Question 3 Question 3: Does the complexity of the task impact team members’ perceptions of the value of GSS in supporting task and social outcomes?

Fourteen of the total sixteen team members agreed to a personal interview (two members from the same team, Team B, declined). The interview guide (see Appendix C) and an interview data sheet, based on Kormanski and Mozenter’s group development and team building integration model, were validated by a panel of experts. The interview guide consisted of 15 questions, organized around three general themes: (a) general stages of development (Questions 1, 4, 7, 10, 13); (b) specific task outcomes (Questions 2, 5, 9, 11, 14); and (c) specific social outcomes (Questions 3, 6, 8, 12, 15). Each question was placed on an individual 5″ × 7″ card and directed to a team member during an interview session that typically lasted 1 hour. The interviewer gave each participant the pack of 15 cards and asked the individual to answer the questions by first indicating the degree using a 7-point scale ranging from 1 (interference) to 7 (support) to which they agreed or disagreed with potential responses. This method was used solely to encourage discussion and elaboration. In most cases, the interviewees took full advantage of the opportunity to elaborate. All interviews were audio-taped, transcribed, coded, and organized

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into the three themes. Additionally, responses were compared to what actually happened during the meetings. The analysis showed that the contrast between the two teams in their respective meeting environments was striking. When Team A used GSS, it progressed through all stages of team development to solve its task. When the system was not available, Team A seemed to go through withdrawal—spending considerable time in the storming stage, unable to reach the last two stages of team development. The team did not solve its task. In personal interviews, Team A members reported the system made a meaningful impact on the way their team developed. Team B, using the system or not, went through all stages of development, solved its first task and partially solved the second task, but spent more time in the storming stage when not supported by GSS. Interview data from Team B members, however, reported the system made little or no difference to the way their team developed. Indeed, the two teams in this study developed very differently and had markedly different reactions to the value of the GSS. Similar to Hackman’s (1991) findings, these teams varied widely in the developmental process following no universal order of a hierarchical, stepwise progression. Although change was constant, team development was neither steady nor gradual. Each team’s formation was influenced not only by its own uniqueness but also by forces encountered along the way, such as (unexpectedly) leadership, which was related to commitment to the task as well as each team’s composition. One of the most important requirements of a leader is not only to create favorable conditions to help the team get off to a good start, but also to maintain a favorable environment (Hackman, 1991). In the case of this study, each team leader began the meetings differently, ran the meetings differently, and in doing so, got the teams off to differing starts. Team B members mentioned lack of leadership and guidance (including not being introduced or guided in the use of the technology) as a stumbling block. Team B leader’s less-directive meeting management style coupled with a lack of familiarity with the use of GSS seemed to intrude on the team’s development process. Even though both team leaders were invited to meet with the system technographer to plan their electronic meetings, Team B’s leader did not participate. As a result, one teammate lamented that because they did not have proper guidance in either the meeting or on using the system, they “weren’t sure how much to use the system; several people desperately wanted to stop” and of feeling confused, “overleadered or underleadered” at times. As a result, many people shared, in “the organizing of the meeting.” He reported that the

The Impact of Group Support System

technology and the team leader increased team chaos rather than decreased it. Another member claimed that more guidance in using the system would have been helpful: “I think there was a weak spot in the [system] presentation and it was the technographer … and the team leader didn’t ask for any help from the technographer.” Team B’s leader demonstrated a less directive management approach, coupled with a lack of familiarity in running a computer-augmented meeting, which may have lessened her ability to conduct entire meetings, thereby offering some clues as to why Team B felt GSS made little or no difference to their team development. On the other hand, leadership was not referred to by any Team A member. Team A’s leader had a more directive management approach, planned the meeting agenda with the technographer, and selected appropriate system tools for supporting the meeting. He was able to successfully guide the team through the computer-augmented meeting. Without the system, Team A did not progress through all stages of development but became snared in the storming stage, unable to complete its task. In fact, one member said, In the afternoon [traditional] meeting, there were some emotional moments. I saw two people reacting to each other by almost telling each other to “shut up.” It was, “I’m speaking, you shut up.” “No, I’m speaking, YOU shut up!” That didn’t [happen] when we did the morning [GSS] session.

Furthermore, even though both teams went through all stages of development in the GSS-supported meetings, Team B spent less time performing than Team A, thereby indicating that leadership was an essential component in the successful team-development process. Katzenbach and Smith (1993), when writing about high-performance teams, maintain that at their core is a deep degree of commitment—to each member (p. 65) as well as the team’s common purpose (p. 37). Without it, teams perform as individuals; with it, they become a powerful unit of collective performance. In the case of these two teams, team commitment and task significance were issues mentioned by participants of both teams but from differing perspectives. Although several Team A members acknowledged both organizational tasks as meaningful and appreciated their teammates “really getting into it,” they were unable to complete their second task. Interestingly enough, they complimented each other’s commitment to solving both tasks. “I saw a real willingness to work on it. People wanted to fix it.” “This was important.”

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Furthermore, they were satisfied with the solutions they produced for Task 1. Responding to the same questions, one member from Team B, however, indicated that they were merely “given an assignment” rather than a “real-life meeting,” suggesting her team did not think the tasks unduly important and therefore were less committed to solving the tasks. Several Team B members accused their teammates of not taking the meetings or the system seriously: “A lot of people were doing hit-and-miss stuff. I don’t think there was enough serious give and take.” “People typed only what they wanted to [say],” ignoring the contributions of others. Finally, two members felt unsure as to whether their team came up with the right solutions, implying a lack of satisfaction with their derisions. “Did the team make the right decision? That, we weren’t too sure of.” “The technology didn’t help ... we arrived at decisions, I guess, but I don’t have any idea how we got there.” Team A, made up of what appeared to be committed members, worked as a unit—recognizing their tasks as significant ones. With GSS support, this team felt GSS had an impact on team development. The longer Team A members spent at their first meeting, the more directed and focused they became, and the more they performed. The system facilitated participants getting involved, becoming committed, digging deeply—searching for answers to a complex task—and feeling satisfied with their efforts. Team A members were involved in their task; Team B members were not. The perceived importance of a task is consistent with various studies focusing on task significance. Successful teams perceived their task to be important and were motivated to succeed (Hackman, 1991). Also, the more important the task, the greater the group’s perceived performance (Nunamaker et al., 1989), and GSS-supported teams participated more evenly (Dennis, 1991; Nunamaker et al., 1989; George et al., 1990). Other findings have shown that participants using GSS felt more satisfied and efficient with their efforts than groups not supported by GSS (Nunamaker et al., 1989), and groups solving difficult tasks felt their productivity improved when using the system (Gallupe, Bastianutti, and Cooper, 1991; Gallupe, 1985). Team A members spoke positively of working in an anonymous environment, supporting the findings of Nunamaker, Applegate, and Konsynski’s 1988 study showing that groups using GSS found the anonymous environment to be a benefit. “People felt that because they were anonymous, they could say almost anything.” “It allowed everyone to say what they wanted.” “You’re not reacting to what you’re hearing ... you think and reflect on the comments—on what you see,” not on the emotion. It takes “out the human emotional element,

The Impact of Group Support System

but leaves in the human thinking and creativity.” “Anonymity ... is a greater leveler.” “People made an effort to ... respect the idea.” On the other hand, similar to Noel’s study (1993), which found that groups operating in decreased levels of anonymity were more favorable in their evaluations of GSS for supporting the group process, several Team B members preferred the face-to-face meeting, disliked anonymous participation, and felt their time was wasted in this environment. “We accomplished a lot more in the morning than we did in the afternoon.” “No great insights came out as a result of people’s anonymous comments—just more wasted time.” Several members spoke of using the system in an underhanded way to “say things that you might not otherwise say face-to-face,” or “someone could write something down ... and you could shoot them down rapidly in an acerbic sort of way.” And finally, “The team felt it was easier to share information when we spoke to one another.” Interpretation for the disparate views between Team A and Team B members’ reactions to the anonymous environment may be found in other investigations with some groups who seemed less satisfied with the anonymous environment because they were looking for recognition of individual efforts (Dennis, 1991) and because anonymity and forced simultaneous contributions seemed to heighten differences and increase conflict [12]. It is possible that the experts who made up Team B performed as a group of individuals because they were looking for recognition of their own individual efforts rather than team efforts. Rao and An (1995) stated that multiple experts on a team may lead to increased conflict. Had Team B used GSS for solving its first task, before individual differences got in the way of team development, it is speculated that they may have been able to develop as a team. Hackman (1991) argued that the time available for a task not only guides the pace of a team’s work but also shapes the group’s climate and direction. If a team feels it is being efficient in the time available, the team strives toward higher productivity. Time was an issue, but from dissimilar points of view. Team A members wanted more time given the task size: “We had to put a time limit on it.” “We could have gone on much longer.” One member felt that because the team generated so much information “it took us some time to organize it all.” On the other hand, several Team B members felt their time was wasted using GSS and wanted less time on it: “I didn’t feel it enhanced the time we spent at all.” “Just more wasted time.” Team A, however, in the time available using GSS, began efficiently. The system tools facilitated member participation in an anonymous environment and the group focused, getting to work (norming) quickly. A high level of

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member participation produced forty pages of electronic meeting printout displaying numerous recommendations for solving their task. By contrast Team B, in its first session (a traditional meeting), produced only five pages of solutions and finished considerably earlier, suggesting a lower level of productivity than Team A. Additionally, the eleven pages of electronic meeting printout produced in the afternoon were austere and lean by comparison to Team A’s output, hinting at lower member participation. This finding is consistent with other studies that found that groups supported by the technology took longer to finish tasks suggesting that as member participation increases so does decision time (Steeb and Johnston, 1981; Gallupe and McKeen, 1990; Chen, 1993, Watson, 1987]. Team A, in the time allotted, supported by GSS became motivated, felt productive—and were. Taking longer than Team B, members actively participated—progressing through the stages of development to reach a high level of productivity. Bikson and Eveland (1990) found that the more tine group used technology, the more the group became impressed with the technology. Another study found that electronic groups felt more motivated to generate quality ideas than nonelectronic groups (Gallupe, Bastianutti, and Cooper, 1991). Without the system, Team A fell apart, reporting their preference for the system. Team B, meeting traditionally first, also went through all stages of development, but produced fewer solutions with less member participation than Team A. The morning climate seemed to set a precedent. In the afternoon they began tenuously on the system, did not feel appreciated for their individual efforts and were unable to complete their entire task. Working in the GSS room was a problem raised by several members of Team B. This was a puzzling reaction for two reasons. First, as this company uses many technological tools to support its work, we expected the employees working in an electronic environment would find it routine. Second, although members spent considerably less time in the storming stage in the electronic environment, they did not seem to realize this. The majority reported a preference for the traditional meeting room. In fact, several members said the GSS interfered with team development: “It just didn’t feel right in that kind of [computer] environment.” “Debating on the keyboard” was perceived as depersonalized and cold. One technologically sophisticated participant hinted at the team being somewhat amused by the GSS meeting environment: “There was some humor about the mechanicalness of a technology meeting.” It seems that the technology supported the team with a direction and commitment to goals. It was not useful to the team that had already spiraled downward.

The Impact of Group Support System

CONCLUSIONS Throughout this study, we saw the dynamics of two expert comparable teams as they worked on tasks with and without GSS. A strength of this study was that it investigated actual corporate teams solving real problems using a comprehensive Level 2 GSS, GroupSystems V. We were, indeed, fortunate to have access to an organization whose top managers were as interested in the results of this study as we were. By coding meeting transcripts, a picture of group development was drawn depicting the teams’ progression through their stages. Through individual interviews, that picture was supplemented with data that helped us understand why things happened when they did. Initially, we asked questions rather than made hypotheses because we truly were not sure how these technologically savvy, team-oriented experts would react to GSS. We found that the presence of GSS did affect team development, and in some ways that may have been anticipated—the impact of GSS was moderated by the group composition and the significance of the task. Moreover, in hindsight, we should not have been surprised by the impact of the leaders’ attitude toward the task and the technology: these individuals appear to have been pivotal to the effectiveness of the system on both social and task dimensions. First, with regard to the impact of GSS impact on these teams’ stages of development, we found that GSS can help a group get started (forming), but only when the group considers the task to be solved important. This initial stage, where the team, influenced by its leader, commits to the task is perhaps the most important factor relative to future stages. When any team gets off to a good start, it tends to perform better; good work begets more good work (performing). We were concerned that the anonymity feature might increase conflict among the teams of experts, but in actuality, GSS reduced the amount of time and the number of times that teams were in conflict (storming). Not too surprisingly, teams using GSS spent more time ensuring that they were together on the task (norming); the facilitation tools of GSS were apparent. We also suggest that these facilitation tools helped the teams disband because closure on the task was more apparent (adjourning). The order in which these tools were introduced, the differing complexity of the tasks, and the differing attitudes of the team leaders toward both the task and the technology may explain the marked differences between the development of these teams. Both teams began with the larger, macro task, but Team A started off on the system with a leader who had taken the time to familiarize

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himself with the technology and was enthusiastic about the activity. Team A members were very positive about their experiences and the value that GSS brought to their meeting process. By the time Team B had access to the technology later in the day, it had already been part of a group whose leader had not taken the time to understand the function of the technology or her own role. We were puzzled when we had evidence that GSS had a positive impact on Team B’s group processes—support in forming, more norming, less storming, more performing, and clearer adjourning—yet Team B members did not perceive any added value of the system. Perception may be reality to individuals, but not necessarily to outcomes. The team may have wanted to blame GSS to justify their acknowledged poor performance, or perhaps it was simply that Team B began unenthused about their task and the system, and that lack of enthusiasm transferred to their overall reactions to the day’s activities, including their use of GSS. Teams are increasingly making decisions in organizations; additional investigations focusing on how GSS impacts the effectiveness of decision making is ultimately tied to GSS’s ability to support teams on both task and social realms. Therefore, it appears that GSS atone cannot make a poor team function well, but may be able to make a good team become better. Clearly, longitudinal field studies should be done both to provide a moving picture of how groups experienced with GSS use it and to show the impact that technology has on overall social and task developmental stages.

REFERENCES Adelman, L. (1984). Real time computer support for decision analysis in a group setting. Interfaces, 14 (2), 75–83. Bikson, T. K., and Eveland, J. D. (1990). The interplay of work group structures and computer support. In J. Galegher, R. Kraut, and C. Egido (eds.), Intellectual Teamwork: Social and Technological Foundations of Cooperative Work, 245–290. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Broome, B., and Keever, D. (1989). Next generation group facilitation: proposed principles. Management Communications Quarterly, 3 (1). Chen, T. (1993). An experimental study of the effects of task training and group decision support systems on face-to-face decision-making processes and outcomes (decision support systems). Unpublished doctoral dissertation, University of Texas, Arlington. Chidambaram, L. (1989). An empirical investigation of the impact of computer support on group development and decision-making performance. Unpublished doctoral dissertation, Indiana University, Bloomington.

The Impact of Group Support System Chidambaram, L., Bostrom, R. P., and Wynne, B. E. (1991). A longitudinal study of the impact of group decision support systems on group development. Journal of Management Information Systems, 7 (3), 7–25. Chidambaram, L., and Kautz, J. (1993). Defining common ground: Managing diversity through electronic meeting systems. Proceedings of the International Conference on Information Systems, 1–11. Connolly, T., Jessup, L. M., and Valacich, J. S. (1990). Effects of anonymity and evaluative tone on idea generation in computer-mediated groups. Management Science, 36 (6), 689–703. Dailavaile, T., Esposito, A., and Lang, S. (1992). Communication in uncertain times: Groupware—one experience. Paper presented at the Fifth Conference in Corporate Communication, Madison, NJ. Dennis, A. R., Tyran, C. K., Vogel, D. R., and Nunamaker, J. F. (1990). An evaluation of electronic meeting systems to support strategic management. Proceedings of Eleventh International Conference on Information Systems, 35–52. Dennis, A. R. (1991). Parallelism, anonymity, structure, and group size in electronic meetings. Unpublished doctoral dissertation, University of Arizona, Tucson. DeSanctis, G., Poole, M. S., Dickson, G. W., and Jackson, B. M. (1993). Interpretive analysis of team use of group technologies. Journal of Organizational Computing, 3 (1), 2–29. Dorando, S., O’Donnell, L., Esposito, A. A., Gregory, D. S., and Lynn, R. I. (1994). Observations of computer-mediated groups in an R & D business environment. Proceedings of Office Systems Research Conference, 123–129. Driskell, J. E., and Salas, E. (1992). Collective behavior and team performance. Human Factors, 34 (3), 277–288. Dubrovsky, V. J., Kiesler, S., and Sethna, B. N. (1991). The equalization phenomenon: Status effects in computer-mediated and face-to-face decision-making groups. Human-Computer Interaction, 6, 119–146. Eden, C. (1992). A framework for thinking about group decision support systems (GDSS). Group Decision and Negotiation, 1 (3), 199–218. Gallupe, R. B. (1985). The impact of task difficulty on the use of a group decision support system. Unpublished doctoral dissertation, University of Minnesota, Minneapolis. Gallupe, R. B., and McKeen, J. ( January 1990). Enhancing computer-mediated communications: An experimental study into the use of a decision support systems for face-to-face versus remote meetings. Information and Management, 18, 1–13. Gallupe, R. B., Bastianutti, L. M., and Cooper, W. H. (1991). Unblocking brainstorms. Journal of Applied Psychology, 76 (1), 137–142. George, J., Easton, G., Nunamaker, J., and Northcraft, G. (1990). A study of collaborative group work with and without computer-based support. Information Systems Research, 1 (4), 394–415. Gist, M. E., Locke, E. A., and Taylor, M. S. (Summer 1987). Organizational behavior: Group structure, process, and effectiveness. Journal of Management, 237–257. Grohowski, R., McGoff, C., Vogel, D., Martz, B., and Nunamaker, Jr., J. F. (1990). Implementing electronic meeting systems at IBM: Lessons learned and success factors. MIS Quarterly, 14 (4), 369–384.

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Margaretta J. Caouette and Bridget N. O’Connor Hackman, J. R. (1991). Groups That Work (and Those That Don’t). San Francisco, CA: Jossey-Bass. Hsu, J., and Lockwood, T. (March 1993). Collaborative computing. Byte, 28, 112–120. Jarvenpaa, S. L., Rao, R. S., and Huber, G. P. (December 1988). Computer support for meetings of medium-sized groups working on unstructured problems: A field experiment. MIS Quarterly, 12, 645–665. Jensen, A. D., and Chilberg, J. C. (1991). Small Group Communication: Theory and Application. Belmont, CA: Wadsworth. Jessup, L. M., Connolly, T., and Galegher, J. (1990). The effects of anonymity on GDSS group process with an idea-generating task. MIS Quarterly, 14 (3), 313–321. Jessup, L. M., and Valacich, J. S. (1993). Group Support Systems: New Perspectives. New York: Macmillan. Katzenbach, J. R., and Smith, D. K. (1993). The Wisdom of Teams: Creating the High-Performance Organization. Boston, MA: Harvard Business School Press. Kormanski, C., and Mozenter, A. (1991). A new model of team building: A technology for today and tomorrow. In J. William (ed.), Working with Teams in Theories and Models in Applied Behavioral Science, volume 4, 227–237. San Diego, CA: Pfieffer. Mantei, M. M. (1991). Computer supported meeting environments. Paper presented at the Conference on Office Information Systems, Toronto, Canada. Martz, W. B., Vogel, D. R., and Nunamaker, Jr., J. F. (1992). Electronic meeting systems: Results from the field. Decision Support Systems, 8 (2), 141–158. McClernon, T., and Swanson, R. (1995). Team building: An experimental investigation of the effects of computer-based and facilitator-based interventions on work groups. Human Resource Management Quarterly, 6 (1), 39–58. Miles, M. B., and Huberman, A. M. (1984). Qualitative Data Analysis: A Sourcebook of New Methods. Newbury Park, CA: Sage. Mosvich, R. K., and Nelson, R. B. (1987). We’ve Got to Start Meeting Like This! Glenview, IL: Scott Foresman. Noel, T. D. (1993). Effects of anonymity on intact group performance and member attitudes in a group support system environment: An empirical assessment. Unpublished doctoral dissertation, Indiana University, 1993. Nunamaker, J. F., Dennis, A. R., Valacich, J. S., Vogel, D. R., and George, J. F. (n.d.). Electronic meeting systems to support group work: Theory and practice at Arizona. Working paper. Nunamaker, J. F., Applegate, L. M., and Konsynski, B. R. (1988). Computer-aided deliberation: Model management and group decision support. Operations Research, 36 (6), 826–848. Nunamaker, J. F., Vogel, D., Herninger, A., and Marlz, B. (1989). Experiences at IBM with group support systems: A field study. Decision Support Systems, 5 (2), 183–196. O’Connor, B. N., and Bronner, M. (1994). The role of electronic meeting systems in supporting curriculum development: A case study. Proceedings of PRIISM, 33–43. O’Hara-Devereaux, M., and Johansen, R. (1994). GlobalWork: Bridging Distance, Culture & Time. San Francisco, CA: Jossey-Bass. Parker, G. M. (1991). Team Players and Teamwork: The New Competitive Business Strategy. San Francisco, CA: Jossey-Bass.

The Impact of Group Support System Peters, T. (1987). Thriving on Chaos. New York: Harper & Row. Poole, M. S., and Roth, J. (1989). Decision development in small groups IV: A typology of decision paths. Human Communication Research, 15 (3), 323–356. Rao, J. R., and An, J. M. (1995). The effect of team composition on decision scheme, information search, and perceived complexity. Journal of Organizational Computing, 5 (1), 1–21. Simon, J. (1989). Transcript of the qualitative methods colloquium. In J. I. Cash and P. R. Lawrence (eds.), The Information Systems Research Challenge: Qualitative Research. Methods, volume 1, appendix I, 35–65. Boston, MA: Harvard Business School. Steeb, R., and Johnston, S. C. (1981). A computer-based interactive system for group decision making. IEEE Trans. on Systems, Man, and Cybernetics, 11 (8), 544–552. Tuckman, B. (1965). Developmental sequence in small groups. Psychological Bulletin, 61 (6), 384–399. Tuckman, B, and Jensen, M. A. C. (1977). Stages of small-group development revisited. Group and Organizational Studies, 2 (4), 419–427. Valacich, J. S., Paranka, D., George, J. F., and Nunamaker, J. F. (2019). Communication concurrency and the new media: A new dimension for media richness. Communication Research, in press. Vogel, D. R. (1990). Research on electronic meeting systems. In A. M. Jenkins, H. S. Siegel, W. Wojtkowski, and G. Wojtkowski (eds.), Research Issues in Information Systems: An Agenda for the 1990’s, 136. Dubuque, IA: Brown. Watson, R. I. (1987). A study of group decision support system use in three and four person groups for a preference allocation decision. Unpublished doctoral dissertation, University of Minnesota, Duluth. Watson, R. I., DeSanctis, G., and Poole, M. S. (1988). Using a GDSS to facilitate group consensus: Some intended and unintended consequences. MIS Quarterly, 12 (3), 463–478. Weisband, S. (1992). Group discussion and first advocacy effects in computer-mediated and face-to-face decision making groups. Organizational Behavior and Human Decision Processes, 53, 352–380. Weisbord, M. R. (1987). Productive. Workplaces: Organizing and Managing for Dignity, Meaning, and Community. San Francisco, CA: Jossey-Bass.

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APPENDIX A Task 1 (Macro)

Task 2 (Micro)

Team “A”

Team “B”

With GroupSystems Software

With GroupSystems Software

Team “B”

Team “A”

Without GroupSystems Software

Without GroupSystems Software

Figure A1.  The research design. Task 1 (on the left) is the morning session of the macro plan. Task 2 (on the right) is the afternoon session of the micro plan.



5

4

3

2

Acclimate Investigate Pursue Get directions Explain Disagree Interpret Define Clarify Question Share information Support each other Assist each other All participate Collaborate Working together Taking action Furnishing information Informing Finish job Complete task Reach end Stop

1

“That sounds good.” “What do you think?” “Try this....” “How about this idea.” “We did it.” “Good job.” “We’re done.” “Let’s go.”

“What are we doing here?” “What’s this all about?” “Let’s get this started.” “What’s the purpose?” “What do you mean?” “I don’t think you’re right.” “I mean ...” “This is dumb.” “I don’t understand.” “This isn’t clear to me.” “That’s interesting.” “I agree.” “Can you explain?” “Enlarge on that.”

What Team May Say

Members accepting of each other and interested in individual contributions.

Social Outcome3

Members feeling value and pride due to contributions. Members satisfied about team efforts. Members feel appreciated.

Members resolving, contributing, and accomplishing. Members recognizing that task is completed.

All members involved and partici- Members supportive of pating in decision-making process. individual differences.

Members asking for clarification to Members feeling connected and specific issues. joined to each other after initial struggle. Becoming part of a team.

Members committed to team goals.

Task Outcome2

2 Task outcome = the “what” or the content members attempt to accomplish in the meeting environment. 3 Social outcome = the “how” members feel about themselves, the meeting process, and the meeting task.

Orienting Searching Adjusting Acclimating Struggling Debating Disagreeing Resisting Opposing Clarifying Cooperating Communicating Sharing Informing Agreeing Producing Creating Solving Providing Terminating Separating Concluding Disbanding

What Team May Do

Stage General Theme

Stages of Development Coding Sheet

APPENDIX B

The Impact of Group Support System

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APPENDIX C Interview Guide Questions As you compare the two types of meetings you participated in, please circle the appropriate number in the scale below that you think is most descriptive of your team and then tell me your reactions and feelings to the questions. 1. Did the technology make any impact on helping your team orient yourselves to the task at hand (i.e., identifying and understanding the task, accomplishing the task or reaching your goals)? 1--------2--------3--------4--------5--------6--------7 The technology interfered with my team’s orientation to the task at hand.

Made no difference

The technology helped with my team’s orientation to the task at hand.

2. Describe any effect that the technology had on your team’s commitment to your goals. 1--------2--------3--------4--------5--------6--------7 The technology interfered with team commitment to the goals.

Made no difference

The technology helped improved team commitment to the goals.

3. Did the technology have any effect on your team members’ acceptance of each other: being concerned and interested in the contributions made by various members? 1--------2--------3--------4--------5--------6--------7 The technology interfered with normal behavior regarding members’ acceptance of each other.

Made no difference

The technology aided in normal behavior.

4. Describe any effect that the technology had on your team’s ability to handle conflict. 1--------2--------3--------4--------5--------6--------7 The technology provided no means for members to handle conflict.

Made no difference

The technology provided ways for members to handle conflict.

5. Did the technology have any effect on members asking for clarification to specific issues (including potentially sensitive issues)?

The Impact of Group Support System 1--------2--------3--------4--------5--------6--------7 The technology provided no means for members to ask for clarification of specific issues.

Made no difference

The technology provided ways for members to ask for clarification of specific issues.

6. Describe any effect that the technology had on your team members’ ability to communicate with each other (i.e., listening and speaking with understanding; sharing information with each other). 1--------2--------3--------4--------5--------6--------7 The technology decreased members’ communicating with each other.

Made no difference

The technology increased members’ communicating with each other.

7. Did the technology have any impact on team cooperation—where everyone was involved and part of the decision-making process? 1--------2--------3--------4--------5--------6--------7 The technology interfered with members’ involvement in the decision-making process.

Made no difference

The technology increased members’ involvement in the decision-making process.

8. Describe any effect that the technology had on providing a supportive environment where members could appreciate individual differences. 1--------2--------3--------4--------5--------6--------7 The technology did not provide a supportive environment.

Made no difference

The technology provided a supportive environment.

9. Did the technology have any influence on members including everyone (i.e., through better communication) in the decision-making process? 1--------2--------3--------4--------5--------6--------7 The technology decreased members’ ability to include everyone in the decision-making process.

Made no difference

The technology increased members’ ability to include everyone in the decision-making process.

10. Did the technology have any impact on team productivity (i.e., furnishing essential information including hardcopy printouts of the actual meeting at member’s fingertips)? 1--------2--------3--------4--------5--------6--------7 The technology decreased productivity.

Made no difference

The technology increased productivity.

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11. Did the technology have any effect on providing ways for members to contribute their ideas and solutions to the problem? 1--------2--------3--------4--------5--------6--------7 The technology decreased ways for members to contribute their ideas.

Made no difference

The technology increased ways for members to contribute their ideas.

12. Describe any effect the technology had on members valuing each other’s contributions. 1--------2--------3--------4--------5--------6--------7 The technology had a negative effect on members valuing each other’s contributions.

Made no difference

The technology had a positive effect on members valuing each other’s contributions.

13. Did the technology have any impact on your team recognizing that the work was completed and you could separate? 1--------2--------3--------4--------5--------6--------7 The technology interfered with our knowledge that the work was done and we could separate.

Made no difference

The technology aided us in knowing that the work was done and we could separate.

14. Did the technology have any effect on members recognizing that the appropriate decision was made? 1--------2--------3--------4--------5--------6--------7 The technology decreased members’ recognition of a right decision.

Made no difference

The technology increased members’ recognition of a right decision.

15. Did the technology have any effect on members’ satisfaction about their team efforts? 1--------2--------3--------4--------5--------6--------7 The technology decreased members’ satisfaction about the team effort.

Made no difference

The technology increased members’ satisfaction about the team effort.

CHAPTER 8

Cultural Transition and Adjustment of International East Asian Undergraduate Students DANIEL KERR, PhD CPA Stony Brook University TARA MADDEN-DENT, PhD Sierra Nevada College

ABSTRACT

I

nternational students studying in the Unites States of America (USA) face a series of transitional difficulties impacting academic, social, and professional success. This is especially true of East Asian students from China, South Korea, Taiwan, and Japan, as they often experience more cross-cultural adaptation distress compared to students from other countries. This study examined the pre-departure and post-arrival cultural knowledge, transition, and adjustment of Eastern Asian undergraduate international students who completed a predeparture cultural preparation treatment or received the university’s standard international student services at a Tier 1 Western USA research university. To better understand international students’ experiences, this phenomenological study investigated themes discovered within international student narratives by

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collecting qualitative data including three in-person interviews, seven student written journal reflections, a student survey, and two cultural reports. The findings of this study expand cross-cultural training and international education research by illustrating that Eastern Asian undergraduate international students gained cultural knowledge, awareness, sensitivity, and competency from a fourweek pre-departure cross-cultural treatment to which they applied during their transition and adjustment in the USA (Madden-Dent, 2014).

THE CHALLENGE OF STUDYING ABROAD Theorists (Hofstede, 2001; Kerr, 2004; Trompennars and Hampden-Turner, 1998) and practitioners (Marquart & Engel, 1993) have described culture as having many layers, much like an onion. It is what is at the center of the “onion,” that which we cannot see when encountering people from another culture, that has the biggest impact on behavior. The outer layers of culture include symbols (for example, words, gestures, pictures), heroes (persons, real or imagined that serve as role models), and rituals (such as ways of greeting, social and religious ceremonies). The inner layer is formed of values and underlying assumptions that are not easily understood by others from a dissimilar culture and are most resistant to change. They are taught to the young and most children have their basic value system established at a young age. Due to this ingrained value system, miscommunication and conflict can easily occur when first encountering people from different cultures. These differences introduce several incompatible practices related to academics, communication and interaction styles, health, safety, legal practices, and professional standards. Foreign students preparing for study in the USA are likely to have different values than the professors and students they will encounter. Hofstede (2001, p. 234) observed that the relationship between individuals and groups is established in a child’s mind early on through their upbringing, reinforced through schooling, and “very visible in classroom behavior.” For example, in a “collectivist classroom,” individual initiative is discouraged, learners associate according to pre-existing in-group ties, and learners will generally not speak up in large groups. This is in marked contrast to an “individualist classroom” where individual initiative is encouraged, students associate according to tasks and needs, and learners are expected to speak up in large groups. In contrasting the learning preferences of individualists and collectivists, Traiandis, Brislin, and Hu encouraged teachers encountering both types to investigate the beliefs, attitudes, and values of individualists and the attributes of groups of

Cultural Transition and Adjustment of International Students

collectivists. “Among individualists one is what one does; among collectivists one is what one’s group does” (Traiandis, Brislin, and Hu, 1988, p. 274). Other cultural differences are likely to come into play in the classroom. For example, how high a pedestal does a foreign student put their professor on? Is it appropriate to disagree with the professor in class? What is the appropriate level of risk? Is it ever appropriate to share an opinion without first having done extensive research? Is it appropriate to ask questions in class or give negative feedback to a disruptive or lazy classmate? How can I work with a fellow student on a project when I have no relationship with them outside of class and they are not interested in spending time getting to know me? Research by The Georgetown Consortium Project (Vande Berg, ConnorLinton, and Paige, 2009) shows that it is not the amount of knowledge one has about cultures, the time spent engaging with people in country, or even learning a new language that increase a person’s cultural competence. It is the intentional, persistent and focused attention of a person’s self-reflection on their learning—over time—that leads to greater understanding and competence. If this is true, international students preparing for study in the USA will likely increase their cultural competence if they begin their reflection on cultural difference before they begin their study abroad. The number of foreign students attending US colleges and universities increased by 3.4% in 2016–17, bringing the number to 1,078,822. Although new enrollments were down by 3.3% (largely due to the recent decline of students from Saudi Arabia, Brazil, and South Korea), this marks the eleventh consecutive year the number of foreign students has increased, according the November 2017 Open Doors report from the Institute of International Education. There are now 85% more foreign students studying in US colleges and universities than a decade ago. The largest number of foreign students come from China (32.5%), and significant numbers come from other East Asian countries such as South Korea (5.4%), Taiwan (2%), and Japan (1.7%). This influx of international students has created complex matrixes of cultural interactions directly impacting academic success, retention, health, safety, and overall student satisfaction. Although most international students experience some level of adjustment stress, Eastern Asian international students have demonstrated higher levels of acculturative distress (Poyrazli, S., Kavanaugh, P. R., Baker, A., and Al-Timimi, N., 2004). In addition to academic, professional and financial stresses, these students face language barriers, unfamiliar academic systems, new social etiquette and student responsibilities, foreign cuisine, and transportation challenges that

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intensify adjustment stress levels. Of note, although this student group can experience high levels of anxiety, isolation, fear and depression, they often avoid using campus counseling services to address cultural challenges. Cultural knowledge contributes to the reduction of students’ adjustment stress and frustrations by helping them manage cultural gaps, create realistic expectations about US environments and interactions, and foster greater intercultural and cross-cultural competencies. Cultural knowledge is built upon cultural awareness and sensitivity, which together help people develop communication skills to navigate between and within different cultural groups. These cultural competencies aid international students’ preparation for, transition into, and adjustment within the US higher education system. On the other hand, a lack of cultural knowledge is linked to less student engagement, underdeveloped communication skills and delayed cross-cultural adjustment, which interferes with academic achievement, sociocultural and psychosocial adjustment, campus engagement, institutional transfer decisions, health, and safety (Madden-Dent, 2014). Most cultural knowledge and skills development training workshops, if the US institution provides them at all, are taught after international students arrive in the USA, and are optional for students to attend. In the weeks after arrival, international students are often distracted and become overwhelmed with the number of new stimuli, language barriers, student responsibilities (such as purchasing textbooks, finding classes, completing course placement tests), and learning where and how to acquire basic life needs (that is, living arrangements, groceries, internet connection, school supplies, and transportation). As globalization increases the demand for college graduates equipped with cultural competencies, US educational leaders continue responding by providing effective cultural training and adjustment support services. One response that institutions may use to address international student needs and streamline cultural adjustment is to shift the instructional focus from post-arrival cultural training to pre-departure cultural training. The following study demonstrates how initiating cultural competency education during the pre-departure preparation stages helps bridge cultural gaps, increase accurate US culture expectations, and foster cultural competencies before international students arrive in the USA.

THE STUDY In an effort to investigate pre-departure cultural competency preparation, this phenomenological study was designed to examine pre-departure and

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post-arrival cultural knowledge, initial transition, and fall semester adjustment of Eastern Asian international undergraduate students who completed one of two different cultural treatments. Phenomenological research “identifies the essence of human experiences about a phenomenon as described by participants in a study” (Creswell, 2009, p. 231). This phenomenological study included a narrative research inquiry relying on written and spoken stories about international student cross-cultural experiences before and during their first semester in the USA. Narrative research is used to “discover regularities in how people tell stories or give speeches” (Bernard, 2000, p. 441) and narrative analysis incorporates first person accounts through life stories emphasizing and making sense of the particular experiences as told by those who lived them (Litchman, 2013). The personal storytelling allowed thematic coding to emerge without hypothesized biographical particulars; authentic regularities were discovered within the data narrated by the participants who lived the cultural phenomenon. This study examined the experiences of East Asian students from two groups: The Treatment Group and the Control Group. The Treatment Group received a four-week pre-departure cultural competency treatment, and the University Group (The Control Group) received the university’s standard international student services (post-arrival orientation). Participants included international undergraduate students from China, Japan, South Korea and Taiwan enrolled in a mid-sized, Tier 1 US research university for their first fall semester. Through online methodologies, the Treatment Group participants completed weekly student journal reflections prompted by researchers’ questions addressing the Cultural Navigator® online learning platform, the Cultural Navigator® Cultural Orientation Indicator (COI®) report, and the Cultural Naviga­tor® Country Comparison Report (student compared to US COI® profiles). Participants used the Cultural Navigator® and the two reports to complete their weekly journal reflections to study culture, their own cultural styles, their country’s cultural impact on their identity and behavior, how US culture differed from their cultural styles, potential cultural conflicts in study abroad programs, and post-arrival coping strategies. After completing the pre-departure treatment, the participants arrived in the USA at the same time as the Control Group and all participants from both groups began their fall semester. Over the next sixteen weeks, participants completed three additional post-arrival journal reflections, three in-person interviews, and an online survey. In addition to narrating their relocation and cultural experiences as they occurred, Treatment Group participants reflected on their experience using the Cultural Navigator®, how the pre-departure cultural study

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contributed to their post-arrival academics and transition, and what they recommended for international student programs during first semester transitions to enhance international student success. Overall, twenty weeks of data was collected and analyzed. Through thematic analysis, three major themes were discovered within participant narratives. Researchers identified how participants defined culture, their perception of the importance of cultural knowledge within their academic and social adjustment, and how cultural competencies influenced their initial transition and semester success. Furthermore, participants indicated that their cultural adjustment had influenced their grades, language development, campus engagement, safety, health, and their decision to either stay at the university or transfer to a new institution for the spring semester.

THE RESEARCH FINDINGS The data revealed three themes within participant narratives: “I’m on my own in a foreign land,” “I wish I knew more,” and “Thank goodness I had friends to help.” The first theme, “I’m on my own in a foreign land,” depicted participants’ initial transitions into the Western USA culture as they learned to balance academic, social, and life-planning responsibilities. Although all of the participants had been learning English as second language in their home countries, almost all of them were living independently for the first time. Participants experienced high levels of stress as they struggled making sense of local customs, interaction styles, communication styles, transportation systems, living arrangements, and foreign foods. During the semester, students experienced anxiety, exhaustion, fear, powerlessness, and intimidation due to cultural differences. Participants also expressed feeling overwhelmed, insecure, shy, awkward, angry, sad, lonely, frustrated, confused, and even afraid in the classroom, on campus, and in the community. The second theme was “I wished I knew more,” which described participants’ perceptions about their transitional experiences in relation to what they expressed wishing they had known prior to leaving their home country. The findings indicated a relationship between pre-departure cultural knowledge and post-arrival transition and adjustment. Participants perceived their adjustment stress as a result of cultural incompetence. They suggested that more crosscultural education would have helped them become better students by helping them adjust faster to the local culture, and thus better navigate the campus and community systems.

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The last theme, “Thank goodness I had friends to help,” described how friendships provided academic support (offering help from study partners), clarified cultural misunderstandings, introduced campus and community resources, and helped participants cope with stress during their transition. Through storytelling, observation, and group experiences, peer friendships taught the participants how to navigate the academic system, the public transportation system, and cultural differences in the classroom and community. Participants were more apt to ask a friend for help or clarification rather than asking university staff. Within the themes, distinctive differences between the two participant groups were discovered. The Treatment Group reflected heightened cultural awareness, competency and sensitivity, as well as strengthened sociocultural adjustment and confidence while speaking to US natives. Participants in this group were acutely aware of the cultural differences between the US cultural styles (interaction, thinking, and sense of self styles) and their own. Participants discussed how differing cultural styles impacted their study skills, classroom engagement, relationships, and communication skills. The Treatment Group expressed that studying US culture prior to arriving in the USA had helped them create more accurate expectations about US culture, and thus helped them begin to cope with or manage cultural differences. The Treatment Group was able to anticipate cultural conflicts with US students, faculty, and peers before the semester began, whereas the University Group learned about cultural differences as they experienced them through trial-and-error interactions. The Treatment Group provided examples of how they intentionally could shift their cultural styles and behaviors to more easily interact and communicate with US natives, to fit into the US academic environment, and to bridge cultural gaps. They often referenced the Cultural Navigator® recommendations from their pre-departure treatment as they prepared to manage the uncertain cultural situations. Through the semester all participants demonstrated some shift towards adopting the US cultural style, but the participants who completed the predeparture treatment displayed having more conscious choice within their stories and reflections regarding how they managed cross-cultural differences. The findings demonstrated that the Treatment Group participants were able to communicate how they consciously alternated between their home cultural styles and US cultural styles more often than the University Group. The Treatment Group reported that their gained cultural knowledge had helped them to fit into and navigate within the US culture and feel more connected to

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the US campus, and they expressed greater levels of confidence to engage with US natives.

CONCLUSION AND RECOMMENDATIONS FOR FUTURE STUDY Treatment Group participants who received the four-week pre-departure cultural preparation treatment had gained cultural awareness, sensitivity and knowledge about the US culture prior to the beginning of the semester. These participants indicated that the treatment had aided their initial transition and adjustment on and off of the university campus by providing them more accurate expectations of US interaction styles and social norms. They expressed that the increased cultural knowledge had helped them manage conflict in the USA. Finally, these participants experienced an increase in cultural awareness about their own cultural styles (interaction styles, thinking styles, and sense of self styles) in addition to US cultural styles. Although the Treatment Group demonstrated greater levels of cultural knowledge and competencies, using the new cultural skills within daily practice had proved to be more of a challenge than participants had originally assumed. Participants indicated that they needed more time to practice using the cultural behaviors (such as direct eye contact, direct communication, actively participating in class discussions) and more opportunities to engage in conversations with native English-speaking people to improve their intercultural communication skills. All participants expressed that learning about US culture was a valuable and needed element for successful academic and social adjustment. Every participant said that differences in culture had influenced their study skills, classroom engagement, communication skills, and quality of life. Both groups recommended that international students study US culture and student responsibilities prior to leaving their home country. Each participant wished they had learnt more about the US culture, their US institution, and its community. Of note, all participants reported that they would have studied US culture if their US institution had offered academic credit for the pre-departure studies or had made it mandatory. Cultural knowledge was perceived to be the most helpful way to prepare for academic and social adjustment. Besides this study’s pre-departure cultural treatment, no participants had received any formal cultural instruction prior to the beginning of the fall semester. All participants expressed that they were unaware of a service that provided cultural training and had lacked opportunities and

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motivation to learn about the US academic culture while in their home country. The cultural assessment and other assigned activities in Cultural Navigator, the related reflections, and other activities in the pre-departure in the online program filled this void. Since cultural knowledge and competencies are learned skills that can be taught online and contribute to international student success, higher educational systems may want to consider including pre-departure instruction into their international student programs to help bridge cultural transitions and help international students establish more accurate expectations about academic responsibilities before they arrive on campus. The data and the research findings suggest that the Treatment Group benefitted from the pre-departure program, providing further evidence to support the conclusion of The Georgetown Consortium Project that the intentional, persistent and focused attention of a person’s self-reflection on their learning—over time—leads to greater understanding and competence (Vande Berg, ConnorLinton, and Paige, 2009). Since this study has demonstrated that cultural knowledge and skill development support initial transitions, academic adjustment, campus engagement, language development, and academic success of Eastern Asian international students, prospective international students should consider attending US institutions that provide cultural bridge services (such as pre-departure cultural instruction, post-arrival cross-cultural workshops or classes). Additionally, these prospective students may want to investigate if the institution offers academic credit for cross-cultural studies or cultural bridge programs that facilitate college student success skills, initial academic transition, and post-arrival adjustment. University administrators addressing negative first-year international student experiences that impact retention and overall student experiences should consider investing in pre-departure training like the treatment described in this study. Such training should include assessments that identify cultural orientations, instructional tools that teach cultural differences which students will encounter and thoughtful reflection and planning activities on how to manage cultural differences. As foreign students and their families become more discriminating in their choice of US colleges, it is likely that universities that invest in such programs will have a competitive advantage in the educational marketplace. Future studies should track international students’ academic performance in the USA to assess the possible impacts of pre-departure training on retention,

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student satisfaction, and academic achievement. This study should also be replicated with students from other countries sending large number of students to study in the USA not included in this study (such as India, Saudi Arabia, Vietnam). Consideration should also be given to adding a pre- and postassessment of cultural competency for the Treatment Group before and after the pre-departure training (for example, Intercultural Effectiveness Scale®).

REFERENCES Instruments and reports 2017 Open Doors report from the Institute of International Education (2017). Retrieved from https://www.iie.org/Research-and-Insights/Open-Doors. Cultural Navigator. (2018). Industry-Leading Cultural Assessment. Retrieved from http://explore.culturalnavigator.com/features/. Intercultural Effectiveness Scale (2018). Retrieved from http://www.aperianglobal.com /learning-solutions/assessments-surveys/.

Literature Bernhard, H. R. (2000). Social research methods: Qualitative and quantitative approaches. Thousand Oaks, CA: Sage Publications. Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed). Thousand Oaks, CA: Sage Publications. Hofstede, G. H. (2001). Culture’s consequences (2nd ed.). Thousand Oaks, CA: Sage Publications. Kerr, D. B. (2004). Across cultural comparison of the learning styles of practicing accountants in Mexico and the United States. PhD dissertation, New York University. UMI Dissertations Publishing. Lictman, M (2013). Qualitative research in education: A user’s guide (3rd ed.). Thousand Oaks, CA: Sage Publications. Madden-Dent, T. (2014). A phenomenological study of cultural transition and adjustment of Asian undergraduate international students using different cross-cultural treatments. PhD dissertation, University of Nevada. UMI Dissertations Publishing. Marquardt, M. J. and Engel, D. W. (1993). Global human resource development. Englewood Cliffs, NJ: Prentice Hall. Mori, S. C. (2000). Addressing the mental health concerns of international students. Journal of Counseling and Development, 78, 137–144. Poyrazli, S., Kavanaugh, P. R., Baker, A., and Al-Timimi, N. (2004). Social support and demographic correlates of acculturative stress in international students. Journal of College Counseling, 7, 73–82.

Cultural Transition and Adjustment of International Students Traiandis, H. C., Brislin, R., and Hui, C. H. (1988). Cross-cultural training across the individualism-collectivism divide. International Journal of Intercultural Relations, 12, 269–289. Trompenenaars, F., and Hampden-Turner, C. (1998). Riding the waves of culture: understanding cultural diversity in global business (2nd ed.). New York: McGraw Hill. Vande Berg, Michael, Connor-Linton, Jeffrey, and Paige, R. Michael (2009). The Georgetown Consortium Project: Interventions for Student Learning Abroad. Frontiers: The Interdisciplinary Journal of Study Abroad, 18, 1–75.

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CHAPTER 9

Game-Based Learning to Raise Awareness of Nuclear Proliferation NANCY B. SARDONE, PhD Georgian Court University

ABSTRACT

T

his chapter reports on a preliminary study conducted with undergraduates preparing to become elementary, middle, and high school teachers in varied domains. Pre-posttest design was employed to determine learning and retention, and an adapted Intrinsic Motivation Inventory (IMI) measured participants’ experience after playing a digital social awareness game. Participants agreed that learning about nuclear proliferation was very important and stated that playing this particular social awareness game taught them that they did not know much about the subject. Post-game debriefing indicated participants’ desire to know more about the topic in conjunction with the headline news (such as Iranian nuclear deal).

INTRODUCTION With an increased focus on digital games that improve outcomes across content areas (Dede, Ketelhut, and Nelson, 2004; Gros, 2007) and positive

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reviews from researchers (Squire, 2006; Pressey, 2013), game-based learning is emerging as an instructional strategy with impact. Social awareness games, a subset of digital games are not as popular or as well known as commercial off-the-shelf titles that contributed in 2009 to the $10.5B computer and video gaming industry (Entertainment Software Association, 2014). How­ ever, they are impressive in their own right, addressing relevant and important issues of our time such as social responsibility, health, environment, freedom, violence, education, economics, and culture (Pereira, Brisson, Prada, Paiva, Bellotti, Kravcik, and Klamma, 2012). Social awareness games address relevant issues with the goal of “promoting collective recognition of the issue as a first step toward its resolution” (Bellotti, Kravcik, and Klamma, 2012, p. 56) to create a more just society. The purpose of social awareness games is to transmit a message rather than teach a skill, representing the need for serious thought about the subject matter. The major social issue in the news at the time of this study (Fall 2014) was the Iranian nuclear deal, and one study goal was to determine how much college students knew about the topic of nuclear proliferation. Digital games as a broad category have made significant strides over the past five years, emerging as a powerful instructional tool that positively affects the learning of K-12 students. In a recent meta-analysis of 39 studies involving digital games across many domains and conducted in varied settings (that is, controlled laboratory and classrooms) encompassing 5,547 participants, reported games as cognitively more effective having greater retention compared to traditional forms of instruction (Wouters, van Nimwegen, van Oostendorp and van der Spek, 2013). However, findings indicated that learning with digital games did not motivate participants to engage more than they did using traditional forms of instruction. Since motivation is a key factor in learning (Malone and Lepper, 1987), the tools used to measure intrinsic motivation require further research. In addition, social awareness games need to be further vetted in terms of their learning impact and engagement factor. This preliminary study evaluates the social awareness learning, retention, and engagement level of participants associated with Peace Doves, a game about social responsibility, violence, and security focused on nuclear proliferation. This chapter is organized as follows: first, a review of social awareness games and intrinsic motivation; next a discussion of the importance of nuclear awareness and the Nobel Peace Prize followed by a description of the game under study; and last, the research design, findings, and conclusion.

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REVIEW OF LITERATURE Social Awareness Games Educators have the responsibility to teach about social issues because understanding social issues is not intuitive. Educators also need to provide meaningful instruction that empowers students to become informed citizens concerned about the welfare of others and to stir positive action toward a just society. Yet, many teachers deem some social issues as too difficult and/or emotional; or lack the “know how,” citing a void in their professional development (Schwartz, 1990). Some teachers feel the need to self-protect from potential administrator or parental concerns; therefore, if they teach difficult social topics, they tend to do so at a superficial level (Byford, Lennon, and Russell, 2009). Social awareness games can provide an entry point to investigating serious issues and stimulating discussion. While the issues raised by social awareness games can be daunting, the greater understanding of social issues they stimulate is critical. A recent definition of social awareness games has emerged as “situations in a society where people need to be made aware of a given topic” (Pereira et al., 2012, p.59). Sample game titles in this category include Darfur is Dying, Enercities, and Stop Disasters. Yet, empirical studies that measure their ability to bring awareness to issues and evoke social change are limited. Studies centering these social awareness games are discussed below. The first was conducted with college juniors majoring in Education who played Darfur is Dying as part of a broader research study on the use of game-based instruction in middle and high school classrooms (Sardone and Devlin-Scherer, 2010). On initial play, participants were frustrated that they could not “win” the game in a conventional way because foraging for water was very difficult to do without being caught. From that frustration came a sparked interest and curiosity as to why the game was in fact so difficult to win. This provided an opportunity to discuss the game’s difficulty, a reflection of the difficult lives of the Darfurian people as refugees. Findings revealed that playing Darfur is Dying brought about an awareness of the genocidal events in Sudan. High levels of engagement during game play was noted, which set the stage for after-play debriefing Students wanted to know the “who” (for example, who is responsible, who is being killed, who helps) and the “why” (for example, why displaced). Results revealed interest in this issue by participants who played the game. Enercities, where players learn about energy choices, environmental management, and reduction methods, revealed a statistically significant positive

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effect on participants who played the game and their attitude toward resource use (Knol and de Vries, 2011). Participants indicated that they would change their specific behaviors at home by turning off their electronic devices instead of leaving them on (saves energy) and taking shorter showers (saves water). In Stop Disasters, players learn about disaster reduction methods (such as the choice of construction materials, proper placement of materials, creation of evacuation plans), make proactive decisions to prepare a community living in a disaster-prone area, and evaluate the effects of their actions when one of five simulated disasters occur (tsunami, wildfire, hurricane, earthquake, or flood). Results revealed a statistically significant positive effect on participants who played the game and their attitude toward disaster prevention (Pereira, Prada, and Paiva, 2014). Peace Doves, the game under current study, is based on the Nobel Peace Prize awarded to people and organizations working for nuclear disarmament. Conceptual knowledge includes politics and tensions that exist in global relations and how nations use nuclear weaponry as a strategy to keep other nations at bay. There are no known studies on this game.

Background on Nuclear Awareness Today, there are over 16,000 known nuclear warheads (Kristensen and Norris, 2014) possessed by nine countries reduced from an all-time high of 60,000 during the Cold War. Nuclear weapon development began as a struggle between Communism and anti-Communism until 1986 when then Soviet leader, Mikhail Gorbachev floated the idea of a “nuclear-weapon-free world” (Rotblat, Steinberger, and Udgankar, 1993). Since that time, the debate and consideration of nuclear weaponry has ensued. An atomic bomb can be made from two types of radioactive materials: uranium or plutonium. During the fall of 2014, world news agencies were reporting on Iran’s growing nuclear ability. Those talks were aimed at curbing Iran’s ability to put these two elements to use in weapons (Broad and Pecanha, 2015). Since nuclear weapons are the most dangerous weapons known to man, it is important to be aware of and give deep attention and consideration to countries stockpiling radioactive materials. The Nobel Peace Prize was developed by Alfred Nobel (1833-1896), an inventor and businessperson, who started over 87 companies and holds over 355 patents. Upon his death, Nobel intended for his vast estate to endow prizes to those who, during the preceding year, conferred the greatest benefit on humanity in the fields of physics, chemistry, medicine, literature, and peace

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(Alfred Nobel’s Life and Work, 2014). To date, seven Nobel Peace Prizes have been awarded to people and organizations working for nuclear disarmament.

Intrinsic Motivation Since Malone and Lepper (1987) first discussed the importance of motivation in learning, research has grown in support of games as an instructional strategy suggesting they can positively influence intrinsic motivation. Intrinsic motivation occurs when people are motivated to learn in the absence of obvious external rewards or punishments. Taxonomy of intrinsic motivation includes challenge, fantasy, curiosity, and control, as well as interpersonal motivations of cooperation, competition, and recognition. Further, videogame player preference has been associated with higher levels of motivation. In an early study of videogame play, Malone (1981) found the following game features most highly correlated with player preference: explicit goal, kept score, audio and visual effects (to a lesser extent), random elements (surprise), and the speed of response. Two other factors associated with videogames originate from a self-determination theory have been found to positively influence motivation: autonomy (that is, the opportunity to make choices) and competence (that is, a task is experienced as challenging but not too difficult) (Przybylski, Rigby, and Ryan, 2010). Findings differ as to whether videogames evoke intrinsic motivation. A recent metaanalysis of thirty-nine games found them to be no more motivating than the instructional methods used in comparison groups (Wouters, van Nimwegen, van Oostendorp, and van der Spek, 2013). The authors argue that since autonomy supports intrinsic motivation, conditions that limit the sense of control or freedom of action in a game’s design may undermine intrinsic motivation. They further explain that in serious games, the level of control is twofold: It is applicable to actions and decisions within the game, but also in the instructional context where decisions about issues such as the type of game and when to play the game were made for the players (p. 258). Yet, in another study, game-based learning was found to be a transformative pedagogy that motivated students to engage in learning at a deep, personal level. Chee and Lee (2009) noted that the use of well-designed games promoted learning, the acquisition of problem-solving skills, and collaborative knowledge building skills among high school students. The theory of cognitive curiosity is investigated in the current study. Curiosity is the most direct intrinsic motivation for learning. Most of the traditional

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theories of curiosity suggest that curiosity is stimulated by providing an optimal level of discrepancy or incongruity from expectations and knowledge (such as Hunt, 1965; Kagan, 1972; Piaget, 1952). Cognitive curiosity is evoked by the prospect of modifying higher-level cognitive structures. Curiosity is stimulated by designing environments or offering instructional materials that make students think their knowledge structures lack one or more of the following characteristics: completeness, consistency, and/or parsimony (Malone and Lepper, 1987, p. 237).

METHODS This study investigates content learning of undergraduate students in a preposttest design. It employs an adapted Intrinsic Motivation Inventory (IMI) that measures participants’ experience after playing the social awareness game, Peace Doves.

Participants Seventeen students in total, thirteen female and four male, at a private liberal arts university participated in the study. Participants are college juniors enrolled in a required education course that investigates the use of technology as an instructional tool in K-12 education.

Research Questions The study is framed by the following research questions. 1. 2. 3. 4. 5.

Can participants learn content from a social awareness game? Do participants retain the content learned? Do participants believe nuclear awareness is important? What is participants’ current level of nuclear awareness? Did the social awareness game pique participants’ interest in the topic?

Limitations The sample size in this study is small, making it difficult to generalize to the larger population. In addition, the Peace Doves game questions sometimes lead the player to answer questions through the provision of hints. For example,

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when asking players to name the state that did not sign the 1963 Limited Test Ban Treaty, it led the player to the correct answer when stating that by 1998 this state had made several nuclear weapon tests and, in protest, many people stopped buying wines produced in this state showing disapproval. Further, this study did not compare the social awareness game (Peace Doves) to other forms of instruction.

Modes of Inquiry Three modes of inquiry were used in this study. The first is a three-question demographic survey constructed using guidelines outlined by Gall, Borg, and Gall (1996). The second is a four-question test that served as the study’s pre- and posttest. The four questions deal with content contained within the game. The third form of inquiry is an adapted Intrinsic Motivation Inventory (IMI) (Deci and Ryan, 2003). The IMI is a multidimensional measurement device that assesses participants’ subjective experience related to a target activity. It has been used in several experiments related to intrinsic motivation (McAuley, Duncan, and Tammen, 1989; Ryan, Koestner, and Deci, 1991; Deci, Eghrari, Patrick, and Leone, 1994). The instrument assesses the following: interest/enjoyment; perceived competence; effort; value/usefulness; felt pressure and tension; and perceived choice while participants perform a given activity, yielding six subscale scores. The perceived competence component is theorized to be a positive predictor of intrinsic motivation, and pressure/tension is theorized to be a negative predictor of intrinsic motivation. Each dimension is characterized by a set of sentences that the participant has to rate using a 7-point Likert Scale, where 1 means “not true at all,” 4—“somewhat true,” and 7 means “very true.” In this study, four dimensions were analyzed (interest/enjoyment, perceived competence, effort/importance, and pressure/tension).

Materials The objective of the game Peace Doves is to use the worldwide symbol of peace, the dove, to disarm nations of their nuclear weapons. Each player is provided with eight peace doves. Once players identify the country possessing nuclear weapons based on provided clues, they launch a dove to that specific country to disarm it. If correctly identified, the mission is deemed successful as the nation is now disarmed. If not, the player gets another chance. Players disarm the

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following countries known to possess nuclear warheads: Russia, the United States, France, China, United Kingdom, Israel, India, and Pakistan.1 Gameplay questions include the following.   

   

Which countries possess nuclear weapons? What is the Non-Proliferation Treaty? Which five states are known as “Nuclear Weapons States,” allowed to possess nuclear weapons according to the Non-proliferation Treaty of 1970? Approximately how many nuclear warheads exist? Which country possesses the most number of nuclear warheads? Are there any nuclear warheads in space? What is the difference between a tactical and strategic nuclear warhead?

Procedures Prior to game play, participants were asked to complete a four-question pretest asking their knowledge about nuclear armament. The pretest included the following questions. 1. The Peace Doves game identifies eight countries in possession of nuclear weapons. Today, there are actually nine countries possessing warheads with the ninth being North Korea. Name the eight countries. 2. Name the five countries allowed to possess nuclear weapons, according to the 1970 Non-Proliferation Treaty. Three countries have not signed the 1970 Non-Proliferation Treaty. Name the three countries. 3. Name the first country to develop nuclear weapons and the only country to have used them in war. After a fifteen-minute session playing Peace Doves in a computer lab, participants were asked to complete an adapted version of the IMI (Deci and Ryan, 2003). The posttest measure was administered one week after initial game play took place. The posttest asked participants the same four questions as the pretest.



1 The game is missing North Korea with an estimated number of warheads of ten (Kristensen and Norris, 2014; The Pyongyang Times, 2007).

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Data Analysis Pre-posttest design was employed to determine content retention, game score to determine learning, and an adapted IMI to measure participants’ experience after playing the social awareness game, Peace Doves. Quantitative data describing students’ experiences were collected using the pre- and posttest instruments and entered into analytic software, SPSS for Windows. SPSS functions of frequencies and descriptives were used. The sample size in this study makes it difficult to generalize to the larger population. As such, non-parametric procedures were conducted to analyze the data.

Results A frequencies analysis revealed that among the seventeen participants, thirteen reported themselves as avid online game players. One reported as never having played any form of online game. To answer the research questions, varied data analyses were performed. To answer question one, “Can participants learn content from a social awareness game,” descriptive statistics revealed that on average, 4.18 missions were won out of a possible eight missions. Eleven participants won three to five missions, representing 64.8% of the sample. A comparison of the mean scores for each of the four questions (Table 1) indicates that the mean value in the posttest is superior to the mean value of the pretest. A Friedman one-way ANOVA non-parametric procedure was conducted on the total mean scores of the pretest and posttest, revealing a pretest mean of 5.29 and a posttest mean of 9.00. Table 1.  Mean and Standard Deviations

Question 1 Question 2 Question 3 Question 4

Median 3.00 2.00 .00 1.00

Pretest Mean 2.76 2.00 .00 .53

StDev 1.522 1.658 .000 .514

Median 1.00 5.00 3.00 1.00

Posttest Mean 4.94 2.53 .82 .71

StDev 1.435 1.179 .951 .470

A Wilcoxon Matched-Pairs Signed-Rank non-parametric test was conducted on each pair of pre-post data to answer research question two, “Do participants retain the content learned?” The posttest was administered one week after initial game play took place.

Game-Based Learning to Raise Awareness of Nuclear Proliferation Table 2.  Results of the Wilcoxon Matched-Pairs Signed-Rank test Question 1 Question 2 Question 3 Question 4

Z value –3.663 –1.279 –2.724 –1.342

Sig (2-tailed) .000 .201 .006 .180

Based on the results of that test (Table 2), it is concluded that students retained content learned in the prior week through the social awareness game Peace Doves. 1. The number of countries possessing nuclear weapons that participants were aware of before playing the Peace Doves game was significantly lower (M = 2.76) than the number of countries they were aware of after playing the game (M = 4.94), Z = –3.663, p = .000 2. The number of countries allowed to possess nuclear weapons according to the 1970 Non- Proliferation Treaty that participants were aware of before playing the Peace Doves game was not significantly lower (M = 2.00) than the number of countries they were aware of after playing the game (M = 2.53), Z = –1.279, p = .201 3. The number of countries that did not sign the 1970 Non-Proliferation Treaty that participants were aware of before playing the Peace Doves game was significantly lower (M = .00) than the number of countries they were aware of after playing the game (M=.82), Z = –2.724, p =.006 4. The first country to develop nuclear weapons and the only country to have used them in war that participants were aware of before playing the Peace Doves game was not significantly lower (M = .53) than they were aware of after playing the game (M = .71), Z = -1.342, p = .180 To answer the third research question, “Do participants believe nuclear awareness is important,” and the fourth question, “What is participants’ current level of nuclear awareness,” a frequencies analysis of the sixteen-question IMI was conducted using SPSS. Results are presented in Table 3.

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Nancy B. Sardone Table 3.  Results of the IMI Frequency Analysis Adapted IMI  1. I enjoyed Peace Doves very much.   2.  I put a lot of effort into playing Peace Doves.   3.  It was important to me to do well at this game.   4.  I felt tense while playing Peace Doves.   5.  I tried very hard while playing this game.  6. Playing Peace Doves was fun.   7.  I would describe this game as interesting.   8.  I felt pressured while playing Peace Doves.   9.  I felt anxious while playing Peace Doves. 10.  I didn’t try very hard when playing this game.

Mean 4.18 5.18 5.00 4.29 5.18 4.12 5.12 4.53 3.76 5.53

SD 1.29 1.55 1.50 1.61 1.51 1.41 .993 1.42 1.75 1.55

11. While playing Peace Doves, I was thinking about how much I enjoyed learning about Nuclear Proliferation through this format. 12.  I was relaxed while playing Peace Doves. 13.  This game held my attention. 14.  Learning about Nuclear Proliferation is important. 15. This game taught me that I do not know very much about Nuclear Proliferation. 16.  Number of missions won

3.24

1.20

3.18 5.35 5.71 1.76

1.51 1.54 1.26 1.09

4.18

1.74

The third research question asked whether participants that believed nuclear awareness was important. The results of a frequency analysis of IMI question 15 (“Learning about nuclear proliferation is important”) indicated a mean score of 5.71, with a standard deviation of 1.26. The fourth research question asked about the participants’ awareness of nuclear proliferation. The results of a frequency analysis of IMI question 16 (“This game taught me that I do not know very much about nuclear proliferation”) indicated a mean score of 1.76, with a standard deviation of 1.09. Fourteen participants (82.3%) agreed that learning about nuclear proliferation was very important and fifteen participants (88.2%) stated that playing this particular social awareness game taught them that they did not know much about the subject matter. This creates a pause as the many state Social Studies curriculum standards in grades 9–12 indicate that students are to assess the impact of the arms race and the proliferation of nuclear weapons on world power, security, and national foreign policy (NJCCCS, 2014). The fifth research question five asked whether the social awareness game piqued participants’ interest in the topic. This question is answered by the quality of the post-game play debriefing and subsequent discussion. Participants were interested in the current news headlines involving Iran nuclear

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ability. They wanted to know if, for example, Iran encroached on the 1970 Non-Proliferation Treaty agreement when constructing a nuclear energy plant. The long-term impact of Iran as holder of nuclear materials on the other Gulf States like Saudi Arabia was discussed and debated. Participants understood that possession of nuclear weaponry was a strategy countries used to keep potential attacks at bay. However, the participants did not understand why the United States was involved in the talks and what they hoped to gain by such involvement. It is postulated that this finding leads back to Malone and Lepper’s (1987) theory of cognitive curiosity. Perhaps the daily news headlines piqued participants’ interest in the topic of nuclear proliferation and the game provided a pathway to learn more about current events.

CONCLUSION This preliminary study is a starting point for future research to determine the impact of intrinsic motivation using an inventory like the IMI on learning outcomes when using social awareness games to teach content. The results of this study indicated that learning occurred with Peace Doves as an instructional tool and content was retained one week later. Games can serve as introductions to a larger unit or a significant theme, help students face a powerful and current issue, illustrate policy-making, serve as a unit summary, or it can be an experience in and of itself. Debriefing a game helps students see other perspectives. Use of the game Peace Doves brought awareness of nuclear weapons to the surface for this type of discussion. Teachers looking for supplemental materials to engage students in the nuclear discussion might consider excerpts from Mikhail Gorbachev’s (1997) book, Perestroika: New Thinking for our Country and the World. This work asks us to determine our own future and the future of the world. Gorbachev’s view of nuclear armament is clear, “The fundamental principle of the new political outlook is very simple: nuclear war cannot be a means of achieving political, economic, and ideological or any other goals.” Gorbachev’s conclusion is truly revolutionary, for it means discarding the traditional notions of war and peace. He further states, “There would be neither winners nor losers in a global nuclear conflict: world civilization would inevitably perish…. The new political outlook calls for the recognition of one simple axiom: security is indivisible” (p. 140–142). Perhaps a look to the past can provide a peaceful pathway for our future.

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REFERENCES Alfred Nobel’s Life and Work (2014). Nobel Media AB. Retrieved from http://www.nobelprize. org/educational/nobelprize_info/gradeschool.html. Broad, W. and Pecanha, S. (2015, July 14). The Iran nuclear deal: A simple guide. The New York Times. Retrieved from http://www.nytimes.com/interactive/2015/03/31 /world/middleeast/simple-guide-nuclear-talks-iran-us.html. Byford, J., Lennon, S., and Russell, W. (2009, March/April). Teaching controversial issues in the social studies: A research study of high school teachers. The Clearing House: A Journal of Educational Strategies, Issues, and Ideas, 82 (4), 165–170. Chee, Y. S., and Lee, L. H. (2009). Game-based learning as a vehicle for developing science inquiry skills using the Centauri 7 Learning Program. In S. C. Kong et al. (eds.), Proceedings of the 17th International Conference on Computers in Education, 659–666. Hong Kong: AsiaPacific Society for Computers in Education. Retrieved from http://www.icce2009.ied.edu. hk/pdf/c5/proceedings659-666.pdf. Deci, E. L., and Ryan, R. M. (2003). Intrinsic motivation inventory. Retrieved from http://www. selfdeterminationtheory.org/intrinsic-motivation-inventory/. Deci, E. L., Eghrari, H., Patrick, B. C., and Leone, D. (1994). Facilitating internalization: The self-determination theory perspective. Journal of Personality, 62, 119–142. Dede, C., Ketelhut, D., and Nelson, B. (2004). Design-based research on gender, class, race, and ethnicity in a multi-user virtual environment. Paper presented at the 2004 American Educational Research Association Conference. San Diego, CA. Entertainment Software Association (2014). Videogame industry statistics. Retrieved from http:// www.esrb.org/about/images/vidGames04.png. Gall, M. D, Borg, W. E., and Gall, J. P. (1996). Educational research. White Plains, NY: Longman. Gorbachev, M. (1997). Perestroika: New thinking for our country and the world. London: Collins Publishing. Gros, B. (2007). Digital games in education: The design of game-based learning environments. Journal of Research on Technology in Education, 40 (1), 23–38. Hunt, J. (1965). Intrinsic motivation and its role in psychological development. In D. Levine (ed.), Nebraska Symposium on Motivation, 13. Lincoln: University of Nebraska Press. Kagan, J. (1972). Motives and development. Journal of Personality and Social Psychology, 22, 51–66. Knol, E., and de Vries (2011). EnerCities—A serious game to stimulate sustainability and energy conservation: Preliminary results. eLearning Papers, 25. Retrieved from: http://ssrn.com/ abstract=1866206. Kristensen, H., & Norris, R. (2014, August 26). Worldwide deployments of nuclear weapons. Bulletin of the Atomic Scientists. Retrieved from http://bos.sagepub.com/content/early/ 2014/08/26/0096340214547619.full.pdf+html. Malone, T. W. (1981). Toward a theory of intrinsically motivating instruction. Cognitive Science, 4, 333–369.

Game-Based Learning to Raise Awareness of Nuclear Proliferation Malone, T. W., and Lepper, M. R. (1987). Making learning fun: A taxonomy of intrinsic motivations for learning. In R. E. Snow and M. J. Farr (eds.), Aptitude, Learning and Instruction, volume 3: Cognitive and Affective Process Analysis. Hillsdale, NJ: Lawrence Erlbaum. Retrieved from http://ocw.metu.edu.tr/mod/resource/view.php?id=1311. McAuley, E., Duncan, T., and Tammen, V. (1989). Psychometric properties of the intrinsic motivation inventory in a competitive sport setting: A confirmatory factor analysis. Research Quarterly for Exercise and Sport, 60 (1), pp. 48–58. NJCCCS (2014). State of New Jersey Department of Education. Student learning standards: Social Studies. Retrieved from http://www.state.nj.us/education/cccs/2014/ss/. Pereira, G., Brisson, A., Prada, R., Paiva, A., Bellotti, F., Kravcik, M., and Klamma, R. (2012). Serious games for personal and social learning & ethics: Status and trends. Procedia Computer Science, 15, 53–65. Retrieved from http://www.sciencedirect.com/science /article/pii/S1877050912008204. Pereira, G., Prada, R., and Paiva, A. (2014, September). Disaster prevention social awareness: The stop disasters! case study. Conference proceedings for the Games and Virtual Worlds for Serious Applications. Retrieved from http://ieeexplore.ieee.org/. Pressey, B. (2013). Comparative analysis of national teacher surveys. Retrieved from http://www. slideshare.net/AleixRisco/2013-comparative-analysis-of-national-teacher-surveys. Przybylski, A., Rigby, C., and Ryan, R. (2010). A motivational model of video game engagement. Review of General Psychology, 14, 154–166. Rotblat, J., Steinberger, J., and Udgankar, B. (eds) (1993). A nuclear-weapon-free world. Boulder, CO: Westview Press. Ryan, R. M., Koestner, R., and Deci, E. L. (1991). Ego-involved persistence: When free-choice behavior is not intrinsically motivated. Motivation and Emotion, 15, 185–205. Sardone, N., and Devlin-Scherer, R. (2010). Teacher candidate responses to digital games: 21st century skills development. Journal of Research in Teacher Education, 42 (4), 409‑425. Schwartz, D. (1990). Who will tell them after we’ve gone? Reflections on teaching the Holocaust. The History Teacher, 23 (2), 109–116. Squire, K. (2006). From content to context: Videogames as designed experience. Educational Researcher, 35 (8), 19–29. “Usher in a great heyday of Songun Korea full of confidence in victory.” The Pyongyang Times, January 6, 2007, 1. Wouters, P., van Nimwegen, C., van Oostendorp, H., and van der Spek, E. D. (2013, February 4). A meta-analysis of the cognitive and motivational effects of serious games. Journal of Educational Psychology, 105 (2), 249–265.

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CHAPTER 10

Virtual Workplace Learning: Promises Met? ROBERT G. BROOKSHIRE, PhD University of South Carolina LYNN B. KEANE, PhD Palomar College KARA LYBARGER, MA

V

irtual learning has become ubiquitous in the workplace as one of many modalities for delivering training. Companies around the world, large and small, provide training to their employees using computer technology. Indeed, the American Society for Training and Development found in a series of studies that 36% of all training programs in organizations were delivered by computer (Rivera & Paradise, 2006). As we will show, however, the impact of virtual learning has been decidedly mixed. Virtual learning can be efficient and effective, but it is not equally well suited for every subject, every employee, or every situation. At the same time, there are a variety of steps employers can take to maximize the probability of success in the implementation of virtual learning. This chapter reviews recent research, from both corporate and academic settings, on virtual learning. Our objective is to explore the many complexities of virtual learning in order to help companies to deploy it successfully. We also hope to make a small contribution to what has become a vast stream of research. We restrict our review primarily to works published since 2006. TallentRunnels and her colleagues provide an exhaustive review of the research literature prior to this date (Tallent-Runnels et al., 2006).

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The chapter is organized into five sections. We begin by identifying, among the myriad definitions and terms associated with the use of computers in training, exactly what we mean by virtual learning. The second section reviews the benefits provided by virtual learning in the workplace. The third portion addresses the pitfalls and barriers to the success of virtual learning. The fourth part presents an examination of the success factors identified by research for virtual learning initiatives. Finally, we conclude with some observations about virtual learning.

WHAT IS VIRTUAL LEARNING? It’s a brave person who attempts to define the term “e-learning”; there are many interpretations and many distinguished papers on the subtle nuances between definitions. Allison, 2007, p. 20.

The concept of virtual learning was born in the mid-1980s when Starr Roxanne Hiltz coined the term “virtual classroom” (Hiltz, 1986). The use of computers for instruction had begun practically alongside the development of computers in the 1950s and 60s, however, under the name “computer-aided instruction” (CAI). Reviewing the early history of CAI, Chambers and Sprecher (1980) distinguish between adjunct CAI, in which the computer supplements learning, and primary CAI, in which the computer substitutes for other modes of instruction. CAI is the primary forerunner of virtual learning. As virtual learning developed through the last few decades of the twentieth century, a variety of terms were coined to describe it. Technologymediated learning, or TML, for example, “is defined as an environment in which the learner’s interactions with learning materials (readings, assignments, exercises, etc.), peers, and/or instructors are mediated through advanced information technologies” (Alavi and Leidner, 2001, p. 2). Another popular term, perhaps more widely used than any other, is “e-learning.” Broadly speaking, e-learning (sometimes “eLearning”) refers to “the process of learning from information that is delivered electronically” (Honey, 2001, p. 201) and is used by many authors to cover a variety of CAI technologies and techniques. It has even become established as part of the title of several journals and magazines, such as The Electronic Journal of e-Learning, the European Journal of Open, Distance and E-Learning, and E-learning Age.

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As Tynjälä and Häkkinen (2005) note, terms such as “distance learning,” “blended learning,” and “mobile learning” have been used as synonyms for “e-learning.” Westbrook (2006) adds the terms online learning, Internet-based learning, and web-based learning. Aggarwal and Makkonen (2009) contribute the expressions asynchronous learning and networked learning. Servage (2005) provides a thoughtful review of the “e-nomenclature” problem and its implications for the way researchers, teachers, and organizations think and deal with the concept. Tynjälä and Häkkinen maintain, however, that e-learning is really more than just “delivering digital information and study materials to people through electronic media” (2005, p. 318). As with e-learning, virtual learning is subject to multiple definitions. Stonebraker and Hazeltine have, probably, the broadest conception: Virtual learning is defined as the delivery of learning through electronic mediation which bridges the gap caused when the instructor and student are separated in either time or place…. The range of electronic mediation includes voice, video, data, and print through such formats as radio, television, Web-based programming, and streaming audio and video, as well as a variety of recording technologies (Stonebraker & Hazeltine, 2004, p. 209).

Most authors, however, restrict virtual learning to that which occurs only in a computer-mediated setting. Piccoli, Ahmad, and Ives, following Wilson, describe virtual learning as occurring in “‘computer-based environments that are relatively open systems, allowing interactions and encounters with other participants’ and providing access to a wide range of resources” (Wilson, 1996, p. 8; Piccoli, Ahmad, and Ives, 2001, pp. 402–403). Likewise, Hornik, Johnson, and Wu write that in virtual learning, “learning processes, communications, shared social context and learning community are mediated through information technology” (Hornik, Johnson, and Wu, 2007, p. 25). For the purposes of this paper, we will use the term “virtual learning” to refer to learning that is delivered through information technology and that uses this technology to permit interaction among the participants, instructors and learners alike. Thus, as with Hiltz’s original virtual classroom, computer technology creates a virtual environment in which learning takes place, rather than supplementing face-to-face instruction. This distinguishes virtual learning from other types of e-learning, such as computer-based training, in which the student works independently and interacts only with the computer. As Littleton and Whitelock write, at the core of virtual learning “is the facilitation

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of discourse for the purpose of building understanding” (2004, p. 173). Our conception is similar to computer-supported collaborative learning (CSCL), a term widely used among European researchers (see, for example, Tynjälä and Häkkinen, 2005). For similar definitions of virtual learning, see Weller, Pegler, and Mason (2005) and Keller (2005).

THE BENEFITS OF VIRTUAL LEARNING Large organizations in just about every field are utilizing eLearning through some of the latest and greatest technological advances. eLearning is helping them to fine-tune production, maximize sales and build the capacity of their workforces. They are gaining a competitive advantage that, in turn, encourages them to advance further along the eLearning adoption curve. Leary and Berge, 2007, p. 1.

The popularity of virtual learning in the workplace is due to its many benefits. The literature on virtual learning over the last thirty years has identified many advantages for businesses. In this section we review some of the most recent research findings and opinion. Bell (2007) identifies the following advantages for businesses. It is easier and more cost-effective for training large numbers of employees in a short time span. Online content may be more up-to-date. Online training insures consistency across a global, diverse workforce. Online training can include automated auditing tools to insure compliance. Benefits for learners include flexibility and control over the learning experience, short periods of learning that do not interfere with work, the ability to take extra time with more challenging material, and a safer environment with less pressure than classroom learning. Like Bell, Schooley (2009) lists consistency as an advantage. Others she identifies include faster learning; the ability to learn anytime, anywhere; reusability of content; and reduction in travel expenses. A chief advantage of virtual learning is its adaptability for a variety of learning styles (Allison, 2007) and learning needs (Pearson and Koppi, 2003; Santos et al., 2007). The use of information technology allows material to be developed for almost any type of learner, “making it available both for on-demand, personal, consumption, as well as for group-based activities” (Allison, 2007, p. 21). Students can participate in group learning, and then return individually again and again to review materials at their own pace. Students’ specific individual

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needs can be addressed (Santos et al., 2007) using virtual learning design (Pearson and Koppi, 2003). Liz Falconer, of the University of the West of England, challenges the notion that tacit information cannot be transmitted or transformed using technology. Through an extensive review of the literature, she shows that, both empirically and theoretically, organizational learning can be enhanced through e-learning (Falconer, 2006). Jane Simmons (2006) makes a similar point from the perspectives of both employers and employees. In the British Journal of Educational Technology, Allan and Lewis report the results of a four-year case study of a virtual learning community. The members of this community, composed of professional staff at a university, were able to increase their innovation and professional expertise through the support they derived from the learning community (Allan and Lewis, 2006). Ward and Riley (2008) recommend virtual learning as a cost-effective strategy in a demanding economic environment such as 2008–2009. They say that virtual learning can provide expanded training at minimal cost, it can save time, and it can target training and learning on demand. Using computer systems allows more detailed tracking and reporting of training as well as different formats that match employee learning styles. As with Falconer and Simmons, Ward and Riley concur that virtual learning is useful for transferring organizational knowledge and keeping employees actively engaged in their jobs. Finally, they define well-designed virtual learning as that which can be used to attract and recruit new employees. To summarize, then, virtual learning can have a variety of benefits that accrue primarily to the employees themselves, to the employers, and to both employees and employers. Benefits for the employees themselves include: • • • • •

flexibility and control over their learning experience; the ability to take extra time with more challenging material; a safer environment with less pressure than classroom learning; the ability to learn anytime, anywhere; and adaptability for a variety of learning styles and needs.

Benefits mainly for the employer include the facts that virtual learning: • is easier and more cost-effective for training large numbers of employees in a short time span; • can expand training at minimal cost;

Virtual Workplace Learning: Promises Met?

• • • • • • •

can reduce travel expenses; insures consistency across a global, diverse workforce; allows more detailed tracking and reporting of training; can include automated auditing tools to insure compliance; has reusable content; enhances and expands organizational learning options; and can attract and recruit new employees.

Finally, some benefits of virtual learning apply to both employees and employers, such as: • • • •

more up-to-date content; shorter periods of learning that do not interfere with work; training and learning that are targeted and on demand; employees who increase their innovation and professional expertise; and • employees who are actively engaged in their jobs.

CHALLENGES TO VIRTUAL LEARNING E-learning will not meet all requirements and the classroom training that has proved a mainstay for most organisations will not be swept away by this technology. Certain skillsets, such as leadership and project management, cannot be taught properly via a purely electronic format. Pancucci, May 28, 2002, p. 22.

Virtual learning is not for everybody, nor is it for every situation. Some kinds of learning seem better suited to face-to-face settings or other modalities. Even in cases where virtual learning is appropriate, trainers and designers must take into account the special requirements of the technology and the special needs of different types of learners (Pearson and Koppi, 2003). This section reviews research and opinion on the challenges to virtual learning. As the introductory quote illustrates, not all subjects are well-suited to virtual learning. Those topics that require frequent close-range person-to-person interaction are in this category. In addition to leadership and project management, developing soft business skills such as negotiation or group facilitation, and creating personal or team trust are situations in which face-to-face instruction is more appropriate (Schooley, 2009).

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Virtual learning requires special preparation to overcome workplace challenges. Simon (2009, January) discusses seven of the most common myths about delivering virtual learning. Workers may not take advantage of available learning materials. Rather than being carefully planned, assessments are often omitted. The learning environment outside the virtual learning space must be considered. The characteristics of the learning management system should be taken into account, especially the user interface. Trainers must make it easy to access the course materials and pay attention to the different hardware and software configurations of the users. Alonso, Manrique, and Viñes examined 385 employees of the Spanish Administration who were studying the Java programming language in either face-to-face or virtual environments. They found significant differences in the amount of learning, satisfaction with learning, and the amount of time it took to complete the material based on the design of the learning modules (Alonso, Manrique, and Viñes, 2009). While virtual learning has the advantage of being potentially adaptable to different learning styles, if employees are presented with materials using a learning style different from theirs, results may be disappointing. In their study of 332 university students using a virtual learning environment, Hornik, Johnson, and Wu found that when there was congruence between learning style and the virtual environment, results were good. If there was no such fit, however, outcomes were significantly poorer. They conclude, “…the potential exists for organizations to waste large amounts of resources in their investments in their distributed initiatives and for employees participating in these initiatives to learn less, participate less, and ultimately have reduced skills and knowledge than if fit were considered.” (Hornik, Johnson, and Wu, 2007, p. 38). Attitudes towards computers can also impact employees’ perceptions of virtual learning. Park and Wentling studied employees of a large construction and agricultural equipment manufacturer involved in virtual learning at work. They found learners who had positive attitudes toward computers viewed the virtual learning environment more favorably and were better able to transfer their learning to their jobs (Park and Wentling, 2007). Using virtual learning with older workers can present different dilemmas than with younger workers. This may become more problematic as the workforce in developed countries ages. According to Githens (2007), organizations must work to eliminate stereotypes of older workers as unable to use technology, develop an appreciation for the advantages of older workers, and avoid situations where older workers could be embarrassed about memory loss. Older

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adults find some technologies easier to use than others, but accommodations may have to be made for vision problems and the slower rate at which older adults learn. Not only is virtual learning different for employees of various ages, it is even different for employees in different parts of the same business. Gallaher and Wentling (2009) examined the rate of adoption of virtual learning across different professional groups in a large US company. They found finance and marketing professionals were the quickest to adopt virtual learning, followed by engineers and legal professionals. Surprisingly, human resource professionals were the slowest of the groups studied. Among the demographic factors they examined, only education and experience with the Internet affected the use of virtual learning. Virtual learning is particularly challenging for smaller organizations. Birchall and Giambona (2007) write that employees in small and medium enterprises (SMEs) find it difficult to fit virtual learning into daily activities; SMEs often operate in relative isolation, and many do not have the infrastructure to support multimedia. Leary and Berge agree, and point out that the economies of scale that help large companies justify virtual learning do not apply to smaller enterprises. In addition, smaller companies may lack professional training and technical staff, or even a learning culture. They may be too busy or unable even to identify their training needs (Leary and Berge, 2007). These conclusions are supported by Roy and Raymond’s study of sixteen SMEs in the Atlantic region of Canada. They found the need to develop an e-learning culture and the availability of technical skills and appropriate software were critical to the use of virtual learning in these companies, prerequisites that were often missing (Roy and Raymond, 2008). The implementation of virtual learning in less developed countries may bring about a different set of problems. Ali and Magalhaes, comparing virtual learning in Kuwait to Western countries, found problems in Kuwait with access to technology, scalability, sharing of assets, measurement, and standards. They especially emphasize the failure of managers and management processes to appreciate and integrate technology into training. They write, “Although the potential for delivery [of virtual learning] at the global level is present, actual delivery is very much dependent upon local circumstances” (Ali and Magalhaes, 2008, p. 49). With increasing security threats to online systems, technology managers have implemented additional security mechanisms. Tsiantis, Stergiou, and Margariti (2007) argue that many of the mechanisms are restrictive and autocratic, reducing dramatically the usability of online learning systems. Users resort to insecure behavior or suffer from low motivation. The answer is for

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designers of security procedures and software to recognize the special nature of virtual learning systems and to work with users to provide user-centered security. Ardito and colleagues present a framework for evaluating the usability of virtual learning systems that includes both software usability and pedagogical effectiveness (Ardito et al., 2006). In her review of the virtual learning literature, Westbrook (2006) identifies problems such as collaboration fatigue, in which students feel overwhelmed by the demands of online collaboration; misunderstandings in the absence of verbal, body, and spoken cues; and irresponsibility among students in turning in assignments. In addition to student problems, teachers need additional training in order to be effective in the virtual classroom. In summary, there are many factors to consider when implementing virtual learning that might negatively affect learning outcomes. We can group these factors into characteristics of the design of the training or training system, characteristics of the workplace, and characteristics of the learners themselves. Among the characteristics of the training system or the training itself, we have the following. • Topics that require personal interaction such as leadership training, negotiation, or group facilitation may not be appropriate for virtual learning. • Assessments should be carefully designed. • The learning management system’s characteristics, including the user interface, can impact the effectiveness of virtual learning. • Training materials must be easy to access. • The technology available to the users must be considered in the design of the system. • Security mechanisms must not interfere with the usability of the learning system. • The pedagogical design of the training can significantly affect its effectiveness. In particular, there must be a fit between the learning style of the students and the style of the materials. The characteristics of the workplace must be taken into account. These include the following. • The physical learning environment must be appropriate. • Adequate technical and professional training staff are required.

Virtual Workplace Learning: Promises Met?

• An e-learning culture must be developed. • Management support is critical. The characteristics of the learners themselves may present challenges to virtual learning. Some of these are the following. • Different types of workers approach virtual learning differently, including older workers and those with less computer experience. • Systems must be adaptable to the physical needs of users. • Overuse of virtual learning may induce fatigue with the system. • Workers must be motivated to participate in the training.

CRITICAL SUCCESS FACTORS IN DEPLOYING VIRTUAL LEARNING It would be nice to think that a well-designed e-learning lesson will break through any obstacle in its way and will illuminate the light bulbs of all learners who touch it. The reality, however, is that many perfectly good e-learning lessons have wilted and died.... Simon, 2009, p. 35.

In this section, we review the recent research on the critical success factors for the implementation of virtual learning. We examine not only quantitative research, but also qualitative studies and the informed opinions of business trainers and managers. There seems to be a general agreement on many of the important determinants of virtual learning success. Luarn, Chen, and Lo, of the National Taiwan University of Science and Technology, surveyed 394 employees enrolled in e-learning through the Taiwan Knowledge Bank. The researchers identified six critical success factors for e-learning. These included factors that enhance learning performance, such as provision of courses that meet learners’ immediate needs; provision of afterclass services, including timely reporting of scores and interaction with instructors; and the maintenance of environmental quality, especially with regard to the equipment and learning space. Other factors were the establishment of an interactive mechanism, particularly with other learners; the provision of flexible learning, especially class times and the ability to work at the learner’s own pace; and satisfaction of user needs, including the ability of learners to choose courses freely that meet their needs. They found that a feedback loop or “positive circle” was created with successful e-learning deployment, whereby enthusiasm for

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learning leads to greater participation, which increases the likelihood of success (Luarn, Chen, and Lo, 2007). Researchers Lim, Lee, and Nam surveyed 151 employees in three Korean firms who had participated in line training from 1 to 6 months. The researchers examined ten factors they hypothesized would influence the effectiveness of online training. Of these, they found eight were significant, including learning motivation, computer self-efficacy, the contents of the training program, ease of use, the support of supervisors, consistency in the learning environment, and face-to-face meetings between instructors and trainees. They found that e-mail communications did not seem to affect performance (Lim, Lee, and Nam, 2007). Roca and Gagné surveyed 174 employees of four United Nations agencies who had taken a virtual learning course offered by the United Nations System Staff College. They found the workers were more likely to continue using the virtual learning system when they felt autonomous and competent using the system. These feelings affected their motivation and their perceptions of the usefulness and playfulness of the system. When the employees felt supported and connected to their colleagues, they used the system because of the enjoyment they felt (Roca & Gagné, 2008). Simmering, Posey, and Piccoli studied the performance of 190 university students in an online software applications course. They found that computer self-efficacy was positively related to learning, even after controlling for factors such as previous knowledge. In contrast to previous research, however, they found that motivation to learn was not related to learning (Simmering, Posey, and Piccoli, 2009). Birchall and Giambona looked at the use of virtual learning communities as a way for small and medium enterprises to meet their training needs. They recommend the following to enhance success: “care in the selection of participants; early dialogue in the virtual community to encourage information sharing and to set the tone; appropriate use of technology for communications; the establishment of ground rules for behaviour within the community; facilitators providing a role model and also putting effort into maintaining momentum and energy levels.” (Birchall & Giambona, 2007, p. 199) Stonebraker and Hazeltine surveyed 338 participants in an online test preparation course at a large US company. They found a reduction in the social processes of learning such as interaction and sense of group cohesion. They also found that prior experience with the technology was the factor most closely related with course satisfaction and with completion of the course material.

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A combination of the students’ perceptions of their levels of learning, the relevance of the material to the jobs, and their sense of cohesiveness explained a significant amount of variation in the levels of satisfaction with the course (Stonebraker & Hazeltine, 2004). Based on interviews with companies and learning management system vendors, Claire Schooley, of Forrester Research, says that the critical success factors for an e-learning initiative are executive support, the learning staff, and a mix of learning formats including face-to-face, engaging content, and easy-touse technology (Schooley, 2009). Some of Schooley’s recommendations are supported by the quantitative and qualitative research of Slotte and Herbert (2008). They studied 298 sales personnel and 37 sales managers participating in simulation-based virtual learning in Finland. They found that the blended learning design, accompanied by socially situated interaction, made the training much more successful. Like Schooley, Aggarwal and Makkonen based their research on critical success factors on their personal experiences and the experiences of their colleagues, interviews with administrators and technical staff, and informal focus groups. They also received input from seminars, panels, and students. They grouped critical success factors for virtual learning into three categories. In the strategic category, they cite visionary senior management, planning for the initial investment, overcoming institutional resistance, and changing organizational culture. In the tactical category, they list building an e-learning team, realizing that one size does not fit all, developing a “custom-centric” approach, acknowledging that e-learning and e-teaching is not for everybody, and sharing knowledge through learning communities. In the operational category, they list creating an e-learning environment on the web, developing course content and management policies, thinking globally and acting locally, developing an e-learning infrastructure, and implementing an ongoing learning assessment process (Aggarwal and Makkonen, 2009). Starke-Meyerring and Andrews managed a virtual learning project that included team members from different cultures. They recommend building interaction into all the instructional strategies, treating team members equally, and providing intensive mentoring, among other strategies. They also stress the use of appropriate technologies and strongly recommend at least one faceto-face meeting of the virtual team members (Starke-Meyerring and Andrews, 2006). In a qualitative study of ten Hong Kong organizations, Chan and Ngai found the key factors influencing the adoption of virtual learning were the

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perceived benefits and costs, organizational readiness, and external pressure. They emphasize that success requires top management support, technically competent users, and the appropriate infrastructure (Chan and Ngai, 2007). Many of the recommendations cited in this section seem clearly designed to counter the barriers or challenges to virtual learning identified in the previous section of this paper. Many of the researchers agree on a number of strategies to help insure the success of virtual learning. These include: • the construction of a cohesive virtual community that provides interaction among the learners; • a learning system that is flexible, customizable and adaptable; • quality content that meets employees’ immediate needs; • appropriate technology infrastructure; • motivated employees with a sense of self-efficacy, competency, and autonomy; • a learning environment that is easy to use; • managerial support; • good facilitators who can be mentors; and • the inclusion of a face-to-face component in the training.

CONCLUSION Overall, the conclusion is clear: Virtual workplace learning can be a successful technique for training employees in the twenty-first century. It has a number of benefits for both employees and employers. There are a variety of issues to consider when implementing virtual learning in the workplace, particularly in SMEs and less developed countries. Research has identified, however, a number of factors that, if implemented, will contribute to the success of virtual workplace learning. For companies, virtual learning can be cost-effective, reusable, and provide consistency across a diverse workforce. It allows for more managerial control and accountability. It can enhance organizational learning and even be proffered as a benefit to prospective employees. Meanwhile, employees will find it adaptable to their needs, less stressful than a classroom environment, and offering great flexibility in time and place. Its content can be easily updated, taken in shorter bursts, targeted to immediate needs, and can increase employees’ expertise, innovation, and engagement with their jobs.

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At the same time, the characteristics of the learning systems, the workplace environment, and the employees must be taken into account when implementing virtual learning. Some important professional development topics may not be suited to virtual learning, the usability of the system must be maintained, and the pedagogical design of the training must be appropriate for the learners. Adequate technical and training staff must be available. The workplace must support virtual learning, both physically and culturally. Here, the support of key managers is critical. Research has identified many critical factors that enhance the probability of successful virtual workplace learning. These include a vibrant virtual community, a flexible learning system with high quality content and appropriate technological infrastructure, employees who have the skills and motivation to use the system, good trainers, and the blending of virtual and face-to-face training. Here again, managerial support is vitally important. Virtual workplace learning has not met every promise that has been made on its behalf; nor should it meet them. As with any tool, virtual learning has its appropriate uses. Just as traditional lectures are most efficient or effective to present some kinds of material while hands-on workshops are best for other types, so virtual learning has its place in the workplace training portfolio. As technologies such as simulation and virtual reality continue to develop, new varieties of virtual learning will appear that may broaden its reach. Employers willing to take the care to implement virtual learning thoughtfully will reap its benefits, both for the company and the employees themselves.

REFERENCES Aggarwal, A. K., and Makkonen, P. (2009). Critical success factors for successful globalised e-learning. International Journal of Innovation and Learning, 6 (1), 92–109. Alavi, M., and Leidner, D. E. (2001). Research commentary: Technology-mediated learning—a call for greater depth and breadth of research. Information Systems Research, 12 (1), 1–10. Ali, G. E., and Magalhaes, R. (2008). Barriers to implementing e-learning: A Kuwaiti case study. International Journal of Training and Development, 12 (1), 36–53. Allan, B., and Lewis, D. (2006). The impact of membership of a virtual learning community on individual learning careers and professional identity. British Journal of Educational Technology, 27 (6), 841–852. Allison, S. (2007). E-learning in the age of multimedia. e.learning age (September), 20–21. Alonso, F., Manrique, D., and Viñes, J. M. (2009). A moderate constructivist e-learning instructional model evaluated on computer specialists. Computers & Education, 53 (1), 59–65.

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Robert G. Brookshire et al. Ardito, C., Costabile, M. F., De Marsico, M., Lanzilotti, R., Levialdi, S., Roselli, T., and Rossano, V. (2006). An approach to usability evaluation of e-learning applications. Universal Access in the Information Society, 4 (3), 270–283. Bell, J. (2007). E-learning: Your flexible development friend. Development and Learning in Organizations, 21 (6), 7–9. Chambers, J. A., and Sprecher, J. W. (1980). Computer assisted instruction: Current trends and critical issues. Communications of the ACM, 23 (6), 332–342. Chan, C. H., and Ngai, E. W. T. (2007). A qualitative study of information technology adoption: How ten organizations adopted web-based training. Information Systems Journal, 17 (3), 289-315. Birchall, D., and Giambona, G. (2007). SME Manager Development in Virtual Learning Communities and the Role of Trust: A Conceptual Study. Human Resources Development International, 10 (27), 187–202. Falconer, L. (2006). Organizational learning, tacit information, and e-learning: A review. The Learning Organization, 13 (2), 140–151. Gallaher, J. and Wentling, T. L. (2008). The adoption of e-learning across professional groups. Performance Improvement Quarterly, 17 (3), 66–85. Githens, R. P. (2007). Older adults and e-learning: Opportunities and barriers. Quarterly Review of Distance Education, 8 (4), 329–338. Hiltz, S. R. (1986). The “virtual classroom”: Using computer-mediated communication for university teaching. Journal of Communication, 36 (2), 95–104. Honey, P. (2001). E-learning: A performance appraisal and some suggestions for improvement. The Learning Organization, 8 (5), 200–202. Hornik, S., Johnson, R. D., and Wu, Y. (2007). When technology does not support learning: Conflicts between epistemological beliefs and technology support in virtual learning environments. Journal of Organizational and End User Computing, 19 (2), 23–46. Keller, C. (2005). Virtual learning environments: Three implementation perspectives. Learning, Media and Technology, 30 (3), 299–311. Leary, J. and Berge, Z. L. (2007, Fall). Challenges and strategies for sustaining eLearning in small organizations. Online Journal of Distance Learning Administration, 10 (3). Retrieved from http://www.westga.edu/~distance/ojdla/fall103/berge103.htm (accessed February 6, 2009). Lim, H., Lee, S., and Name, K. (2007). Validating e-learning factors affecting training effectiveness. International Journal of Information Management, 27, 22–35. Littleton, K., and Whitelock, D. (2004). Guiding the creation of knowledge and understanding in a virtual learning environment. CyberPsychology and Behavior, 7 (2), 173–181. Luarn, P., Chen, M. I. J., and Lo, P. K. Y. (2007). Critical success factors in introducing e-learning. International Journal of Information Technology and Management, 6 (2/3/4), 209–231. Pancucci, D. (May 28, 2002). Finding the right blend. Personnel Today, 22–24. Park, J., and Wentling, T. (2007). Factors associated with transfer of training in workplace e-learning. Journal of Workplace Learning, 19 (5), 311–329.

Virtual Workplace Learning: Promises Met? Pearson, E., and Koppi, T. (2003). Essential elements in the design and development of inclusive online courses. International Journal on E-Learning, 2 (4), 52–59. Piccoli, G., Ahmad, R., and Ives, B. (2001). Web-based virtual learning environments: A research framework and a preliminary assessment of effectiveness in basic IT skills training. MIS Quarterly, 25 (4), 401–426. Rivera, R. J., and Paradise, A. (2006). State of the Industry in Leading Enterprises: ASTD’s Annual Review of Trends in Workplace Learning and Performance. Alexandria, VA: American Society for Training and Development. Roca, J. C., and Gagné, M. (2008). Understanding e-learning continuance intention in the workplace: A self-determination theory perspective. Computers in Human Behavior, 24 (4), 1585–1604. Roy, A. and Raymond, L. (2008). Meeting the training needs of SMEs: Is e-learning a solution? The Electronic Journal of e-Learning, 6 (2), 89–98. Santos, O. C., Boticario, J. G., Fernández del Viso, A., Pérez de la Cámara, S., Rebate Sánchez, C., and Gutiérrez y Restrepo, E. (2007). Basic skills training to disabled and adult learners through an accessible e-learning platform. In Universal Access in Human-Computer Interaction, Applications, and Services, 796–805. Berlin: Springer. Schooley, C. (2009). The ROI of eLearning. Retrieved July 2, 2009 from Forester Research, Inc. at http://www.forrester.com/Research/Document/Excerpt/0,7211,53282,00.html. Servage, L. (2005). Strategizing for workplace e-learning: Some critical considerations. The Journal of Workplace Learning, 17 (5/6), 304–317. Simmering, M. J., Posey, C., and Piccoli, G. (2009). Computer self-efficacy and motivation to learn in a self-directed online course. Decision Sciences Journal of Innovative Education, 7 (1), 99–121. Simmons, J. (2006). E-learning and earning: The impact of lifelong e-learning on organisational development. European Journal of Open, Distance and E-Learning. Retrieved January 28, 2009 from http://www.eurodl.org/materials/contrib/2006/Jane_Simmons.htm. Simon, M. (2009, January). E-learning no how. T+D, 63 (1), 34–39. Slotte, V. and Herbert, A. (2008). Engaging workers in simulation-based e-learning. Journal of Workplace Learning, 20 (3), 165–180. Starke-Meyerring, D., and Andrews, D. (2006). Building a shared virtual learning culture: An international classroom experience. Business Communication Quarterly, 69 (1), 25–49. Stonebraker, P. W., and Hazeltine, J. E. (2004). Virtual learning effectiveness: An examination of the process. The Learning Organization, 11 (3), 209–225. Tallent-Runnels, M., Thomas, J. A., Lan, W. Y., Cooper, S., Ahearn, T. C., Shaw, S. M., and Liu, X. (2006). Teaching courses online: A review of the research. Review of Educational Research, 76 (1), 93–135. Tsiantis, L. E., Stergiou, E., and Margariti, S. V. (2007). Security issues in e-learning systems. In T. E. Simos and G. Marouis (eds.), Computation in Modern Science and Engineering, Proceedings of the International Conference on Computational Methods in Science and Engineering 2007, 959–964.

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CHAPTER 11

The Care and Feeding of Interns: A Framework for Maximizing Intern Learning and Productivity KEVIN E. MCEVOY, PhD University of Connecticut

ABSTRACT

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raduate-level business school internships provide experiential learning activities that are considered opportunities for adult students to apply what they have learned in coursework to solving problems, developing communications and teamwork skills, and advancing their identity as a professional. Internships also provide benefits to sponsoring organizations. However, there is more to creating a successful internship program for interns and organizations than simply placing an intern inside a work environment. This article contributes to the area of organization effectiveness through internships by presenting a framework for intern management and development through partnerships between universities and organizations. This partnership framework creates a unique environment in which MBA-level interns can both learn and contribute to organization objectives by working in teams under both managers and professors simultaneously to meet organizational goals. Managers provide organization resources, internal

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expertise through specific subject matter experts, while professors provide methodological support and theatrical concepts that support organizational tasks and activities. The environment is a blend of workplace activity and teamwork with independent study. Rather than a conceptual framework, this framework has been tested and utilized by a global manufacturing organization with marketing MBA interns. This article presents the organizational and interns’ experience that provides proof of concept for the framework.

TODAY’S BUSINESS NEED FOR QUALIFIED INTERNS Education is an endeavor that can dramatically affect the cultural, political and economic aspects of society (Arendt, reprinted 1993). Both culture and commerce in the United States are based on a market-oriented economy, suggesting that both are affected by marketing (Kotler, 1999)—the practice of which is, in turn, affected by how marketing education is conducted (Leventhal, 2002). Marketing education has evolved over the years from a training activity traditionally completed on-the-job into an academic degree, but wherever they are learned, marketing skills include analytical, interpersonal and creative components. New marketers must be prepared with these skills and other knowledge required by employers (Floyd and Gordon, 1998) who face increasing pressure from global competition (Kennedy, Lawton, and Walker, 2001), creating urgency within marketing practice for these skills. In this new global environment, knowledge, know-how, wisdom, and character have emerged as required skills (Gill and Lashine, 2003). In a comparison of employers’, recruiters’, and students’ expectations regarding required skills, many employers noted problem-solving skills to be more important than communication skills, work experience, and interpersonal skills (Floyd and Gordon, 1998). Beyond analytical, interpersonal and creative skills, many employers consider communication even more important than specific content knowledge in marketing, and believe that it is a key missing component in marketer employment preparation (Young and Murphy, 2003). Communication skills are important tools in the development of early marketers’ verbal skills and advanced marketers’ writing skills (Young and Murphy, 2003; Floyd and Gordon, 1998; Silk, 1960). Other employers add interpersonal and team capabilities to communication as important requirements for success (Walker, Hanson, Nelson, and Fisher, 1998). Other studies found problem-solving skills as most important while suggesting communication, analytical-thinking, and ambiguity-tolerating skills are

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absent in new marketers (Smart, Kelley, and Conant, 1999). Effective written and verbal communication, presentation, teamwork, critical thinking and quantitative reasoning are considered more important than a special major, including marketing (Taylor, 2003). New marketers also benefit from analytical, communicative, and multi-disciplinary skills, as well as a knowledge of global cultures, laws and regulations, and character traits such as individual responsibility, self-motivation, self-esteem, sociability, self-management, integrity (Gill and Lashine, 2003), and curiosity (Nadler, 1987). Skill sets considered deficient include critical thinking for problem solving, understanding financial perspectives, leadership and communication skills (O’Brien and Deans, 1995). In addition, lack of analytical thinking also appears a key concern; “after four years, most students can regurgitate details from a textbook, but few can think” (Rotfield, 1993, p. 10). In addition to the integration of marketing concepts through critical thinking, creativity training is needed so that creativity does not diminish with age, experience, or exposure to environmental factors within the organization (McIntyre, Hite, and Rickard, 2003). To add value to the business community, students need to be able to creatively generate ideas and concepts to meet future challenges, a capability very difficult to achieve but necessary for recent graduates (Ackerman, Gross, and Perner, 2003). Employers suggested that while optimistic about students’ ability to learn about the functional and practical issues in the business environment, they were skeptical about students’ ability to learn the necessary critical thinking and creative skills required to be effective in marketing. Some have considered degree level achieved by new employees to correct any deficiencies in business preparation, relying on the Master of Business Administration degree (the MBA) to fill any perceived gaps. The MBA degree is a newer, more recently introduced educational program, now only about one hundred years old. There have been a rapidly growing number of new MBA graduates entering the workforce and observations about MBA preparation are being made. MBA programs focus on hard skills at the expense of soft skills (Hulsart, 2002). MBA curriculums do not focus on leadership, creativity or entrepreneurship; lack emphasis on teamwork; are often not integrated between subjects; are theory-oriented and lacking focus on practical implementation (Neelankavil, 1994). Possessing an MBA degree does not correlate with long term career success, and grades earned in courses do not accurately predict career success (Pfeffer and Fong, 2002). MBA degrees need to become more practical (Richards-Wilson, 2002). Formal education, even at the MBA

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level, is not enough preparation for today’s workplace. The issue of preparation for the workplace remains. Another method used to correct any deficiencies in business preparation is business student participation in internships. Internships are intended to provide real world experience (Clark, 2003) for learners not possible to fully obtain through formal learning classroom methods. In addition, internship participation may affect the hiring process for participants after graduation (Paulins, 2008), with results showing an enhanced ability to be hired (Gault, Redington, and Schlager, 2000). The learning and hiring experience for marketers with internship experience has not yet been fully explored (Alpert, Heaney, and Kuhn, 2009).

THE LIFE OF INTERNS The term “employability” has been tossed around by politicians, journalists, and business leaders in assessing the value of a college education. Higher education at all levels is being charged with creating not only global citizens but also individuals who can, on day one of their new job, create value for an organization. Even individuals considering an MBA are “seeking assurances that a chosen school will propel them on a desired career path” (Korn, 2013). Ensuring employability and career success, however, cannot be the sole responsibility of the university. There is a call for approaches that can integrate study and work, creating new types of partnerships that “promote individual competence, business innovation, and global competitiveness” (Soares, 2015, p. ix). In other words, there is a call for new ways to determine how universities can better prepare students for employability (Stokes, 2015). MBA graduates traditionally have had some work experience behind them, but a recent trend is indicating that an increasing number of business schools are accepting students with little or no business experience (Dillon, 2011). Graduates of all ages who enter the workforce with experiential learning experiences, whether they be from part time jobs, internships, service learning, or civic engagement activities, generally are considered more employable than those without work experiences (Knouse and Fontenot, 2008). Experiential learning activities can instill interpersonal skills, problem-solving skills, critical thinking abilities, and communications skills (Young and Murphy, 2003; Floyd and Gordon, 1998; Silk, 1960). The staple of business school experiential learning, the internship, sometimes instills these skills and other times misses the mark. The questionable assumption is that by simply making a good

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organization/intern match, the student will be engaged in valuable activities (Moore, 2013); internships, to be effective, must be meaningful. This article proposes a framework based on a partnership between a business school and an organization that has been touted for its success in building high level skills. How learning happened in this co-created and co-supported internship environment is identified. Characteristics of the interns, their learning strategies, and the affordances that the workplace managers and the university faculty melded together to create this program. We look at what went on as though the students themselves were new employees, learning to practice their craft.

THEORETICAL FRAMEWORKS AND STUDIES THAT INFORM THIS FRAMEWORK Theoretical frames and empirical studies related to experiential learning and employability, skill development, individual learner characteristics, and organizational affordances combine to provide a foundation for this study.

Experiential Learning and Employability John Dewey has described all learning as social. Dewey purported that learning should result in critical thinking skills and learning how to learn rather than having curriculum developed and delivered by experts (Dewey, 1938). Experiential Learning Theory (ELT) is defined as “the process whereby knowledge is created through the transformation of experience. Knowledge results from the combination of grasping and transforming experience” (Kolb and Kolb, 2005, p. 194). Peter Stokes in Higher Education and Employability (2015) suggested that knowledge creation can be linked with job creation, and academic learning can be linked with applied learning. He cited John Sexton, then-President of the New York University, who has suggested that NYU’s mission, while focused more on learning than professional outcomes, acknowledges that going to college must also be a ticket to a good job. The demand for return on investment of tuition dollars in the form of employability is a force that even research universities are considering to be a call for experiential learning at all levels of education. Intended to provide real-work experiential learning, internships can provide experiential learning opportunities that the classroom cannot (Clark,

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2003). Internships for MBA students, increasingly coming into programs without the once expected five years of business experience, can help ensure their employability (Paulins, 2008; Alpert, Heaney, & Kuhn, 2009). More­over, the organization benefits when theoretical frames are tested and problems are addressed in new ways. By supporting internships, an organization can help ensure the transfer of learning, and in some cases actually vet new employees (Stitts, 2006).

Skill Development Marketers tend to be both analytical and creative, dealing with topics as diverse as accounting in profit and loss statements, statistics in marketing research, and graphic design in advertising art. This range of action suggests that both quantitative and qualitative thinking skills need to be developed, but there is debate on how to describe skill development. One description is Fuller’s Model of Teacher Development: survival, task, and impact (Fuller, 1970). Another is Dreyfus and Dreyfus’s discrete five-stage competency development model: novice, advanced, competent, proficient, and expert (Dreyfus & Dreyfus, 1986; Dreyfus & Dreyfus, 2005). Can these linear models explain marketers’ workplace learning experiences? Is the creativity necessary in marketing more amenable to learning in conjunction with and from others as suggested by technically based situated learning apprenticeships (Gott, 1989) or more oriented to learner disposition in what and how learning occurs (Billett, 1993)? Learning to be a marketer may better be described based on the process of doing and experimenting as suggested by action learning (Marsick, 1988; Marsick, 1991), which includes a reflection stage. And even deeper learning may be gained through self-reflection after a significant life-orienting experience, such as a major workplace challenge (Mezirow, 1990; Daley, 2001). These approaches can be useful in describing how a marketer learns to navigate his/ her workplace.

Individual Characteristics Yet another dimension for understanding workplace dynamics is the individual him/herself. The individual possesses certain characteristics that make learning at and through work possible, including self-direction, critical thinking, self-regulation and control, reflection, self-esteem, self-efficacy, motivation, and proactivity (Eraut, 2004).

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In a very early study of adults’ self-directed learning, learners’ expectations, the learners’ skills, knowledge base, and available resources affected their learning (Spear & Mocker, 1984). Later research showed individual responsibility, individual control, and integrated critical thinking were important (Garrison, 1992). Learner control was also connected to flexible learning in the context of how organizations attempt to offer affordances (Kay, 2001). Self-directed learning also appeared connected to self-determination and motivation, which is considered a naturally developing characteristic in individuals (Rigby, Deci, Patrick, and Ryan, 1992). Critical thinking begins with a learner’s habitual actions followed by understanding, reflection, and intense reflection. A survey of 220 recent MBAs (those who graduated no more than three years prior) found “student-tostudent” and “instructor-to-student” interactions to be important (Peltier, Hay, and Drago, 2005). Self-efficacy and workplace performance was also studied in a meta-analysis of 114 studies. Results indicated that self-efficacy affected a variety of elements from the level of complexity of activities attempted to the learner’s choice of career (Stajkovic and Luthans, 1998).

Organizational Affordances How an organization develops learning a culture is a product of its commitment to their employees’ development. Goller and Billet (2014) have suggested that neither training nor intelligence can explain employees’ development as “convincingly as effortful engagement in domain-related experiences” (p. 28). The opportunity for authentic work and problem solving experiences related to one’s area of study is what an internship is all about. Researchers who interviewed interns after an internship experience suggested that one exemplary practice by the interning organization was the structure that supported informal learning (Beenen, G., and Mrousseau, D., 2010). For example, encouraging teamwork was a useful approach to the exchange of knowledge, ideas, and experiences. In fact, teamwork affects organizational commitment, satisfaction, turnover intention, socialization, and learning (Major, Kozlowski, Chao, and Gardner, 1995); psychological safety (Van den Bossche, P., Gijselaers, Segars, and Kirshner, 2006); and organizational performance (Fisher and O’Connor, 2014). Other approaches included ensuring that new employees have opportunities for socialization and enculturation (Bauer and Green, 1998; Morrison, 1993). In fact, findings from a longitudinal study of 594 new engineers and

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managers showed that the socialization process itself directly affected the identification of what needed to be learned and how well it was learned (Chao, Wolf, Klein, and Gardner, 1994). The faster socialization and enculturation occurred, the faster the employee was able to contribute to the organization’s success. An important set of studies closely related to this investigation provided insights into early career learning within the nursing, engineering, and accounting professions. Data from over two hundred interviews resulted in a typology of tasks (such as problem solving, participating in group processes), learning actions (for example, asking questions, listening, reflecting), and support both within and outside the workplace (for example, being supervised, coached, mentored). Learning for practical application involved not only skillset development but when, wherem and how to use the new skills. Findings led to further questions of learning contexts and environment, and differences between formal education and learning on the job (Eraut, 1994; Eraut 2004; Eraut et al., 2004; Eraut et al., 2005, Eraut, 2011).

The Research Questions These frames and studies related to experiential learning and employability, skill development, individual characteristics, and organizational affordances guided this study. We wanted to know how the partnership between the university and the organization helped ensure that interns were supported, learned, and performed. Specifically, we asked, how did these interns learn to navigate the work environment and hone their marketing skills? What did the organization and the university do in tandem to support such learning?

THE CASE STUDY RESEARCH METHOD Taking a constructivist approach to inquiry, the case study requires the researcher to develop an in-depth analysis of a situation bounded by time and activity (Creswell, 2006). The case itself can center on a typical, exceptional, or purposeful case, depending on the research question posed. While case study findings are typically not generalizable, results can provide insights into practices. The method requires extensive, in-depth data collection through many onsite visits for interviews and observations. We chose to focus on a purposeful site—an exceptional partnership that had resulted in an innovative internship program.

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The Research Site ThinkTank (a pseudonym) is a small marketing and product development research facility specializing in marketing, market research, and product development in a wide variety of product and service areas. It is a wholly owned subsidiary of Global Products (also a pseudonym), a very large global marketing, manufacturing, finance, and distribution conglomerate that manufactures and markets products in a wide variety of product and service categories. ThinkTank has historically had a long term and significant interest in employee learning, development, and career growth. Its internship is considered an exemplary learning opportunity for all stakeholders. The director gave the primary researcher a high degree of accessibility to both its facility and its people, making this an appropriate location for this study. ThinkTank has its own management team who, while employees of Global Products, operate independently. Managers contract with the university for physical on-campus space and pay the interns. The facility itself has very hightech presentation rooms, meeting rooms, conference rooms, offices, showcase rooms and individual workplaces (cubes), with sophisticated equipment and internet connections. Access is limited; entrance is secure and requires an eye scan. Laptops and computer hardware appear everywhere, so employees are never more than a few steps away from Internet connectivity and computer access. Graduate student interns sit in cubes bundled together in project team groups. Managers sit in private offices along the outer walls, with the cubes located in the middle of a large workspace. A large presentation area, isolatable by an automatic moving wall, provides a presentation theater for videoconferencing presentations and meetings. Another room holds a large presentation screen plus a high tech white board that can record, store, and print whatever is written or drawn on it. A showcase room houses a number of technological product samples. A kitchen area is also installed with a full size refrigerator, microwave, coffee machines, and a five-gallon water bubbler. Competition was strong; in this semester, fifty students applied for each full-time semester-long internship placement. Criteria for selection included a superior academic record, very strong recommendation letters, and results of a Global Products skills matrix that assessed both hard and soft skills. Applicants also needed to demonstrate that they could think and work independently as well as in a team. Leadership and teamwork skills were required, as were English language skills.

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Research Procedures Upon request, the faculty invited the primary researcher to present a brief description of the study to all team members, including interns, at a regularly scheduled meeting. They then emailed participation invitations to the marketing interns. Those interested responded by email to the researcher, and six volunteers who had been assigned to two separate project teams (three on each team) participated. In addition to the interns, three faculty advisors, the faculty reference librarian, and two corporate managers (including the director) agreed to be observed and interviewed.

The Internship Projects Supported by faculty and mangers, the project teams are referred to here as the Power Team and the Medical Team (pseudonyms). The Medical Team was to develop a marketing plan for a new product concept in the consumer medical products area, and the Power Team—in the business-to-business energy distribution area. Interns were expected to test the product’s conceptualization, its fit with the organization’s direction, and assess market opportunity. In creating the confidential plan, they also estimated costs and potential profits. The teams operated in the highly iterative nature of product development and review. Throughout the semester, interns presented their work periodically to both the managers and their faculty advisors. Feedback was given on content as well as presentation style. Each of as many as five dry runs were “practice” for a final presentation. The dry runs were Socratic in nature, leading the interns to a final project. Interns could create their own tools or methods to solve new problems.

Data Collection and Analysis Interview and observation data were collected throughout a thirteen-week semester. More than sixty-four open-ended interviews of one or two hours each were conducted with the interns, the faculty advisors, the business reference librarian, and the two corporate managers. Observation sessions, in which the researcher shadowed participants varied from two hours to an entire workday. This included attendance at meetings, group discussions, social events, business meals, and business social activities; at all events, the researcher played the role of a non-participating observer. A field log that included analytical memos was kept of all interviews and observations.

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Atlas.Ti© was used to compile and analyze data. Data analysis consisted of recursively reviewing the field log to note any similarities, commonalities, differences, corroborations, refutations, insights, comments, thoughts, beliefs, and impressions in the recorded data. As information emerged from the data, a code was assigned to each data point. The number of times in which each coded data point emerged from the transcriptions was also recorded as potential evidence of importance. Once the codes were identified, code families were created by identifying how coded data appeared to fit together into patterns. These patterns combined to become the significant themes emerging from the data.

THEMES The four themes that follow are organized around the central characteristics of the partnership—the synergy of the stakeholders, the safe learning environment, and the importance of teamwork to community and confidence. The patterns for each theme are identified below. 1. An effective partnership is one that engages all stakeholders. Patterns: application of learning, curiosity, challenges, feedback, commitment, support. Perhaps, ThinkTank’s director best summarized the benefits of having a campus site and MBA-level interns and their faculty participate together: What I want to do is I want to show the businesses…. This is how academia does marketing, these are the best practices that we can glean out of emerging academic research, and some new ways that we can do marketing that we don’t today. So that’s kind of the overall philosophy on that. Specifically we’re looking to be able to get new techniques from academia and introduce them into industry.

Does this actually happen? He said it did: “…some marketing best practices were things that came out of academia that really helped us.” For example, in one dry-run episode, a faculty advisor suggested that when applying academic models, they were to describe the model and then its application into the business application. In a later session, she reiterated: “The models we are using are not for academic discussion but to provide practical application.” Thus, interns were encouraged to make direct connections

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between theory and practice. The interns themselves reported the academic and business collaboration in combining theory and application as one of the main lessons of the collaboration: “…giving a more corporate orientated presentation, trying to bring academic information to a corporate setting.” One intern later explained: “The team was a little iffy … because it was one of those things that sounded good theoretically, but we didn’t know about practical application how it would turn out.” Practical application would provide the answer. Another advantage to the collaboration was the ability to bring additional university academic resources and materials into the business facility. The university business reference librarian visited the facility and hosted question and answer events in the library. “There’s also the university library downstairs for journals[,] … academic journals[,] … other companies’ reports, other types of research that’s available.” The Principles of Marketing textbook one intern had on his desk was taken out of the university library. Moreover, interns found the copies of past projects that the library had kept on file to be valuable as models for their own work. 2. A supportive environment enables individual work as well as teamwork. Patterns: access to information, equipment, and materials, mentoring, and the support of managers in the workplace. To succeed, interns had to work both independently and interdependently to share, modify, and address whatever issues came up. One intern reported that she liked the level of activity this created: What I like is distributing your work, and then coming together, and then sharing your ideas and telling others what you did. Then getting comments from others and then start working again, so it’s like it boils down to the individual work but then you come together and discuss and you come up with new ideas, and then you go back and work on that.

Team management itself required a proactive approach to problem solving. The Power Team needed to work through a number of challenges on the survey section of their project. One intern explained: If somebody has some issue on their own task we’ll just call a meeting of the team and we’ll come into this room … and discuss, and basically

The Care and Feeding of Intern after the discussion we’ll have some kind of solution. Either we’ll know what to do or we need some extra help from the faculty members or the ThinkTank staff.

3. Confidence was built through teamwork and a relatively riskfree environment. Patterns: critical thinking, feedback, self-direction, self-esteem, selfefficacy, teamwork. The interns’ ability to quickly jump into complex problems depended on their confidence in both themselves and the environment. Interns had the opportunity to make their individual preferences known about their tasks and activities. In doing this, they also had the opportunity to build their expertise and confidence in the areas they wanted. One intern stated: “I chose to do the analysis and I think I was very successful in doing that.” Another intern, when describing what might happen if she did not know how to do something (which was a certainty in this environment), responded: When you study stuff and you learn things you know exactly what it is so if you are doing something wrong you know how it can be corrected[,] … if you don’t know how it can be corrected, then … you panic, but if you know that it can be corrected you don’t panic.

A faculty advisor concurred that confidence came in part from the teamwork-oriented culture: “They have to have both capabilities to be a supportive person in a team environment, to use their skills to back up other people’s weaknesses, and use other people’s skills to develop their weaknesses—which is one of my functions—to form a working team that can reinforce each other.” In this environment, a sense of support existed. One intern indicated that she liked the fast paced atmosphere: “I like to have an environment that is a little bit tense so that I feel the pressure and then I think I’ll do better if I feel the pressure and then I like to take the challenge and I think I’ll be able to overcome the difficulties.” Yet another intern commented: “I think if I’m learning things in this kind of environment—it’s just a very safe environment to make mistakes, to take risks.” She added: “There’s a big difference between what you decide in a safe environment and what you decide in a totally uncontrollable environment,” and then said: “I would be more aggressive here than in other job situations.”

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Learning was based on trial and error, guided experimentation and risk taking—all through the teamwork experience. This was also supported by the concept of disruptive thought, based on the philosophy of creating opportunities for breakthroughs. This dynamic is dependent on teams that are comfortable taking such risks and being willing to forward controversial ideas, the Director explained: …the team will be arguing with a faculty member, they’ll be arguing with a staff member and what’s nice is that … we’ve typically got two faculty members, two staff members, and then the graduate students and so as we start conversations, you try to get all those different opinions onto the table so that everybody is kind of able to understand the way you approach something and then you come to a consensus as to the best way to do that….

4. Socialization and enculturation evolved through teamwork. Patterns: socialization, enculturation, teamwork, culture, coaching, risk-taking. Teamwork pervaded every aspect of intern activity in ThinkTank. The interns, faculty advisors, and corporate partners all operated as teams. As one manager explained about the teamwork philosophy: “This is a partnership.” Teamwork was a priority from the beginning of the semester. On both projects, the ability to work within a team structure was a mandatory component. The environment, the projects, and the culture were all based in the teamwork concept. The interns recognized this from the start as well: “I think that’s a good approach for this kind of task, teamwork.” When comparing various approaches to accomplishing tasks another intern said: “I think teamwork is better.” The bonding of team members into function teams quickly was very important if project timelines were going to be met. Specific socialization activities such as Ethnic Edibles Food Day, where team members brought in foods from their home areas, described and shard them for full meals. One team member commented this was his “favorite day of the semester” since it got everyone together in the same place at the same time. Movie Night was another such activity where movie selections were discussed and voted on, supported quickly breaking the ice and developing a team identity. One team member commented: “I thought I’d work through the movie, but I never saw Iron Man.” An important outcome of socialization supported tem work was in team conflict

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resolution. Regarding team interactions and the handling of conflict, one team member stated, “I think it’s easier because … we are friends, we are very tolerant and at the same time it’s easier for friends to fight. When you are not friends it’s more difficult to criticize, because you want to be polite.…” Socialization is closely correlated with enculturation, in which the organization creates and fosters an environment designed to enhance learning. From this process the learner begins to accept the organization’s values, understand the culture, associate themselves with the organization and its mission, and begins to fit in. The physical layout of the facility was specifically designed to the development of teamwork by encouraging socialization and enculturation. The close proximity to each other and the team project focus all worked together to create teams almost overnight. The teams’ cubes were organized by teams. Status meetings, dry runs, and final presentations were conducted by individual teams in this task-supported environment. The Power Team’s questionnaires and the Medical Team’s blog were both examples of important project activities that were developed through teamwork. One intern commented that the environment made it easier to take risks such as sharing: “…we have to learn from each other.” Another agreed: “I think the way we are learning is by asking each other.… I think I’m learning more because I’m on a team.” Teamwork provided both learning and task completion opportunities, allowing interns to develop an identity as a marketing professional. Brainstorming, sharing, question and answers, experimentation, and presentations were team activities. The key project components were tackled by teams. A surprising finding was how quickly the teams coalesced into a unit. Socialization activities such as Ethnic Edibles Food Day and Movie Night, the close proximity to each other and the team project focus all worked together to create teams almost overnight. The entire culture seemed directed at developing this, and given the success of the Final Presentations, worked very well.

DISCUSSION AND IMPLICATIONS Our goal was to investigate what was considered to be an exemplary MBA-level internship, one that met was the result of a committed partnership. We wanted to depict the approach that the university and the organization used to provide a unique learning experience. In doing this, we asked, how did these interns learn to navigate the work environment and hone their marketing skills? What did the organization and the university do in tandem to support such learning?

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How did these interns learn to navigate the work environment and hone their marketing skills? Consistent with early research (Eraut, 2004; Garrison, 1992; Spear and Mocker, 1984), an intern’s self-direction was important. Even with state-of-the-art technology, a world-class library, previous project files, and on-site experts, the interns needed to navigate the worksite themselves. How to work around gaps in resource support was a challenge the interns experienced as they met time-sensitive challenges. This included when and how to ask for access, how to find alternate channels of information, and how to present a case for access permissions. Skill development was in no way linear. Knowledge and skills were learned quickly, and reflection was vital. The students who had had little formal work experience in marketing prior to this experience had a steeper learning curve, but they navigated that curve rapidly. Using Fuller’s model (1970), one could say that their survival stage was very short, but in this environment, learning could better be described as organic. These individuals were in a situation where there was no one-right-way to do the tasks they were asked to do, and so they had opportunity to explore—independently and interdependently—their options. Marsick’s (1991) and Daley’s (2001) description of self-reflection, evidenced by the descriptions that the interns offered of their workplace challenges, is a much better way to understand their development. When a learner has control over how a project can be completed, the environment must support the individual’s development and maximize the opportunity to learn (Rigby, Deci, Patrick, and Ryan, 1992; Kay, 2001; Moore, 2013). Perhaps this is why ThinkTank managers looked for the individual motivation as well as the ability to work within a team when recruiting for positions. Not only was personal motivation desirable, it was required for an intern’s success within this creative environment. The interns described their experiential learning as more effective than any formal training they had received. Together, they were able to solve complex problems in new ways. The iterative nature of the dry run sessions, including constant challenges, questions, and revisions created a structured environment of continuous learning and development within a supportive, individual growth minded environment. Repetitive, ongoing challenges leading to new insights and ideas created feedback loops, helping to establish a path to mastery of both process and product, which is fundamental to the development of expertise.

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What did the organization and the university do in tandem to support learning? This internship program was a partnership between the university and the sponsoring organization. As partners, faculty worked closely with the sponsoring organization to identify appropriate projects and match interns to those projects. Depicted here was a description of their planning efforts and how the internship evolved. An incredibly vital relationship grew between faculty advisors and the interns, as well the university’s reference librarian. The physical facility itself was designed to foster innovation and teamwork, but it was the workplace learning culture that resulted in a relatively risk-free environment that helped nurture intern creativity. A limitation of this study is that we there is no real way of knowing just how creative these interns actually were. The rush to get projects done within a tight timetable (a real-world issue) may have led to some de-optimization of potential talent. Moreover, these individuals had an opportunity to be creative but creativity itself is something that is virtually impossible to measure. That said, perhaps the ultimate value of this investigation is the depiction of the incredibly important relationship among the three key sets of players— the university (faculty, librarians), the managers, and the students themselves. Demonstrated here is how interns worked independently and interdependently in problem solving and project completion within a very supportive learning culture that was created by the partnership of the university and the sponsoring organization. These interns were not simply introduced to a worksite and project. While they were independent, they had a repertoire of university and organizational support services they could call upon. The combination of autonomy, teamwork, and culture combined to create exemplary experiential learning, a response to Soares’s call for new ways to ensure employability by integrating work with learning.

RECOMMENDATIONS FOR RESEARCH AND PRACTICE An effective partnership is one that is a win-win for all stakeholders. Through a series of targeted exemplary case studies, we could continue to identify strategies that have been used to ensure value to students, university staff, and managers. The cases could focus on an examination of the roles of all stakeholders and how the influence of multiple stakeholders with potentially different agendas have been combined to ensure learning occurs. The appropriate

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level of stakeholder support and direction without overmanaging or overwhelming interns could be better established and could change with organization size, type of industry, and complexity of the experiential projects. A supportive environment enables individual work as well as teamwork. Here, we saw a combination of individual and group assignments, tasks, challenges, and objectives that worked synergistically to create learning opportunities to meet project objectives. How can individual and group tasks be assigned and managed to maximize this potential in the shortest period of time? What type of support works best? Does this change from industry to industry or from individual to individual? Further research in this area may provide insights that can support interns, their universities, and their sponsoring organizations in working well together. Confidence was built through teamwork. Is this confidence built within the individual, such as in self-esteem, or within specific activities, as in selfefficacy? Does this confidence continue when a project ends? Further research can help our understanding of the effects of teamwork in developing confidence work, which may lead to organizational practices that can both help develop and sustain confidence. Also, community evolved through teamwork. Teams are an entity within a larger structure, in a sense, like a neighborhood within a city. As a team becomes effective and influential, it can begin to have an effect on organizational learning and culture, which can affect the future direction of the organization itself. Having said that, there is more to discover about this process. How does a team evolve into a community? At what point does a community form? How does an evolving community affect organizational culture? Perhaps most importantly, how does community and culture affect organizational learning help create a learning culture?

Implications for Practice Prior to any internship experiences, business classroom pedagogy could include the development of team projects. Projects can help student teams bond quickly. Providing physical space allowing team members to work in close proximity to each other, providing research support with a dedicated librarian or other researcher, and access to subject matter experts regarding technical issues could provide a real-world classroom experience. Providing multiple opportunities for teams to review and present their work (as in the dry-run method used by teams in this study) can support the iterative learning experience so successfully implemented in the study. Professors can simulate environmental

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and activity characteristics of internships if actual internship opportunities are not available, or to supplement the internship experience. If internship opportunities are available, professors can work to provide affordances such as those in ThinkTank. Both businesses and universities could seek out prospective partners based on the industry, segment, and category of the business and of School and faculty foci. A program can begin small with one project by matching a faculty member’s interest and expertise with a relevant organization. Here, we have seen how the grouping of learners by academic discipline (marketing) worked. A further suggestion is to design learning opportunities with sponsors of projects that require interdisciplinary expertise in designing products or services. Teams of interns could come from diverse Schools (for example, Business, Engineering, Education) or fields (such as Marketing, Information Technology, Human Resources Management).

References Alpert, F., Heaney, J., Kuhn, K. (2009). Internships in marketing: goals, structures and assessmentstudent, company and academic perspectives. Australian Marketing Journal, 17 (1), 36. Bauer, T. & Green, S. (1998). Testing the combined effects of newcomer information seeking and manager behavior on socialization. Journal of Applied Psychology, 83 (1), 72–83. Beenen, G., Mrousseau, D. (2010). Getting the Most from MBA Internships, Promoting Intern Learning and Job Acceptance. Human Resource Management, 49 (1), 3–22. Billett, S. (1993). Authenticity and a culture of practice within modes of skill development. Australian and New Zealand Journal of Vocational Education and Research, 2 (1), 1–29. Chao, G., O’Leary-Kelly, A., Wolf, S., Klein, H., and Gardiner, P. (1994). Organizational Socialization: Its content and consequences. Journal of Applied Psychology, 79 (5), 730–743. Clark, S. (2003). Enhancing the educational value of business internships. Journal of Management Education, 27 (4), 472. Creswell, J. W. (2006). Qualitative inquiry and research design: Choosing among five traditions (2nd ed.). Thousand Oaks, CA: Sage Publications. Daley, B. J. (2001). Learning and professional practice: A study of four professions. Adult Education Quarterly, 52 (1), 39. Dewey, J. (1938). Experience and Education. New York: Touchstone. Dillon, M., McCaskey, P., and Blazer, E. (2011). MBA Internships: More Important Than Ever. Journal of Education for Business, 86, 44–49. Dreyfus, H. L., and Dreyfus, S. E. (1986). Mind over machine: The power of human intuition and expertise in the era of the computer. New York: Free Press. Dreyfus, H., and Dreyfus, S. (2005). Expertise in Real World Contexts. Organization Studies, 27 (5), 779–792.

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Kevin E. McEvoy Eraut, M. (2011). Tools for enhancing learning. In M. Malloch, L. Cairns, K. Evans, and B. N. O’Connor (eds.), Sage Handbook of Workplace Learning, chapter 13. London: Sage Publications. Eraut, M. (2004). Informal learning in the workplace. Studies in Continuing Education, 26 (2), 274–273. Eraut, M. (1994). Developing professional knowledge and competence. Bristol, PA: The Falmer Press. Eraut, M., Maillardet, F., Miller, C., Steadman, S., Ali, A., Blackman, C., and Furner, J. (2005). Methodology and theoretical frameworks. Economic & Social Research Council (UK) and Teaching and Learning Research Program (UK) Montreal Conference. Montreal: AREA. Eraut, M., Maillardet, F., Miller, C., Steadman, S., Ali, A., Blackman, C., and Furner, J. (2004). Learning in the Professional Workplace: Relationships between learning factors and contextual factors. Paper presented at AERA Conference, San Diego, CA. Fisher, C., and O’Connor, B. N. (2014). Informal learning in workplaces: Understanding learning culture as a challenge for organizational and individual development. In C. Harteis, A. Rausch, and J. Seifried (eds.), Discourses on Professional Learning, chapter 1. New York: Springer. Floyd, C., and Gordon, M. (1998). What skills are most important? A comparison of employer, student and staff perceptions. Journal of Marketing Education, 20 (2), 103–109. Fuller, F. F. (1970). Personalized education for teachers: An introduction for teacher educators. Austin: Research Development Center for Teacher Education, The University of Texas. Garrison, D. (1992). Critical thinking and self-directed learning in adult education: An analysis of responsibility and control issues. Adult Education Quarterly, 42 (3), 136–148. Gott, S. (1988-1989). Apprenticeship instruction for real-world tasks: The coordination of procedures, mental modes, and strategies. Review of Research in Education, 15, 97–169. Goller, M., and Billet, S. (2014). Agentic behavior at work: Crafting learning experiences. In C. Harteis, A. Rausch, and J. Seifried (eds.), Discourses on Professional Learning, chapter 2. New York: Springer. Kay, J. (2001). Learner Control. User Modeling and User-Adapted Interaction, 11 (1-2), 111. Knouse, S., and Fontenot, G. (2008). Benefits of the business college internship: a research review. Journal of Employment Counseling, 45 (2), 61. Kolb, A., Kolb, D. (2005). Learning Styles and Learning Spaces: Enhancing Experiential Learning in Higher Education. Academy of Management Learning & Education, 4 (2), 193–212. Korn, M. (2013, January 04). Life/Work: M.B.A. pop quiz: Are you employable? Wall Street Journal. Retrieved from http://ezproxy.library.nyu.edu:2048/login?url=http://search.proquest.com/docview/1266268020?accountid=12768. Major, D., Kozlowski, S., Chao, G., and Gardner, P. (1995). A longitudinal investigation of newcomer expectations, early socialization outcomes, and the moderating effects of role development factors. Journal of Applied Psychology, 80 (3), 418–431. Marsick, V. (1991). Action learning and reflection in the workplace. In J. Mezirow (ed.), Fostering critical reflection in adulthood, 23–46. San Francisco: Jossey-Bass. Marsick, V. (1988). Learning in the Workplace: The Case for Reflectivity and Critical Reflectivity. Adult Education Quarterly, 38 (4), 187–198.

The Care and Feeding of Intern Mezirow, J. (ed.). (1990). Fostering critical reflection in adulthood: A guide to transformative and emancipatory learning. (1st ed.). San Francisco: Jossey-Bass. Moore, D. T. (2013). Engaged Learning in the Academy. New York: Palgrave-Macmillan. Morrison, E. (1993). Longitudinal Study of the effects of information seeking on newcomer socialization. Journal of Applied Psychology, 78 (2), 173–183. Paulins, V. Ann (2008). Characteristics of retailing internships contributing to students’ reported satisfaction with career development. Journal of Fashion, Marketing and Management, 12 (1), 105–118. Peltier, J., Hay, A., Drago, W. (2005). The reflective learning continuum: Reflecting on reflection. Journal of Marketing Education, 27 (3), 250–263. Rigby, C., Deci, E., Patrick, B., and Ryan, R. (1992). Beyond the intrinsic-extrinsic dichotomy: Self-determination in motivation and learning. Motivation and Emotion, 16 (3), 165–185. Silk, L. (1960). The education of businessmen. New York: Business-Education Committee of the Committee for Economic Development. Soares, L. (2015). Forward. Higher Education and Employability: Models for Integrating Study and Work. Cambridge, MA: Harvard Education Press. Spear, G., and Mocker, D. (1984). The organizing circumstance: Environmental determinants in self-directed learning. Adult Education Quarterly, 35 (1), 1–10. Stajkovic, A. D., and Luthans, F. (1998). Self-efficacy and work-related performance: A metaanalysis. Psychological Bulletin, 124 (2), 240–261. Stitts, D. K. (2006). Learning to work with emotions during an internship. Business Communication Quarterly, 69 (4), 446–449. Stokes, P. J. (2015). Higher Education and Employability: Models for Integrating Study and Work. Cambridge, MA: Harvard Education Press. Van den Bossche, P., Gijselaers, W., Segars, M., and Kirshner, P. (2006). Social and cognitive factors driving teamwork in collaborative learning environments. Small Group Research, 37 (5), 490–521. Young, M. R., and Murphy, J. W. (2003). Integrating communications skills into the marketing curriculum: A case study. Journal of Marketing Education, 25(1), 57.

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CHAPTER 12

Understanding MBA Students’ Intention to Transfer to Teamwork Skills: A Theory-Based Model CHUNHUI MA, PhD New York University

ABSTRACT

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lthough teamwork skills development is visibly emphasized and built  into the MBA curriculum and extra-curricular activities, the end result— the transfer of teamwork skills to the workplace is not ascertained. Transfer is an individual choice and MBA students’ intention to transfer teamwork skills is essential for the transfer of learning. This article proposes a model based on the theory of planned behavior, which addresses the impact of attitude, subjective norm, and perceived behavioral control on intention to transfer teamwork skills. The model leads to several hypotheses that could be tested to expand our understanding of the intention to transfer teamwork skills. The model also offers potential implications for future research and practice.

Understanding MBA Students’ Intention to Transfer to Teamwork Skills

INTRODUCTION According to Bloomberg Recruiter Report (Bloomberg, 2015, p. 4) and Graduate Management Admission Council (GMAC)’s Corporate Recruiter Survey (2016), teamwork and collaboration continue to be ranked among the top skills emphasized by MBA employers. To prepare students to be effective team players or leaders in the workplace, MBA programs have made efforts to develop and strengthen students’ teamwork skills. A cursory browse of many MBA program websites will not fail to notice words or phrases such as collaboration, collaborative community, teamwork, teams and so on. Teamwork skills development or enhancement is visibly emphasized and built into the MBA curriculum and extra-curricular activities. In MBA programs, teamwork knowledge and concepts are often taught through core management courses where teamwork skills are highlighted and practiced (Tonn and Milledge, 2002). The team projects assigned to students aim to improve their learning outcome related to course content and to develop their teamwork skills (Bacon, 2005). Teamwork knowledge and skills development goes beyond coursework and spans the whole MBA program through multiple avenues such as team-building exercises during the program orientation (Mazany, Francis, and Sumich, 1995), outdoor challenge training (Shivers-Blackwell, 2004), team-based projects in case and business plan competitions, and integrative and experiential field trip projects (Navarro, 2008). Students are expected to develop and/or improve their teamwork skills through their MBA experience. Despite the recognized importance of teamwork skills and the ubiquitous teamwork skills development in MBA programs, little attention is paid to the outcomes of such targeted training. The common assumption seems to indicate that once MBA students go through the whole program, they will apply the acquired or enhanced teamwork knowledge and skills to the workplace. Teamwork skills are soft skills. Anecdotal evidence has indicated that soft-skills training is more difficult to be transferred than hard-skills training because soft-skill trainees may have greater resistance to learning than hard-skill trainees (Laker and Powell, 2011). Will MBA students intend to transfer the teamwork skills to the workplace? Since behavioral intention might be the most influential variable to predict human behavior (Ajzen, 1985, 2002), it is important to understand learners’ intention to transfer, a critical motivational factor in the transfer process. This article presents a theory-based model to uncover the important

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determinants that can affect MBA students’ intention to transfer teamwork skills to the workplace. I apply the theory of planned behavior (TPB) (Ajzen, 1985, 1991) to explore MBA students’ intention to transfer teamwork skills. I start with brief overviews of the TPB and its relevancy to exploring the intention to transfer teamwork skills, propose a TPB-based model that explains the effects of different determinants on intention to transfer, and present several hypotheses derived from the model. After briefly presenting the relevant research methods, I conclude with a discussion of expected results and their potential implications for future research and practice.

THE THEORY OF PLANNED BEHAVIOR The theory of planned behavior (TPB) is designed “to predict and explain human behavior in specific contexts” (Ajzen, 1991, p. 181). The TPB posits that an individual’s behavior is driven by his or her behavioral intentions. Such intentions are determined by three conceptually independent components: the individual’s attitude toward the behavior, the subjective norm surrounding the performance of the behavior, and the degree of individual’s perceived behavioral control (Ajzen, 1991). One determinant represents personal aspects (attitude toward the behavior); one reflects social pressure (subjective norms); and another refers to issues of control (behavioral control) (Ajzen, 2005). Though individuals can have many beliefs about a certain behavior, only the salient beliefs become the prevailing determinants of their intentions and actual behavior (Doll and Ajzen, 1992). These salient beliefs cognitively affect individuals’ attitudes, subjective norms; and perceptions of behavioral control and later their behavioral intentions are predicted based on their beliefs (Ajzen, 2005). A schematic representation of the theory is displayed in Figure 1. Attitude toward a given behavior is determined by a person’s behavioral beliefs (accessible beliefs about outcomes related to that behavior and the evaluation of these outcomes) (Ajzen, 2005). “The evaluation of each salient outcome contributes to the attitude in direct proportion to the person’s strength of belief that the behavior will produce the outcome in question” (Ajzen, 2005, p. 123). The equation below describes the relation between attitude toward the behavior; and behavioral beliefs in symbolic form. Here AB is the attitude toward behavior B, bi is the behavioral belief that performing behavior B will produce outcome i; ei is the evaluation of outcome i; and the sum is the number of accessible behavioral beliefs (Ajzen, 2005).

Understanding MBA Students’ Intention to Transfer to Teamwork Skills

Figure 1.  Theory of planned behavior (Ajzen, 2005)

AB ∝ ∑biei Subjective norms reflect an individual’s normative beliefs (accessible beliefs about the expectations of important referents and motivation to comply with such expectations) (Ajzen, 2005). The equation below shows the relation between subjective norms and normative beliefs. Here SN is the subjective norm; ni is the normative belief about referent i; mi is the person’s motivation to comply with referent i; and the sum is over the number of accessible normative beliefs (Ajzen, 2005). SN ∝ ∑nimi The perceived behavioral control is a function of an individual’s control beliefs (accessible beliefs about the presence or absence of factors that facilitate or impede performance of a given behavior and the perceived power of these factors) (Ajzen, 2005). The equation below displays the relation between perceived behavioral control and control beliefs. Here, PBC is perceived behavioral control; ci is the control belief that a certain factor i will be available; pi is the power of control factor i to help or hinder performance of the behavior; and the sum is the number of accessible control beliefs (Ajzen, 2005). PBC ∝ ∑cipi Generally speaking, the more favorable the attitude and subjective norms about the target behavior, and the better the perceived behavioral control, the

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stronger an individual’s intention will be to perform the given behavior (Ajzen, 1991). The theory of planned behavior (TPB), a well-supported theoretical framework in social psychology (for meta-analysis, see Albarracín, Johnson, Fishbein, and Muellerleile, 2001; Armitage and Conner, 2001), has been widely applied to predict and understand people’s various intentions and behaviors.

THE RELEVANCY OF TPB TO UNDERSTANDING THE INTENTION TO TRANSFER Transfer of Learning Transfer of learning is often called transfer of training in the training context. Researchers often treat transfer of training and transfer of learning indiscriminatingly (see Blume, Ford, Baldwin, and Huang, 2010; Bunch, 2007; Holton, Bates, and Ruona, 2000; Merriam and Leahy, 2005). Transfer refers to the application of learned knowledge, skills, and attitudes from training back on the job and the retention of such learning for a period of time on the job (Baldwin and Ford, 1988). In this case, transfer of teamwork skills means MBA students’ application of teamwork related knowledge, skills and attitudes to the workplace and the retention of the teamwork related learning for a certain period of time. (Teamwork skills in this article is a broadly defined term encompassing teamwork knowledge, skills, and attitudes.)

TPB in Transfer of Learning In two literature reviews on transfer of learning by Cheng and Hampson (2008) and Gegenfurtner, Veermans, Festner, and Gruber (2009), they proposed using the theory of planned behavior to understand motivational aspects in the transfer process. In their view, the TPB may help reveal the connections between intentions and their determinants in the transfer context, and clarify some variables related to intention to transfer (Cheng and Hampson, 2008) and can provide a good avenue for understanding learners’ intention to transfer, which is instrumental in the transfer process (Gegenfurtner, Veermans et al., 2009). In the context of transfer of learning, some researchers have used the TPB either completely or partially to predict relevant behavioral intentions and relationships: learners’ development behavior (actual behavior change) (McCarthy and Garavan, 2006), the relationship between training motivation and a few measures of training effectiveness (Bell & Ford, 2007), employees’ participation in e-learning (Garavan, Carbery, O’Malley, and O’Donnell, 2010), public

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sector employees’ training participation (Ho, Tsai, and Day, 2011), learners’ transfer intention (Al-Eisa, Furayyan, and Alhemoud, 2009), and learners’ autonomous and controlled motivation to transfer (Gegenfurtner, Festner, Gallenberger, Lehtinen, and Gruber, 2009). The last two studies mentioned above are directly relevant to intention or motivation to transfer. Gegenfurtner, Festner et al. (2009) examined 444 safety inspectors in Germany after their training courses related to occupational health and safety. They used attitudes toward training content (attitude toward the behavior, a construct from the TPB) as one of the three variables to predict behavioral intention (autonomous and controlled motivation to transfer). The results indicated that attitudes were positively correlated with autonomous motivation to transfer, the internalized desire to transfer. Al-Eisa et al. (2009) applied the TPB to explore the effects of self-efficacy, supervisor support, and motivation to learn on transfer intention among 287 public employees in Saudi Arabia who had attended 12 training programs. The findings showed that supervisor support and motivation to learn exerted more influence on transfer intention whereas self-efficacy’s influence on transfer intention was limited. These two studies further indicate that the TPB has shown its relevancy in exploring learners’ behavioral intentions such as intention to transfer learning by focusing on key individual and environmental determinants.

Intention to Transfer In the TPB, intentions “are indications of how hard people are willing to try, of how much of an effort they are planning to exert, in order to perform the behavior” (Ajzen, 1991, p. 181). The intention here is about MBA students’ desire and willingness to transfer the teamwork skills learned or enhanced from their MBA program to the workplace. In transfer of learning, direct research on intention to transfer is sparse. However, motivation to transfer, a closely related construct, has attracted some attention. Motivation to transfer refers to “the trainees’ desire to use the knowledge and skills mastered in the training program on the job” (Noe, 1986, p. 743) and emphasizes “the intended effort” of the trainees to apply the skills and knowledge (Seyler, Holton, Bates, Burnett, and Carvalho, 1998). Individuals with motivation to transfer are more likely to make intentional transfer when an opportunity arises (Pugh and Bergin, 2006). As “intentions are assumed to capture the motivational factors that influence a behavior” (Ajzen, 1991, p. 181), a trainee’s intention to transfer can be perceived as “an endpoint of the motivational process that encompasses his or her motivation to transfer” (Al-Eisa et al.,

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2009, p. 1225). Thus, despite their differences, both constructs can be affected by the same individual and contextual factors (Al-Eisa et al., 2009). In this context, because the focus is on MBA students’ desire and willingness to apply teamwork skills to the workplace, intention to transfer and motivation to transfer have some degree of conceptual overlap and can mean very similar things.

Intention to Transfer Teamwork Skills and the TPB-Based Model With its emphasis on personal beliefs and attitudes, perceived workplace norm, and issues of behavioral control, the TPB seems particularly appropriate for studying the determinants that influence MBA students’ intention to transfer teamwork skills to the workplace. In this instance, the TPB-based model comprises these components: intention to transfer teamwork skills, attitude toward transferring teamwork skills, subjective norm of transferring teamwork skills, and perceived behavioral control of transferring teamwork skills. The three determinants of intention are underpinned by behavioral beliefs, normative beliefs, and control beliefs, respectively. Compared with hard skills, “‘soft’ skills do not transfer as readily” (Olsen, 1998, p. 70) and learners normally have more resistance to acquire and transfer soft skills back to the workplace (Laker and Powell, 2011). Hence, as an extension of the TPB, variable motivation to learn teamwork skills, an important learner’s characteristics, is added to the model, along with several relevant background variables. Figure 2 presents the proposed model.

Figure 2.  A TPB-based model to understand intention to transfer teamwork skills

Understanding MBA Students’ Intention to Transfer to Teamwork Skills

HYPOTHESES DERIVED FROM THE MODEL The model as shown in Figure 2 allows us to test various hypotheses in the context of transferring teamwork skills. Testing these hypotheses could both expand our understanding of MBA students’ intention to transfer teamwork skills and help MBA program leaders, instructors, or corporate trainers design effective teamwork skills training programs.

Attitudes toward Transferring Teamwork Skills and Intention to Transfer The behavior under consideration here is to transfer (apply) teamwork skills learned or enhanced from the MBA program to the workplace. In the TPB, MBA students’ attitudes toward transferring teamwork skills to the workplace consist of their beliefs about the potential outcomes of teamwork skills development and their perceived evaluation of the outcomes. Teamwork skills are open skills (soft skills). Such skills emphasize the adaptation to various circumstances based on general principles (Yelon and Ford, 1999). Due to the intangible nature of teamwork skills, MBA students who question the utility of teamwork skills training through the program probably could form a salient negative belief about such training. On the other hand, some MBA students who believe the usefulness of teamwork skills training through the program would develop a positive belief about such training. Both beliefs, the positive as well as the negative, could contribute to the overall attitude toward transferring teamwork skills. According to literature review on training transfer compiled by Burke and Hutchins (2007), trainees’ perceived utility or value of the training can influence the transfer. A meta-analysis of relations among training criteria by Alliger, Tannenbaum, Bennett, Traver, and Shotland (1997) has also noted that trainees’ utility reaction correlates with training transfer. This leads to hypothesis 1. Hypothesis 1. MBA students who believe in utility of teamwork skills training and development in the MBA program will show a stronger intention to transfer teamwork skills to the workplace than will those with negative beliefs about the utility of such training and development.

In transfer of learning, attitude toward training or attitude toward specific training content can affect the motivation to transfer learning to the job setting (Gegenfurtner, Veermans et al., 2009). Some researchers stated, “the

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more behaviorally specific attitudes are, the more likely that they are predict behavior” (Alliger et al., 1997, p. 352). Teamwork may not be embraced by all MBA students. Some researchers have noted that certain MBA students hold a negative attitude toward the topic of teamwork and view teamwork as only a workplace slogan even though they recognize the benefits of teamwork theoretically (see Dean, Brandes, and Dharwadkar, 1998). MBA students who have a negative belief about teamwork skills development and its future benefits and rewards would be more likely to form a negative attitude toward transferring teamwork skills. Vice versa, MBA students who have a positive belief about teamwork skills development and its future benefits and rewards would be more likely to develop a positive attitude toward transferring teamwork skills. In the TPB, MBA students’ attitude toward transferring teamwork skills can predict their intention to transfer. Hypothesis 2. MBA students who believe teamwork skills training and development can produce long-term benefits and rewarding experience will show a stronger intention to transfer teamwork skills to the workplace than will those who do not believe such benefits.

Subjective Norms of Transferring Teamwork Skills and Intention to Transfer Transferring teamwork skills, a behavior without complete volitional control, is not a solo act. To transfer teamwork skills to the workplace, individuals need to interact with the management (often their immediate supervisor) and peers at work. In TPB, the subjective norms of transferring teamwork skills are directly related to MBA students’ two specific referents: supervisors and peers in the workplace. The extent that these referents’ support for teamwork can affect MBA students’ normative beliefs about transferring teamwork skills and their motivation to comply with the referents. According to a meta-analytic review of the transfer literature by Blume et al. (2010), transfer climate is one of the critical elements of work environment for predicting transfer of training. Another literature review on key factors for the transfer of training by Grossman and Salas (2011) has indicated that both supervisor and peer support can saliently affect transfer climate and ultimately the transfer. One study found that the opportunity to use the trained skills was perceived as the highest form of support for learners, whereas the lack of opportunity to apply the trained skills was considered the biggest hurdle to transfer (Lim and Johnson, 2002). As summarized well in a literature review on motivation

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to transfer by Gegenfurtner et al. (2009), organizational normative context can exert either a positive or negative influence on motivation to transfer. This leads to hypotheses 3 and 4. Hypothesis 3: MBA students who believe that their immediate supervisor supports teamwork will show a stronger intention to transfer teamwork skills to the workplace than will those who do not perceive supervisor support. Hypothesis 4: MBA students who believe that their coworkers support teamwork will show a stronger intention to transfer teamwork skills to the workplace than will those who do not perceive coworker support.

Perceived Control to Transfer Teamwork Skills and Intention to Transfer Theoretically, the perceived behavioral control draws insights from Bandura’s concept of perceived self-efficacy (Ajzen, 2002). Bandura (1986) defined perceived self-efficacy as “people’s judgments of their capabilities to organize and execute courses of action required to attain designated types of performances” and perceived self-efficacy was “a significant determinant of performance that operates partially independently of underlying skills” (p. 391). Moreover, the perceived behavioral, as a proxy for actual control, can directly contributes to the predication of behavior (Ajzen, 1991). In transfer of learning, studies have shown that learners with higher selfefficacy are more likely to transfer what they have learned to their job (see Ford, Weissbein, Smith, and Gully, 1998; Seyler et al., 1998). A meta-analysis of the literature on training motivation, its antecedents, and its relationships with training outcomes has revealed that post-training self-efficacy can predict transfer implementation intentions (see Colquitt, LePine, and Noe, 2000). Moreover, prior research has indicated that self-efficacy can impact learners’ intention to transfer soft skills. One study noticed that after the diversity training, trainees’ self-efficacy increased and their self-efficacy was positively related to intention to become involved in diversity-related activities, a sign of intention to transfer (see Combs and Luthans, 2007). Another study found that undergraduate business students’ team conflict self-efficacy positively affected behavioral intention to use team skills (see Stone and Bailey, 2007). The perceived behavior control here refers to MBA students’ perceived competence to transfer teamwork skills to the workplace and the perceived power of control factors to facilitate or impede such transfer. MBA students are

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not likely to transfer teamwork skills if they do not believe that they have the abilities or opportunities to do so even if they have a positive attitude toward transferring teamwork skills. In contrast, MBA students are more likely to transfer teamwork skills if they believe that they have the abilities to transfer teamwork skills with ease and can have opportunities to do so. This leads to hypotheses 5 and 6. Hypothesis 5: MBA students who have a high perceived self-efficacy for transferring teamwork skills will show a stronger intention to transfer teamwork skills to the workplace than will those with a low perceived self-efficacy for transferring teamwork skills. Hypothesis 6: MBA students who have a high sense of controllability over transferring teamwork skills will show a stronger intention to transfer teamwork skills to the workplace than will those with a low sense of controllability.

Motivation to Learn Teamwork Skills and Intention to Transfer Literature reviews (see Gegenfurtner et al., 2009; Merriam and Leahy, 2005) show that motivation to learn is an important factor that affects the outcome of transfer of training. Motivation to learn is defined as a specific desire of a trainee to learn the content of the training program (Noe, 1986) and to fully embrace the training experience (Carlson, Bozeman, Kacmar, Wright, and McMahan, 2000). In this case, motivation to learn teamwork skills is very important because teamwork skills are not as tangible as hard skills. According to Laker and Powell (2011), with soft skills training, trainees tend to be adversely influenced by multiple factors such as prior learning and experience, their own resistance, less precise identification of training needs and objectives, less immediate and visible feedback and consequences, less similarity between training and work, and work settings; trainees tend to feel that they have the relevant expertise and would not admit the need to be trained in soft skills willingly. Laker and Powell (2011) have thus argued that soft skills training transfer is more difficult than hard skills transfer. As soft skills, teamwork skills cannot be mechanically replicated but require the application of related principles and knowledge to different situations. Unlike replication of a skill, generalization of a skill to a new situation needs different cognitive processes and motivation to learn affects both learning

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and intention to transfer (Foxon, 1993). Given the learner resistance to acquiring soft skills, motivation to learn teamwork skills can exert an important effect on intention to transfer teamwork skills. Motivation to learn here implies that MBA students embrace all teamwork training and development activities in the MBA program and make efforts to learn and improve their teamwork skills. This leads to hypothesis 7. Hypothesis 7: MBA students who have a high motivation to learn teamwork skills will show a stronger intention to transfer teamwork skills to the workplace than will those with a low motivation to learn teamwork skills.

Background Factors and Intention to Transfer In TPB, various background factors may exert some influence on behavioral intentions and their effects on intentions are often through their impact on the proximal determinants of intentions (Ajzen, 2005). Since transfer is a conscious personal choice (Baldwin, Ford, and Blume, 2009), individual differences may have some impact on intention to transfer teamwork skills to some extent. There are some relationships between certain Big Five personality variables and training-related aspects of motivation (Naquin and Holton, 2002; Rowold, 2007). In the management realm, a meta-analysis that examined the correlations between the Big Five personality dimensions and performance in jobs involving interpersonal interactions found that agreeableness and emotional stability were valid predictors for jobs involving teamwork (see Mount, Barrick, and Stewart, 1998). Though not definitive, some research has indicated that certain demographic attributes may potentially influence MBA students’ reaction to teamwork. For instance, students’ age might affect their attitude toward teamwork (Thompson, Anitsal, and Barrett, 2008); gender showed some differences in attitude toward teamwork (Karakowsky and Miller, 2002) and female students learned more from team projects than male students (Bacon, 2005); racial and cultural background might subtly affect students’ attitude toward cooperation (Tang, 1999) and team performance (Sosik and Jung, 2002); academically more talented students were less favorable toward teamwork than their less talented peers (Baldwin, Bedell, and Johnson, 1997) and students’ GPA showed some weak but statistically significant negative correlation with their attitude toward working in a group (Chapman and van Auken, 2001). Hence, these background factors are included in the model and their potential indirect influence on intention to transfer are explored (Figure 2).

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RESEARCH METHODS A brief overview of the research methods related to the application of this TPB-based model is presented below (for practical TPB research examples, see Davis, Ajzen, Saunders, and Williams, 2002; Harrison, 1995).

Population of Interest This study can use a cross-sectional survey design. Sample can be drawn from MBA students in a business school with a curriculum that cultivates teamwork skills and encourages teamwork throughout the whole MBA program. Since the subjective norm here concerns the workplace, part-time MBA students who are working would be the target population. It is also preferable to survey these MBA students toward the end of the program or right after they finish the program.

Instrumentation The survey items can be developed following the specific TPB questionnaire construction guidelines and examples provided by Ajzen (2006b). The three main predictors in the TPB (attitude, subjective norm, and perceived behavioral control) are often assessed both directly and indirectly (Ajzen, 2005).

Formulating direct measures For practical purposes, direct measures of attitudes, subjective norms, and perceived behavioral control are used to assess global evaluations of people’s intentions and behaviors and the relative importance of these factors (Ajzen, 2005). As suggested by Ajzen (2006b), five to six 7-point bipolar adjective items are developed to directly assess each of the major TPB constructs in the model: attitude, subjective norm, perceived behavioral control, and intention with respect to transferring teamwork skills to the workplace. Respondents would report their personal opinions on these items directly. A pilot questionnaire containing these items for direct measures is needed and the internal consistency of each construct is tested.

Eliciting salient beliefs To gain a more comprehensive understanding of people’s intentions and actions, it is necessary to explore the antecedents of attitudes, subjective norms, and

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perceived behavioral control (Ajzen, 2005). These antecedents are behavioral beliefs, normative beliefs, and control beliefs, which can be indirectly assessed. Based on Ajzen’s (2006b) instructions, a small sample of members (a focus group) from a target population (in this case, part-time MBA students) are used to elicit salient beliefs. The elicitation is conducted by asking respondents to answer open-ended questions linking to their behavioral, normative, and control beliefs about transferring teamwork skills to the workplace. For behavioral beliefs, respondents are asked to list the benefits (or costs) resulting from transferring teamwork skills. In terms of normative beliefs, respondents are asked to indicate the extent to which they believe that their normative referents (supervisors, coworkers) would encourage them to transfer teamwork skills to the workplace. Transferring teamwork skills requires a teamwork environment. In this context, it is the perception of MBA students’ normative referents in encouraging them to engage in teamwork at work. Regarding control beliefs, respondents are asked to list factors or circumstances that would facilitate or inhabit their transfer teamwork skills to the workplace. All these questions are included in the pilot questionnaire. It is expected that some salient beliefs elicited might have overlap with the beliefs in the hypotheses suggested by the model. Through a content analysis of the responses, researchers can identify lists of salient behavioral outcomes, normative referents, and control factors about transferring teamwork skills to the workplace and develop relevant items to be used in the final questionnaire.

Motivation to learn teamwork skills Items measuring motivation to learn used in Noe and Schmitt (1986) and other motivation to learn scales might be adapted to the purpose of this study by specifying teamwork skills as the learning content. The items assessing motivation to learn teamwork skills are included in the pilot questionnaire.

Other measures The pilot questionnaire also includes the following background variables: agreeableness, emotional stability, age, gender, racial and cultural background, and GPA.

Final questionnaire The final questionnaire contains items for direct measures selected for their reliability, and internal consistency within each construct in the proposed model.

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Using the data generated from the pilot questionnaire, researchers can identify the salient behavioral outcomes, the important referent others and control factors. Again Ajzen’s (2006b) instructions on developing TPB questionnaire are applied here. For each salient behavioral outcome, items are developed to measure the strength of the behavioral belief and the evaluation of the outcome. For each salient normative referent, items are developed to measure the strength of the normative belief and the motivation to comply with or the identification with the referent individual or group. For each salient control factor, items are developed to measure the strength of the control belief and the power of control factor to help or hinder their performing a given behavior. The final questionnaire includes both items for direct measures, items derived from salient beliefs elicited, items to measure motivation to learn teamwork skills, and several individual background variables.

Data Analysis Multiple regression analysis is broadly applicable to test hypotheses that are both theory-driven and non-theory-driven (Cohen, Cohen, West, and Aiken, 2003). Researches can use multiple regression analysis to test the hypotheses derived from the model. Researchers can use hierarchical regression analysis to test the predictive validity of the model. In step one, the three TPB determinants (attitude, subjective norm, perceived behavioral control) form the first set of predictors in the model. In step two, motivation to learn teamwork skills is added to the model to see its impact on intention to transfer. In step three, two personality variables (agreeableness and emotional stability) can be added to the model together or individually. In step four, several demographic variables (namely, age, gender, GPA, racial and cultural background) can be added to the model, respectively. The relative importance of attitude toward behavior, subjective norm, and perceived behavioral control in predicting intention tends to vary with different behaviors and in different situations (Ajzen, 1991). Hence, the relative importance of the three TPB determinants in the model is examined for the relative contribution of each determinant in impacting intention to transfer teamwork skills. Ideally, both direct measures and indirect measures of attitude, subjective norm, and perceived behavioral control are used in the analysis. Direct measures of assessing individuals’ global attitude, subjective norm, and perceived behavioral control could obtain a general picture of the TPB determinants on intention to transfer. Direct measures are economical and time efficient and

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researchers may consider just using direct measures when they do not have the resources and time. With indirect measures developed from the accessible beliefs, researchers can identify what specific beliefs make up MBA students’ attitudes, subjective norms, and perceived behavioral control concerning their intention to transfer teamwork skills to the workplace. In their meta-analysis of the TPB literature, Armitage and Conner (2001) have noted that direct measures and indirect measures (belief-based measures) tend to correlate well with each other. The sum of behavioral beliefs, normative, and control beliefs can be calculated respectively, using the relevant equation listed earlier. If the sum of each indirect measure correlates with its corresponding direct measure with significance and of high magnitude, the informational foundations for direct measures of attitude, subjective norm, and perceived behavioral control in the model are well supported.

DISCUSSION AND CONCLUSION The proposed model displayed in Figure 2 aims to understand the intention to transfer teamwork skills, applying a robust social-psychological framework, the theory of the planned behavior (TPB). The hypotheses suggested by the model could be tested to expand our understanding of MBA students’ intention to transfer teamwork skills to the workplace. This model is not limited to educational programs but can also be employed to explore corporate trainees’ intention to transfer teamwork skills to the workplace when they complete their teamwork skills training and development programs. This model may contribute to the research on teamwork skills training and development in the following aspects. First, the model identifies important determinants of intention to transfer teamwork skills in the TPB. As specifically noted in a literature review on motivation to transfer training by Gegenfurtner et al. (2009), individual, organizational, and training-related factors can contribute to trainees’ motivation to transfer and precede their transfer of training to the workplace. The attitude, subjective norm and perceived behavioral control in the TPB-based model directly correspond with either the individual or work environment factors that can affect MBA students’ intention to transfer teamwork skills. Second, the model may offer new ground for future investigations. Using salient beliefs in the hypotheses, researchers can detect and confirm specific factors that are instrumental to MBA students’ intention to transfer teamwork skills. These factors might be worth further exploration to see if they can be applied across other teamwork skills training and development settings. Also

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the salient beliefs in the hypotheses are based on the current research. Further investigations such as qualitative interviews may elicit additional salient beliefs. Third, the model targets the intention to transfer teamwork skills (that is, soft skills). Most of the transfer research has centered on hard skills learning and transfer (Merriam & Leahy, 2005) and most theoretical frameworks of training transfer do not differentiate the soft skills and hard skills training (Laker & Powell, 2011). The findings from the application of this model can expand our understanding of soft skills transfer and help with future research on soft skills training design and implementation.

Limitations Even though the proposed model has good potential for future research, it does have some limitations. First, the model focuses only on intention to transfer teamwork skills. Certainly intention is an important cognitive representation of individuals’ willingness to perform a given behavior as indicated in Ajzen’s (1991) theory of planned behavior (TPB), it does not reveal the actual transfer. Sometimes there are intention-behavior discrepancies (Ajzen, 1991). Second, because the model is parsimonious, its explanatory power may be limited. Given that intention to transfer soft skills such as teamwork skills has not been explored extensively in prior research, the model probably needs to be fine-tuned by adding other pertinent variable(s) or testing other relevant hypotheses in future research. Third, the model assumes that the teamwork skills training and development in MBA programs is similar. This assumption ignores the differences existing among various MBA programs in developing and honing students’ teamwork skills. A well-designed teamwork skills development program in MBA curriculum may exert more positive influence on MBA students than does a perfunctory and routine teamwork skills development program in MBA curriculum. Probably, some program design factors need to be considered in the model.

Practical Implications The proposed model provides a theory-based explanation for MBA students’ intention to transfer teamwork skills to the workplace. The knowledge about the relative influence of three TPB determinants on intention to transfer teamwork skills, combined with MBA students’ motivation to learn teamwork skills, will benefit future teamwork skills training and development in MBA programs as well as organizational training programs targeted for teamwork

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skills development. Particularly, this model offers a useful framework to diagnose MBA students’ salient beliefs that might enhance or impede their intention to transfer teamwork skills to the workplace. According to Ajzen (2005), salient beliefs constitute the informational foundation of behavior. The specific beliefs identified from the study might be targeted for behavioral interventions through future teamwork skill training designs and implementation strategies. According to TPB, interventions can be designed to change behavioral intentions and ultimately behaviors through one or more of a behavior’s theoretical components: attitudes, subjective norms, or perceived behavior control (Ajzen, 2005). Based on the survey results, some interventions might be introduced accordingly to enhance the individuals’ intention to transfer teamwork skills. TPB-based interventions can be designed to help MBA students or other trainees develop a more positive attitude toward transferring teamwork skills. For instance, if the survey results indicated that MBA students did not believe the utility or benefits of the teamwork skills training and development in their program, that MBA program may need to develop intervention strategies for future students. In transfer of training, pretraining interventions—framing a training program can affect transfer motivation (Gegenfurtner et al., 2009). Thus, a persuasive framing on the utility, necessity, and benefits of teamwork skills training and development prior to the MBA program is essential. For instance, it may make sense to put student testimonials about their positive experience in developing teamwork skills on the program website, invite program graduates to share their thoughts about the necessity of enhancing teamwork skills, and distribute articles about the importance of teamwork at the workplace. When individuals form more positive beliefs about their teamwork skills training and development in the program, their salient beliefs can determine their attitude toward transferring teamwork skills, which can impact their intention to transfer and actual transfer. Such interventions might also help motivate individuals to learn teamwork skills. Another practical implication may concern the subjective norms of transferring teamwork skills. If the survey results revealed that MBA students did not believe that their supervisor and coworkers showed genuine support for teamwork in their workplace, their intention to transfer teamwork skills could be discouraged to some extent. In the case of MBA programs, it is not operationally feasible to design interventions to target subjective norms as students are from different organizations. But in workplace teamwork training programs, program designers and trainers can apply the TPB-based interventions to

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diminish potential negative subjective norms before the training. For instance, they might reach out to the top management to gain support for promoting a culture of teamwork in the workplace. If the workplace is ready to nurture an encouraging teamwork environment, it offers a helpful normative environment for developing and transferring teamwork skills. Targeted efforts can be made to involve organization leaders in elaborating the importance and benefits of teamwork skills training to the success of the organization, raising awareness of supporting teamwork, and encouraging teamwork skills development at all levels within the organization. Individuals would then feel positive about attending teamwork skills training programs and transferring teamwork skills to the workplace. With open skills (soft skills), the trainees have more options as to “whether, how and when to transfer” (Blume et al., 2010, p. 1073), and probably how much to transfer. Hence, appropriate interventions can probably make a difference. Additionally, according to Ajzen (2005), asking individuals to formulate a specific behavioral plan can increase the efficacy of interventions. In this context, asking MBA students or training participants to form an action plan to transfer teamwork skills could help them carry out their intention to transfer. Practitioners can refer to Ajzen (2006a) for more detailed information about developing TPB-based interventions. In conclusion, teamwork skills training and development is emphasized and integrated into MBA curriculum and extra-curricular activities. The transfer of soft skills such as teamwork skills may not happen automatically. MBA students’ intention to transfer teamwork skills to the workplace is instrumental to the success of such training and development. The TPB offers a robust conceptual framework for understanding MBA students or trainees’ intention to transfer teamwork skills from education programs or training programs to work settings. Potential barriers to transfer may exist before, during and after the learning experience and such barriers can be both individual, and situational (Thomas, 2007). By uncovering the links between intentions and their determinants (attitude, subjective norm, and perceived behavioral control) regarding transferring teamwork skills, the links between these determinants and their antecedents (behavioral beliefs, normative beliefs, and control beliefs), leaders of MBA programs, researchers, and practitioners can identify barriers that would inhibit MBA students or trainees’ intention to transfer teamwork skills and make targeted TPB-based interventions in future programs. The proposed model can potentially benefit researchers and practitioners in the area of teamwork skills training and development as well as other soft skills development and transfer.

Understanding MBA Students’ Intention to Transfer to Teamwork Skills

REFERENCES Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (eds.), Action Control: From cognition to behavior, 11–39. New York: Springer. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2), 179–211. DOI:10.1016/0749-5978(91)90020-T. Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32 (4), 665–683. DOI:10.1111/ j.1559-1816.2002.tb00236.x. Ajzen, I. (2005). Attitudes, personality and behavior. Maidenhead, UK: Open University Press. Ajzen, I. (2006a). Behavioral interventions based on the theory of planned behavior. Retrieved March 23, 2011, from https://people.umass.edu/~aizen/pdf/tpb.intervention.pdf. Ajzen, I. (2006b). Constructing a theory of planned behavior questionnaire. Retrieved March 23, 2011, from http://people.umass.edu/~aizen/pdf/tpb.measurement.pdf. Al-Eisa, A. S., Furayyan, M. A., and Alhemoud, A. M. (2009). An empirical examination of the effects of self-efficacy, supervisor support and motivation to learn on transfer intention. Management Decision, 47 (8), 1221–1244. DOI:10.1108/00251740910984514. Albarracín, D., Johnson, B. T., Fishbein, M., and Muellerleile, P. A. (2001). Theories of reasoned action and planned behavior as models of condom use: A meta-analysis. Psychological Bulletin, 127 (1), 142–161. DOI:10.1037/0033-2909.127.1.142. Alliger, G. M., Tannenbaum, S. I., Bennett, W. Jr., Traver, H., and Shotland, A. (1997). A metaanalysis of the relations among training criteria. Personnel Psychology, 50 (2), 341–358. DOI:10.1111/j.1744-6570.1997.tb00911.x. Armitage, C. J., and Conner, M. (2001). Efficacy of the theory of planned behaviour: A metaanalytic review. The British Journal of Social Psychology, 40, 471–499. DOI:10.1348/ 014466601164939. Bacon, D. R. (2005). The effect of group projects on content-related learning. Journal of Management Education, 29 (2), 248–267. DOI:10.1177/105256299902300503. Baldwin, T. T., Bedell, M. D., and Johnson, J. L. (1997). The social fabric of a team-based M.B.A. program: Network effects on student satisfaction and performance. Academy of Management Journal, 40 (6), 1369–1397. DOI:10.2307/257037. Baldwin, T. T., and Ford, J. K. (1988). Transfer of training: A review and directions for future research. Personnel Psychology, 41 (1), 63–105. DOI:10.1111/j.1744-6570.1988.tb00632.x. Baldwin, T. T., Ford, J. K., and Blume, B. D. (2009). Transfer of training 1988–2008: An updated review and new agenda for future research. In G. P. Hodgkinson & J. K. Ford (eds.), International review of industrial and organizational psychology, volume 24, 41–70. Chichester, UK: Wiley. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall. Bell, B. S., and Ford, J. K. (2007). Reactions to skill assessment: The forgotten factor in explaining motivation to learn. Human Resource Development Quarterly, 18 (1), 33–62. doi:10.1002/ hrdq.1191.

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Chunhui Ma Bloomberg (2015). The Bloomberg recruiter report: Job skills companies want but can’t get. Retrieved from https://www.bloomberg.com/graphics/2015-job-skills-report/. Blume, B. D., Ford, J. K., Baldwin, T. T., and Huang, J. L. (2010). Transfer of training: A meta-analytic review. Journal of Management, 36 (4), 1065–1105. DOI:10.1177/01492063093 52880. Bunch, K. J. (2007). Training failure as a consequence of organizational culture. Human Resource Development Review, 6 (2), 142–163. DOI:10.1177/ 1534484307299273. Burke, L. A., and Hutchins, H. M. (2007). Training transfer: An integrative literature review. Human Resource Development Review, 6 (3), 263–296. DOI:10.1177/1534484307303035 Carlson, D. S., Bozeman, D. P., Kacmar, K. M., Wright, P. M., and McMahan, G. C. (2000). Training motivation in organizations: An analysis of individual-level antecedents. Journal of Managerial Issues, 12 (3), 271–287. Chapman, K. J., and van Auken, S. (2001). Creating positive group project experiences: An examination of the role of the instructor on students’ perceptions of group projects. Journal of Marketing Education, 23 (2), 117–127. DOI:10.1177/0273475301232005. Cheng, E. W. L., and Hampson, I. (2008). Transfer of training: A review and new insights. International Journal of Management Reviews, 10 (4), 327–341. DOI:10.1111/j.14682370.2007.00230.x. Cohen, J., Cohen, P., West, S. G., and Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Erlbaum. Colquitt, J. A., LePine, J. A., and Noe, R. A. (2000). Toward an Integrative Theory of Training Motivation: A Meta-Analytic Path Analysis of 20 Years of Research. Journal of Applied Psychology, 85 (5), 678–707. DOI:10.1037//0021-9010.85.5.678. Combs, G. M., & Luthans, F. (2007). Diversity training: Analysis of the impact of self-efficacy. Human Resource Development Quarterly, 18 (1), 91–120. DOI:10.1002/hrdq.1193. Davis, L. E., Ajzen, I., Saunders, J., and Williams, T. (2002). The decision of African American students to complete high school: An application of the theory of planned behavior. Journal of Educational Psychology, 94 (4), 810–819. DOI:10.1037/0022-0663.94.4.810. Dean, J. W., Jr., Brandes, P., and Dharwadkar, R. (1998). Organizational cynicism. Academy of Management Review, 23 (2), 341–352. DOI:10.5465/AMR.1998.533230. Doll, J. R., and Ajzen, I. (1992). Accessibility and stability of predictors in the theory of planned behavior. Journal of Personality and Social Psychology, 63 (5), 754–765. DOI:10.1037/00223514.63.5.754. Ford, J. K., Weissbein, D. A., Smith, E. M., and Gully, S. M. (1998). Relationships of goal orientation, metacognitive activity, and practice strategies with learning outcomes and transfer. Journal of Applied Psychology, 83 (2), 218–233. DOI:10.1037/0021-9010.83.2. 218.  Foxon, M. (1993). A process approach to the transfer of learning. Australian Journal of Educational Technology, 9 (2), 130–143. DOI:10.14742/ajet.2080. Garavan, T. N., Carbery, R., O’Malley, G., and O’Donnell, D. (2010). Understanding participation in e-learning in organizations: a large-scale empirical study of employees. International Journal of Training & Development, 14 (3), 155–168. DOI:10.1111/j.1468-2419.2010.00 349.x.

Understanding MBA Students’ Intention to Transfer to Teamwork Skills Gegenfurtner, A., Festner, D., Gallenberger, W., Lehtinen, E., and Gruber, H. (2009). Predicting autonomous and controlled motivation to transfer training. International Journal of Training & Development, 13 (2), 124–138. DOI:10.1111/j.1468-2419.2009.00322.x. Gegenfurtner, A., Veermans, K., Festner, D., and Gruber, H. (2009). Motivation to transfer training: An integrative literature review. Human Resource Development Review, 8 (3), 403–423. DOI:10.1177/1534484309335970. GMAC (2016). Corporate recruiters survey report. Retrieved from https://www.gmac.com/ market-intelligence-and-research/research-library/employment-outlook/2016-corporaterecruiters-survey-report.aspx. Grossman, R., and Salas, E. (2011). The transfer of training: What really matters. International Journal of Training & Development, 15 (2), 103–120. DOI:10.1111/j.1468-2419.2011. 00373.x. Harrison, D. A. (1995). Volunteer motivation and attendance decisions: Competitive theory testing in multiple samples from a homeless shelter. Journal of Applied Psychology, 80 (3), 371–385. DOI:10.1037/0021-9010.80.3.371. Ho, Y.-Y., Tsai, H.-T., and Day, J.-D. (2011). Using the theory of planned behaviour to predict public sector training participation. Service Industries Journal, 31 (5), 771–790. DOI:10. 1080/02642060902960776. Holton, E. F., III, Bates, R. A., and Ruona, W. E. A. (2000). Development of a generalized learning transfer system inventory. Human Resource Development Quarterly, 11 (4), 333–360. DOI:10.1002/1532-1096(200024)11:43.0.CO;2-P. Karakowsky, L., and Miller, D. (2002). Teams that listen and teams that do not: Exploring the role of gender in group responsiveness to negative feedback. Team Performance Management, 8 (7/8), 146–156. DOI:10.1108/13527590210452086. Laker, D. R., and Powell, J. L. (2011). The differences between hard and soft skills and their relative impact on training transfer. Human Resource Development Quarterly, 22 (1), 111–122. doi:10.1002/hrdq.20063. Lim, D. H., and Johnson, S. D. (2002). Trainee perceptions of factors that influence learning transfer. International Journal of Training & Development, 6 (1), 36–48. doi:10.1111/146 8-2419.00148. Mazany, P., Francis, S., and Sumich, P. (1995). Evaluating the effectiveness of an outdoor workshop for team building in an MBA programme. Journal of Management Development, 14 (3), 50–68. doi:10.1108/02621719510078966. McCarthy, A., and Garavan, T. (2006). Postfeedback development perceptions: Applying the theory of planned behavior. Human Resource Development Quarterly, 17 (3), 245–267. doi:10.1002/hrdq.1173. Merriam, S. B., and Leahy, B. (2005). Learning transfer: A review of the research in adult education and training. PAACE Journal of Lifelong Learning, 14, 1–24. Retrieved from http:// www.iup.edu/assets/0/347/349/4951/4977/10267/F66B135A-DB09-4BA0-8D2090D751AF39B6.pdf. Mount, M. K., Barrick, M. R., and Stewart, G. L. (1998). Five-factor model of personality and performance in jobs involving interpersonal interactions. Human Performance, 11 (2/3), 145–165. DOI:10.1080/08959285.1998.9668029.

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Chunhui Ma Naquin, S., and Holton, E. F., III. (2002). The effects of personality, affectivity, and work commitment on motivation to improve work through learning. Human Resource Development Quarterly, 13 (4), 357–376. DOI:10.1002/hrdq.1038. Navarro, P. (2008). The MBA core curricula of top-ranked U.S. business schools: A study in failure? Academy of Management Learning & Education, 7 (1), 108–123. DOI:10.5465/ AMLE.2008.31413868. Noe, R. (1986). Trainees’ attributes and attitudes: Neglected influences on training effectiveness. Academy of Management Review, 11 (4), 736–749. doi:10.5465/AMR.1986.4283922. Noe, R., and Schmitt, N. (1986). The influence of trainee attitudes on training effectiveness: Test of a model. Personnel Psychology, 39 (3), 497–523. DOI:10.1111/j.1744-6570.1986.tb009 50.x. Olsen, J. H., Jr. (1998). The evaluation and enhancement of training transfer. International Journal of Training and Development, 2 (1), 61–75. DOI:10.1111/1468-2419.00035. Pugh, K. J., and Bergin, D. A. (2006). Motivational influences on transfer. Educational Psychologist, 41 (3), 147–160. DOI:10.1207/s15326985ep4103_2. Rowold, J. (2007). The impact of personality on training-related aspects of motivation: Test of a longitudinal model. Human Resource Development Quarterly, 18 (1), 9–31. DOI:10.1002/ hrdq.1190. Seyler, D. L., Holton, E. F., III, Bates, R. A., Burnett, M. F., and Carvalho, M. A. (1998). Factors affecting motivation to transfer training. International Journal of Training & Development, 2 (1), 2–16. DOI:10.1111/1468-2419.00031 Shivers-Blackwell, S. (2004). Reactions to outdoor teambuilding initiatives in MBA education. Journal of Management Development, 23 (7), 614–630. DOI:10.1108/02621710410546 632. Sosik, J. J., and Jung, D. I. (2002). Work-group characteristics and performance in collectivistic and individualistic cultures. Journal of Social Psychology, 142 (1), 5–23. DOI:10.1080/ 00224540209603881. Stone, R. W., and Bailey, J. J. (2007). Team conflict self-efficacy and outcome expectancy of business students. Journal of Education for Business, 82 (5), 258–266. Retrieved from https://ezproxy. library.nyu.edu/login?url=http://ezproxy.library.nyu.edu:2128/docview/202822228?accountid=12768. Tang, S. (1999). Cooperation or competition: A comparison of U.S. and Chinese college students. The Journal of Psychology, 133 (4), 413–423. DOI:10.1080/00223989909599752. Thomas, E. (2007). Thoughtful planning fosters learning transfer. Adult Learning, 18 (3/4), 4–8. Retrieved from http://search.ebscohost.com/login.aspx? direct=true&db =a9h&AN= 37376672&site=ehost-live. Thompson, D., Anitsal, I., and Barrett, H. (2008). Attitudes toward teamwork in higher education: A comparative study of religiously affiliated universities and secular-based universities. Paper presented at the Allied Academies International Conference, Academy of Educational Leadership. Tonn, J. C., and Milledge, V. (2002). Team building in an MBA “gateway” course: Lessons learned. Journal of Management Education, 26 (4), 415–428. DOI: 10.1177/10525629020 2600407. Yelon, S. L., and Ford, J. K. (1999). Pursuing a multidimensional view of transfer. Performance Improvement Quarterly, 12(3), 58–78. doi:10.1111/j.1937-8327.1999.tb00138.x

CHAPTER 13

Learning: The Experiences of Adults Who Work Full-time While Attending Graduate School Part-time1 BRIDGET N. O’CONNOR, PhD New York University ROBERT CORDOVA, MA New York University and Rob Cordova Consulting, LLC

ABSTRACT

T

he experiences of students who are working full-time and going to graduate school part-time were the focus of this investigation. The literature cited comes from the learning and development literature. Taking a phenomenological approach, we interviewed six individuals who had recently completed either an MA in Business Education or an Advanced Certificate in Workplace Learning to explore their experiences as part-time students. Analysis of interview data

1

This chapter was developed from a paper presented at the American Education Research Association, San Diego, California, April 2009. We thank the Delta Pi Epsilon Research Foundation for their financial support of this research.

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showed that these individuals, who reported high job involvement and strong career planning, were often stymied when they attempted to apply new ideas to the workplace. Those with strong social/family support reported less stress than those who did not. They preferred learning experiences in which that were active learners and had some control. Data from this exploratory study provide a clear distinction between the role of corporate education and its (usually) focused rationale for planned learning experiences and the role of academia in providing an outlet that provides learners more opportunities to explore what it means to be themselves—in an environment where risk is limited and opportunities to be themselves flourish.

INTRODUCTION Working adult students who return to the university part-time for advanced professional degrees come with the expectations that what they learn will enhance their knowledge of their field, the practices they see at their workplace, and their own self-understanding in relation to society and the work they have chosen to do. Sometimes, they return because they must have a credential or degree to retain their current job or obtain the job they want. However, even with this external motivation, they are also intrinsically motivated to learn. The definition of learning is evolving as we come to better understand what learning is and what learning means to individuals. Mackeracker’s (2004) definition was that learning is “a process of making sense of life’s experiences…. making choices and decisions as a means of obtaining feedback to confirm or disconfirm meanings and choices,” (p. 8). Illeris (2004) said learning is a result of the tension among cognitive, emotional, and societal processes. Jarvis (2006) suggested that learning is …the combination of processes whereby the whole person—body (genetic, physical and biological) and mind (knowledge, skills, attitudes, values, emotions, beliefs and senses): experiences a social situation, the perceived content of which is then transformed cognitively, emotively or practically (or through any combination) and integrated into the person’s individual biography resulting in a changed (or more experienced) person [p. 13].

What these definitions have in common is the focus on the individual and the understanding that adults’ choices and perceptions of the value of learning and their resultant transformation of experiences is the ultimate predictor of whether or not learning happens.

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Our purpose here was to describe the learning experiences of adult parttime masters students, who are rarely the focus of research. It is anticipated that an understanding of their experiences could be a contribution to the literature, providing an example of a novel approach to not only describing what happened, but also the perceived value of a graduate degree. Findings could inform classroom practices and, at the same time, provide a richer understanding of the personal lives and work environments that impact learning and the transfer of learning to the workplace of these part-time adult students. Individuals and their workplace managers, who often pay tuition for graduate school, may be interested in the results of this study as well as university program evaluators.

RELATED LITERATURE A literature review helped us identify variables related to adult and workplace learning. Not all experiences are learning experiences, yet those that are touted as instruction are clearly focused toward learning but do not always get their intended results (O’Connor, Bronner, and Delaney, 2007). We have organized variables that help us understand “learning” as those that address the personal needs of the individual (helping the learner “become”) and the job demand needs (helping the organization “become”). These variables are directly related to the academic learning environment, including, but not limited to instructional design and the resultant feedback to curriculum, that provides the academic impetus for “becoming” or changing. A premise here is that where there is synergy among these variables, learning is transferred, which results in “becoming.” Learning is organic; it is not the result of any one input and whether or not learning is demonstrated is a product of the intersection of multiple variables. Of special interest is where the variables overlap—personal relevance as a direct overlap between individual and learning environment characteristics; job involvement as the direct overlap with individual characteristics and the work environment; and content relevance as the overlap between the learning and organizational environments. In other words, when individual characteristics, the classroom learning environment, and the workplace are congruent, it is suggested that change is most apt to occur.

Personal Relevance Guidelines for the transfer of training have been developed in relation to learner characteristics. Cheng and Ho (1998) suggested that locus of control and

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self-efficacy were vital to the transfer of learning from organizational training programs. They also found that individuals with high job involvement and strong career planning were more likely to use what the learned back on their jobs. In another study, it was a “need-to-know” that led to individuals’ quest for applying what was learned to the workplace, as well as a need to learn to persuade others to change (Lim and Johnson, 2002). Adults come to the academic classroom with a wide variety of experiences that impact both their motivation to learn as well as how they prefer to learn. Typically, motivation to learn among adults in higher education is strong. They typically have strong preferences as to how they want to learn, and appreciate those classrooms where the instructor treats them as adults, allowing them opportunities to use/share their experiences in problem analysis or by offering options as to assignments and work group composition (McKeachie and Svinicki, 2006). Many researchers have explained the role of experience by emphasizing the role of reflection in the learning process. When adults reflect on their experiences, they are making meaning of them. Experiences by themselves are not learning opportunities, unless we think about them and evaluate them (Brookfield, 1987). The academic learning environment has been defined as the actual classroom facilities and technology support (Chism, 2002; Mackeracher, 2004), but it also includes the campus itself—for example, its library, cultural, and recreational facilities. Moreover, faculty as well as classmates (McKeachie and Svinicki, 2006) and university support staff contribute to the overall learning experience.

Content Relevance Content relevance means that what is being learned in the classroom has relevancy back at the workplace. The curriculum for the development of professionals must be relevant to those who are learning, and Lindell and Stenstrom (2005) have suggested there is a mutual dependency. Moreover, the effectiveness of a particular instructional technique is related to the content being taught (Alvarez, Salas, and Garofano, 2004; Mathieu, Martineau, and Tannenbaum, 1993). Information technology practitioners who rated their organization as a “learning organization” were motivated to transfer their learning (Egan, Yang, and Bartlett 2004). The most common reason for low transfer has been no direct relationship of learning to jobs, and a lack of understanding of the content (Lim and Johnson, 2002).

Learning: The Experiences of Adults Who Work Full-tim

Job Involvement In one study, individuals with high job involvement and strong career planning were more likely to use what they learned back on their jobs (Cheng and Ho, 1998); in another study of managers, however, the social system at work played a central role in whether or not learning was transferred (Tracey, Tannenbaum, and Kavanagh, 1995). Etienne Wenger suggested that learning is a result of personal ability as well as being able to position yourself within a community. We learn with and from members of our community. Communities, he said, become stale when all they do is bump up against each other (Wenger, 2003). Accepting this premise, it seems that individuals grapple to implement new ideas. The very best learning outcomes may become stale when their implementation bumps up against incompatible management practices.

OVERALL RESEARCH QUESTIONS From the initial question of how these part-time students described their lives while they were working full-time and going to school part-time, we asked questions including: how did these working adults adapt and adopt what they are learning? What impact did they see their education having on their own personal growth as well as their organization’s growth? What classroom experiences either aided or detracted from their learning? For example, how did they handle potential conflicts between what was taught and what was practiced at the workplace? Did their academic experiences help them adapt to new circumstances and result as catalysts for organizational learning? Moreover, did they see their instructors accepting and encouraging their sharing of experiences in class to clarify or negate what is being taught? Sometimes dissonance occurs when what is being learned in the classroom is not connected with organizational work practices or individual values. In other words, what did it mean to be an adult learner—with a personal life and a professional life—studying parttime for an advanced degree?

METHOD Because we wanted to understand the lives of these part-time students from their own perspectives, we used a modified phenomenological approach. Used more frequently in nursing than education, phenomenology helps researchers explore experiences that cannot be captured quantitatively and helps us make

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sense of a “phenomenon,” (Creswell, 1998) described here as the overall experience of working full-time and studying part-time. We opted not to report individual cases because we wanted to capture the overall essence of the experience. Because participants were graduates of a program in which one of us had taught and another had graduated, we worked hard to ensure that we did not impose our own ideas into the interviewees or into data analysis. As their major advisor and classroom instructor, Researcher 1 has for decades seen how her adult students typically flourished in the graduate-level classroom despite heavy workloads and (often) heavy family responsibilities. As a graduate student, she had worked part-time and gone to school full-time (the reverse situation of this group) and was fortunate to have been teaching and studying in the same institution at the same time. She has watched her extremely busy students master an ability to excel in all areas of their lives and has always wondered how they managed, and if this management was as easy as they made it appear. She went into this investigation truly wanting to know not only how they did what they did, but how they experienced their academic lives and the impact that their studies had on their work and personal lives. As Researcher 2 interviewed the study participants, he found his own experiences as a part-time student in the program and working full-time coming to the surface, so he worked to use this common knowledge and experiences as a tool to assist him in hearing the interviewees as opposed to coaching or leading them. He went into this investigation realizing that each of us has an independent and unique graduate experience, and he was eager to hear about the interviewees’ personal perspective and personal journey toward their degree. The interview protocol was based on the literature cited earlier. The researchers did not go into this investigation knowing nothing of how adults transferred learning outcomes from organizational learning initiatives to the workplace, as quantitative literature existed. This literature was used to identify questions that could be used to help participants reflect on their experiences. Researcher 1 emailed an invitation to participate to individuals who met these criteria and who had graduated within the past three years. Those interested in participating were asked to return a short questionnaire, and Researcher 1 selected six participants on the basis of obtaining a diverse group (diverse in terms of gender, age, race, socio-economic status, marital status, and job levels). The researchers gave each volunteer a $50 gift certificate from the University Bookstore. Researcher 2 conducted most interviews face-toface; two were conducted via the phone. Each interview lasted approximately 90 minutes. Researcher 2 recorded and stored data on a digital recorder, then

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downloaded data to a memory device. Later, both researchers—and a graduate assistant—transcribed the recordings, which were subsequently reviewed by the participants for clarity and completeness. Additionally, Researcher 2 wrote a detailed reflective log after each interview. Treatment of the data followed a modified approach developed by Colaizzi (1978). Individually, we carefully read all transcripts several times, to ensure that we had a good understanding of each participant. Then, each researcher identified significant statements and later we worked together to develop codes that could be used to group the significant statements. We used a qualitative software analysis tool, Atlas.ti, to sort and network the coded statements. The next step was to translate coded statements into meanings and then organize them into themes. We complied with the strict requirements of the University’s Committee on Human Subjects. Participation was voluntary and confidentiality was maintained. Consent forms were developed and signed. Data have been kept secure and will be destroyed in three years.

THE PARTICIPANTS Six graduates who had studied part-time for either an MA in Business Education or an Advanced Certificate in Workplace Learning while working in fulltime jobs were the focus of this study. Situated in a school of education, the MA is a 36-credit degree, and the Post-BA Advanced Certificate consists of 18 credits that could also be applied toward an MA. The curriculum is aimed at understanding adult learning in both academic and organizational settings. Students take course coursework in research techniques, instructional design, curriculum development, instructional strategies, and evaluation of learning. Supplementing these specialization courses are courses in educational foundations and advanced content areas, typically taken in our school of business. An internship option exists; however, those who come in with full-time positions are not required to do an internship. Four female and two male graduates between the ages of 29 and 51 (average age when they graduated—36) agreed to be interviewed. Of the six, three had been working directly in positions related to their major—as an educational specialist, a technical trainer, and as a college instructor; the other three were in marketing related positions—marketing (general), product manager, and as a vice president of sales. Of note, each participant had either changed jobs—or added a job (the vice president of sales became an adjunct professor)—while

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studying. Two married while studying; two were single, two were in committed relationships; and none had children. One woman was Asian-American; others were Caucasian, with one participant an international student from South Africa.

FINDINGS We have organized the findings around nine central themes, relating these individuals’ experiences to taking a journey. These themes and their context are discussed in this section.

Theme 1: Why I embarked on the journey: A graduate degree = career development Several participants suggested that they began studying to obtain the position they wanted, and two commented they believed they were hired in their current positions because of their pursuit of the degree. The general consensus was that they, as individuals, wanted this particular degree as a means for career development. Knowing that I didn’t have a master’s degree, she [the hiring Program Director] suggested that if I wanted to continue this [adjuncting], that I probably should get a master’s degree. Yeah, as a matter of fact she suggested Business Education over an MBA. Because she told me at the time that she had MBAs coming in every single day and she was really looking for someone who could understand what goes on in the classroom over a simple MBA. I shouldn’t say simple. I was having a really hard time getting a job at the level I wanted so I looked into going back to school, which is when I decided to do my Master’s parttime. I realized that I really wanted to get back into Learning and Development. I think the reason I was really able to get going and encouraged to go back to school is because I was quite bored in my job.

For these individuals, going back to school had meaning—they wanted to expand their knowledge of their field so as to have a useful credential and at the same time were excited about doing so. As the following section shows, these individuals were quite confident of their abilities.

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Theme 2: I’m the driver: I can do it! No participant doubted his or her ability to succeed in graduate school. While several expressed math, writing, or test-taking phobias, all were confident from the start that they would succeed. This confidence was a result of past academic experiences and feedback they had received through their workplace. I always enjoyed being a student. I know that, you know, if I study hard I can do well on anything. If I have my mind set to it I will do well in any of the classes. I believe I was a pretty good student. I do well in a work setting. If you give me something to do, if you give me deadline, give me timeframe I do it you know no matter what. I’ve always done well. I put a lot of pressure on myself. It was uncertain that [my company] was going to pay for half unless I got a certain grade. It really changes things when you realize that you’re paying out of pocket. The fact that I was going back to school under different circumstances than usual, that was part-time and I have a demanding job really made me focused and concentrated on achieving results so I was extremely dedicated to achieving results and success in my academics. Again, I put a lot of pressure on myself. Throughout my career I have always progressed pretty quickly. A lot of it [going back to school] had to do with my confidence in my ability really to know that I could go back to school do really well.

From these quotations, it is clear that any obstacle to completing their degree was not a result of their own ability to excel in an academic environment. However, they all reported they needed support from friends and family, as reported below.

Theme 3: Roadside support: I had help! Participants who were in committed relationships had an easier time balancing work/life/school issues than the two single (and not engaged) women in the study. Here’s how a few of those in committed relationships described the support they received: My wife was very supportive. She knew the amount of work that was involved in getting a master’s degree. I would spend hours upon hours researching, writing papers. That was never a problem.

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Bridget N. O’Connor and Robert Cordova My family and my husband was a tremendous support, and so were my friends and family, you know, extremely patient. My husband values education highly. All those weekends when I was working seeing him very little. He always encouraged me, and so did my family. I know my partner, you know, was working full-time while I was in school. So even though I was paying for tuition with loans[,] … there were a lot other expenses, food, just general expenses that were, fell more to him during those periods.

The single women were more challenged, although not for the same reasons: And my parents are traditional, you know. They really don’t see a woman, you know, going so far, you know going out with schooling, you know, for years. Their goal for me is to get married and settle down, that’s it. So I didn’t really get more support from my family. Myself, I guess I didn’t, I should have been more firm about it and I didn’t. Yeah. My sister is going for her pharmaceutical doctor degree right now. So it’s like, okay, you have a master’s degree, good, good, good enough. I guess for our parents, it’s never good enough for them. I remember my friend commenting, because I was stressed out about something[,] … “How do you manage a full-time job, go to graduate school, have this new boyfriend, host parties, and something else.… Oh work out.…” So yeah, I realized I did have a lot going on. Yeah, I was a deacon at church as well. So I was really involved in my church community, so there was a lot. There was a lot.

It is important to point out here that despite time demand issues, all participants coped. Following is how they described problems related to balancing their personal, work, and school lives.

Theme 4: Detours: A search for balance World events, demanding jobs, and demanding schoolwork all competed for their time and energies. One of the interviewees had begun her MA the semester of 9/11. She subsequently took a semester off to cope with her overwhelming sadness, but did return. When she did return, she and one other interviewee typically enrolled in only one class a semester. Here’s what she said:

Learning: The Experiences of Adults Who Work Full-tim I lost a bunch of people [during 9/11]. People coming up to you and reminding you of it all the time…. I had just moved; there were lots of changes in my life at that time. I thought about quitting like, almost every semester. I thought like, why am I doing this? It was really hard. It was really hard for me. It was hard to go to school, go to work, to have relationships, and deal with 9/11 and all this stuff going on. I took a semester off after that first semester. I had taken an extension. That first semester back at [company] was really difficult for me—how difficult it would be to be back at [company] with 9/11 in your face.

Others simply described challenges in finding enough time in the day to do what needed to be done: I think that it was demanding. Because at the end of the day, the last thing I wanted to do was come home and do reading or whatever or spending my weekends doing homework. But that was at a time in my life when it was rewarding and satisfying, and I liked it. You know there were moments I felt overwhelmed. Oh my God. Weekends I had to write papers you know, meet up with my groups to discuss the projects. But for the most part, I managed. I don’t know how I did but managed to go through all the paper writing, all the reading I had to do for school. I am amazed how I did it.

Theme 5: Potholes: Limited workplace support These part-time students faced unexpected challenges in the workplace. Sometimes, they reported their peers simply dismissed the value of their graduate work; and other times their supervisors downplayed the value of their studying. That said, four had financial support from their employers, including half tuition, a set dollar amount, and complete reimbursement. Only two were responsible for their own tuition, often taking out student loans or tapping their $401Ks to pay tuition. One respondent, interestingly enough, found emotional support outside of her immediate group, but not within it. I think the work that I did was valued if I kept it to…. Yeah, I’d say it was more outside of my group; it was valued by the business, by the people outside of

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Bridget N. O’Connor and Robert Cordova my group who were directly affected by my work. I’ve always gotten great kudos from project managers. There is really no career path for trainers. I get all the time, “Oh, you’re still in training?” It’s not really a valued position. It [a graduate degree] wasn’t a priority to my supervisor. Because again I was working in those positions where I wasn’t, a degree wasn’t required. This latest position, I think, it was one of the reasons why they were interested in hiring me. So that, so they were more supportive…. As far as knowing that I’m not going to thrive in this place. Because they really don’t appreciate higher education. I kinda thought that I would be asked to, “[Name], we know you’re taking this class[,] … let’s maybe do a lunch and learn—we’d love to hear more about evaluation, how we can incorporate that into [company]. We’d love to…. However, when I brought up Kirkpatrick, I was told to stuff it down. I was not supposed to use that verbiage. Adult learning and education and that everyone should know. I wasn’t trying to boast; I was trying to share and those are things we don’t know we don’t want to hear it.

Life and jobs have a way of changing, and those who reported an ability to apply what they were learning on the job reported the highest job satisfaction. As noted earlier, everyone interviewed either changed jobs or added a job while they were studying—usually they wanted more opportunities to apply what they were learning, and when they found positions that provided that, switched jobs; when transferred to areas in their organizations that were more unrelated, they were not happy. Overall, these students were incredibly agile, adept, and confident that they knew what they wanted. I think the reason why I like my work so much is that it matters. It matters to the individuals who want to do something better in their in their jobs. I knew it [a career in Learning] was in my career trajectory. Absolutely. I liked my work when I was going to school. When I could do it. At the beginning, I was very happy. It was really two different experiences. One, when I was happy at work and with the certification project. As time went on, I didn’t want to be working where I was; I was trying to get into the [Learning and Development] organization I am [now] in. So for the first half, very happy, and second half very unhappy.

Learning: The Experiences of Adults Who Work Full-tim

The students were frustrated when they were unable to use what they were learning right away. I got a little bit frustrated with the business education program. I was really looking for something more applicable to my work and I found that a lot of the discussion was very theoretical. There was a lot of value actually for me, some of it from the professional standpoint—just to personal situations as well, the group dynamics [course] resonated from that point of view because it was very real. I really found this class [web design] incredibly frustrating. I didn’t see how this class fit into helping me in my current context at all. I think it [electives] did give me what I was looking for; they were more aligned with what I was doing at work. Even if I was applying it immediately at work, it was more in line with the skills I would have hoped to have gone or was looking to get through the business education program.

Theme 6: Behind the wheel: Active learning Participants reported that they learned best when they were treated as adults— when instructional methods matched the way they preferred to learn. Well, I think that [Professor Y’s] [classes stood out] because of her teaching style. I had never seen anybody teach her classes that way. Different activities. Her classes stood out for that reason. Her ability to listen and hear what people had to say and facilitate a discussion. She was a great role model as far as facilitating. She was one of the best facilitators that I’ve ever seen in an academic environment. I’ve seen that kind of skill in a corporate environments since then, but that was my first experience in an academic environment. Yeah, one thing that I remember with [Professor Y’s] class was the videotaping exercise. That was nerve wrecking but as well as so helpful. You really, really see what you did wrong. That was really helpful. It was fun, too. I got to watch everyone else’s video.

However, when they encountered individuals who they acknowledged knew what they were talking about but who did not engage them in the learning, reported:

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Bridget N. O’Connor and Robert Cordova They [graduate students who were giving guest lectures] were very concentrated on the subject matter and the research they were doing and trying to get deep into the research and didn’t relate to us as students. So I didn’t find that as interesting. At [the business school], they [professors] used a lot of PowerPoints. They would hand out a copy of the lecture on PowerPoint, show it on slides. I found that I almost never looked at the printout after I left the class. I might use it to scribble some notes on. But I found it much useful to just to take my own notes in a notebook. And I found, I actually found the PowerPoint more distracting. So I never got into using it. I may be wrong on that. But I didn’t find it a good learning tool. The professor was so awful. She was an adjunct professor. Treated us like children. She read her dittos. She treated us with utter and no respect, so we had none for her. This one class I took, the professor was very, just kind of like, you know, standing there and didn’t do much. And even though the class was huge, we had like sixty students. And after the first day of the class, half of the class didn’t bother to come to lectures. Yeah, it was that bad. The professor, yeah, she wasn’t engaging. All the notes that she had in the PowerPoint were directly taken from the book.

Despite problems related to finding time for group work outside of class, group projects were definitely appreciated: [I liked] group projects. I always met great people. You know, I had good experience with that and it was encouraging. Yeah, it wouldn’t be a program if it was just me sitting in a room. Because of [Professor X and Professor Y’s] teaching style, you couldn’t have any learning without your peers, it was all about peer learning. And it was pretty cool for people to share their experiences. I think because I was one of the few people who were actually in the job they were appreciative of my experiences, too.

And when asked about challenging subjects, they were positive when they encountered professors who knew not only what they were talking about, but also how to teach:

Learning: The Experiences of Adults Who Work Full-tim I remember taking a statistics course, saying like “Oh my gosh, I am going to fail this,” you know. But [Professor X] really presented it that way—like that’s the teacher you always wanted for stats. Because they really understood how to teach, again that you can be a subject matter expert but really know nothing about how to deliver. You can be a SME [subject matter expert], but not really know how to teach. That was fantastic.

They preferred class sessions and assignments that presented challenges or caused them to think about learning in new ways. I’m definitely a learner by doing. I’m not too much of a reader…. I want to get in and do it. I don’t have the greatest attention span in reading directions or so on. One that [Professor Y] taught, I remember it was called adult learning. She had a great practice in that class. I remember ... the learning journal. That’s a good way for me to learn, like I really like to journal anyway. So I really enjoyed that process.… It was a catharsis of like, wow, we’re learning this, but this is how we’re doing this at [my company]. That was a good outlet for me. And I remember another thing I liked in that class, she would hand out little strips of paper, like with questions, and it was very self-taught. I remember, “Like, who’s teaching this class? Are we teaching each other? Aren’t you here for a reason, like ‘teach me’!” Like even though that didn’t work for me, I thought, “That was the way to do it!” It was this class—the session where my group presented the book Good to Great. And I just felt that session was, because we had three of us were reading the book together and we had to put together a presentation to present a book to the class. I felt when that’s the class we presented even as much as I was so nervous about presenting it, but at the end I felt so good about that. Because I know everyone in the class said just like, “Wow, I want to go out now and read this book.”

While these graduates remembered only a few specific class sessions that they had with their major professors, they did remember specific teaching strategies, such as the ones listed above. However, half of the group identified two specific guest lecturers as highlights of their time in the classroom; one was a renowned neuroscientist, and the other a well known consultant and book author.

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Bridget N. O’Connor and Robert Cordova That was the semester she [Professor Y] brought in a neuroscientist from [university]. Who talked about…. Yeah, the brain guy. That was one of those classes that I didn’t want that lecture to stop. [Professor Y] had a medical doctor come in and talk with us about how the brain worked. And I remember that session. Something was wrong with the computer, and his charts, so he had to draw them on the blackboard. He was fascinating, very interesting, and left a very strong impression on me. Another guest lecturer I remember vividly; I think his name was; I want to say [incorrect name]. He talked to us about getting published. A professor who was well published in the New York Times and he explained to us about how to go about getting published. [Correct name!] I remember that session. And I remember the reading circles.

The individuals in this study were also quick to point out instances where they were given special, individual attention by a professor: I really had to come to terms with my writing in graduate school…. [Professor Y] let me do a paper on mindfulness. This woman…. [I]t was on her book list—not just educational mindfulness, but general mindfulness— and so I really got into that, and because of it, I wrote a better paper, and I got a great grade on it. Because I was really interested in it. They allowed me to flourish. I had a lot of fun with one class. Maybe [Professor Y] might, may have spoken about it, where I had to analyze a book and was supposed to be a group project. And I was in it with another person and the other person dropped the class. And I was the only one doing the book. So I had to read the book, and analyze it and do a presentation on it by myself. And it was about a 500-page book on Alexander Hamilton. But I enjoyed the subject. It wasn’t an education subject. It was a history subject. Obviously, Alexander Hamilton as the subject, and I had to make the presentation on my own. And I had some fun with it. I tried to use some of the techniques that [Professors X & Y] used, you know, using visuals, and I even gave out prizes at the end for people who could answer questions as [Professor X] did.

Learning: The Experiences of Adults Who Work Full-tim [Professors X & Y] were really encouraging around projects, papers, ideas. I can’t remember either one of them saying, “eh… maybe not.”

Perhaps the set of the most telling remarks around their experiences as parttime students were those around how they felt while in the academic classroom. Interviewees seemed to become quite animated when discussing how they felt when they were studying: I just wanted to do it for my personal reason, to feel more, I guess to feel more alive. You know when I work, every day is the same. You go to the office. You do what you got to do. Then you leave work. That’s it. That’s the end of the day. Going back to school just makes me feel more alive. Yeah, I miss school now though. I loved school so much. Back to me now. School allowed me to, like, be me. Like [Professors X & Y] didn’t mind me asking questions, challenging, throwing crazy ideas, you know, being a leader, all that stuff. And I loved that! I loved being around people who liked that, and who wanted to learn. And I liked being supported in that. He [an adjunct professor] had seen me in class and knew me—everything that he said he liked about me, was what in my performance review was what [my company] didn’t like about me. Oh, yeah, like don’t talk up at meetings, you know, that my new ideas stunk, like I really feel, even though I didn’t take that job, it felt that professor was a life reason, he gave me a counterbalance to my review at [my company]; it really crushed me and it gave me a reality check. You know, here are my talents—like I had the same talents in both areas, at school and at job, but at work they were considered a negative. And I really got to see that they were the same skills, but they were assets, assets in different settings.

Theme 7: Others on the road: A quest for community Interviewees reported that they wished they had had more time to interact with their classmates and be a bigger part of the overall university community and were sometime a bit envious of those who were full-time students. All but one were members of Delta Pi Epsilon, the Business Education Honorary Society,

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and for many, participation in that organization’s events were their only university-related social networking outlet. Sometimes, because of time constraints or because they were not lock-stepped in their curriculum with the same set of students, they felt a distinct lack of community. Not at all [involvement with extracurricular]. I really regret that. But I felt I had so much going at work, at school, deacon at church. New relationship. I remember, like they really recruited me for DPE and I was already begrudging going up to the upper east side for church, doing volunteer stuff for church, and I knew I am going to be really nasty at these meetings, and I didn’t want to do that. I feel I really missed out on that. The part-time people had no time to get involved and be a part of the community. There was no one I was really going through with; no one started with me, and then ended with me, took the same electives or anything. I didn’t really feel that. Oh, [peers] helped very, helped very much. I was with a group of students who were in a doctoral program. And I was not, but I was only in the master’s program. But they helped me a lot. A lot of my group work was done with them. Some of them [classmates] had already had master’s, they had previous master’s, going for second and third master’s. They were able to teach me a lot. It [classmate comradeship] was very high. Especially among people who had deep work experiences. People who really wanted to be there are were professionally mature; there was a lot of comradery. It was probably that kind of experience…. Younger or less experienced students were a little overwhelmed by that. I didn’t feel as tight a connection with them, necessarily. I think working with them [my classmates] in a sort of interaction with them certainly helped my education. I got a lot of positive feedback from them. So this was good reinforcement, which I thought was good I liked being back on campus. It made me feel young again, being around all those young people. Those kids! They don’t know how good they have it.

Learning: The Experiences of Adults Who Work Full-tim I wasn’t socializing with a lot of them [classmates]. I met two wonderful, wonderful friends throughout the program. And we still keep in touch. But I wasn’t that involved in social thing of the graduate school. I wish, I wish with this program we have more of kind of happy hour, or like we meet, you know, more often, more social events.

The campus environment was not an important part of their lives. None used the school’s athletic/recreational facilities, and many reported they did not use the physical library, instead relying on its digital holdings. However, two students did find the library a useful location for doing school work: Yeah, I did spend a lot of time on campus. The library was just my place for doing work. I really enjoyed the environment. I really used the library facility to do my research and write papers. I will bring my laptop there. The sports center I wish I used more. During my graduate years, I didn’t use sports center at all. I didn’t take advantage of it. I should have. But I didn’t. I definitely was in the library just because I used that as a way to get out of the house, get away from distractions. So I would use library, computer labs and such. But it was directly related to like academic work. I wasn’t going to Kimball Hall, is that the student center? I think that the library offered fantastic resources. The online research and resources are incredibly valuable. I actually miss not having [them] at my fingertips.

Theme 8: The road ahead: I have options for the future Just as these interviewees were confident of their ability to succeed in graduate school, they were equally confident that they would do well, and that they were on a career trajectory. I am so very grateful for so many things in my life. A big part of it is my education[,] … all the opportunities that I’ve had. I really feel I can do anything. I don’t think [I will] dramatically [change careers]. I can see it yeah, some sort of soft skills capacity, maybe, or train-the-trainer, training other people to be trainers, but I don’t see it dramatically changing. I really enjoy

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Bridget N. O’Connor and Robert Cordova education…. There’s no train the trainer, and this is my dream, this is one of the reasons I’ve stayed, my former boss [said to me,] if that group ever comes back, you should be at the head of that group of regional trainers. [This is] my pipe dream.

That said, a number were frustrated by having too many options, suggesting that having succeeded in a graduate program made them even more marketable that they ever believed they could be. And several interviewees were looking into the possibility of continuing their education. That’s part of my frustration in not knowing where to go next is knowing that I can do anything. I could go to India for 6 months; I could go back to Detroit. I could move to the West Coast where I always wanted to live. I could go back to school. I could take an internship here. So many options. I am really grateful for that, but that [but I want to be in] a position that was using all my talents. I am looking for a top management position in learning. I would like to get my doctorate in education, and I have no idea if that could ever happen. I would love to stay in Learning and Development. Perhaps doing something on my own at some point as a consultant or coaching. At some point I may do a coaching certification.

Theme 9: Yes! The journey was worth it: Impact We were careful in examining statements in which the interviewees described any impact having a professional degree had on their lives; after all, as adults they brought a significant set of experiences with them to academia, and much of their success can be attributed to their individual characteristics. However, nearly everyone did make what we considered to be explicit statements that credited what they learned with either job opportunities or skills/understandings that made their work life richer; for example: I do think that if I wasn’t doing my masters when I interviewed with [the second company] I don’t know if they would’ve hired me for this role. They were interested in the fact that I had some background with Training and Development and the fact that I was doing my masters was compelling for them to hire me.

Learning: The Experiences of Adults Who Work Full-tim I really like that—actually conducting classes; seeing people’s ah-ha moments. Having heart-to-heart one on ones with people, how they haven’t been able to learn in the past. You know, talking to people about different learning styles. Connecting to them about that. Yeah, I am doing what I want to do. Enjoy working for [company as vice-president for marketing]. I enjoy the freedom that allows me to be able to teach, do what I like to do in the classroom. I certainly learned a lot about research at [my university]. And that becomes very handy in business. I have been asked to be part of the president of the college’s marketing recommendations’ team. I am happy with my work situations, income, family situation. I have achieved the degree I wanted to. And I am using, I am using it every day I try [to bring the business world into my classroom] as much as I can in my teaching also. I think it makes it more interesting for students than just keeping the academic. I came here to get a degree so that I could teach. I am doing what I wanted to do. I guess it would be better if I had a PhD. But I don’t know how much better would make the experience for me. Maybe it would be better for the students. I am not sure. But you know I am happy. I’ve been in Learning [the Learning Department] for two years; it’s going extremely well. My managers have put me in top talent and they are trying to get me into what they call leader readiness training program. I went through a major career change and I’ve kinda had to fight tooth and nail to get into the Learning Organization [department] at [my company]. The value was that I was able to take problems and analyze them in a very disciplined way. That has made me a better learner in the workplace. I’ve taken some of that discipline of the classroom and put it in the workplace. And being able to reflect upon what was going on at work in that “safe” environment.

Participants overwhelmingly saw themselves as having a new “self,” demonstrated by new jobs and the newly realized importance of friends and family. I have the best friends. I have the best hobbies. And the best… best opportunities outside of work. I love to dance. I love to knit. I love to be with friends. I love to travel. And my job affords me the ability to do things. Both time and monetarily. And I have a great family. Healthy.

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Bridget N. O’Connor and Robert Cordova I am very pleased with my life. I have my recreation time at the beach that I enjoy and I am able to balance all the things I love to do. I got my family, I got my great friends. I have got a life which other people would die for. You look at all the unfortunate, poor, hungry people out there in other countries. I feel very lucky and very blessed, yeah. I am pretty happy with my personal and professional life. I do work in a non-profit, I am little bit under compensated. But that was a choice, so…

While acknowledging overall life satisfaction, the two single women reported they were continuing to struggle. One explicitly credited part of her angst to not having a “soul mate”; but the other reported being quite satisfied with her personal life of friends and family. Their unhappiness at their current jobs, too, were for different reasons. One was concerned that she was in the wrong industry; the other that she was working in the wrong company. Both expressed a need to be more content: So you know, the financial industry, I don’t think it’s a fit for me. As much as you know what’s keeping me here obviously is the money. I am comfortable with the money I am making and it gives me a life style I am comfortable with. But I just I am not passionate about it. This is just a job… not a career I want to be in. No, sadly, I’ve lost my mojo there [at the company]. You do the little that you can. In their defense, it’s turning a huge ship. If [the company] were a tiny person, I’d be able to do everything I learned. But [company] is the world’s largest insurance brokerage, it so gigantic. It’s old school. To get them to make any change, I’d have to lower my expectations about how fast that could happen. Change is difficult, you know, you’re learning that! So, it’s definitely not all [company]. It’s definitely about having realistic expectations about what we can do. Yeah, they’re getting rid of their regional trainers. And what can I do. And how can I be more creative about how we train the people. Admittedly, I’m not the best first starter and I definitely need encouragement. I could say I’m going to do it anyway, but I don’t. I would not be at [my company] if that were the case. I’d be more of an entrepreneur. Self-starter. I’m sure there are many factors that go into my decision to stay at [company]. At the end of the day, I’m still there.

Learning: The Experiences of Adults Who Work Full-tim

DISCUSSION AND IMPLICATIONS The goal of this research was to explore how these individuals experienced their lives as part-time graduate students studying in a professional field. We have established that the experiences of these part-time students were characterized by strong internal motivation and self-assurance, appreciation for those in their lives who helped them both in and outside the classroom, and a preference for learning experiences in which they were active learners and had some control. All were regretful that they hadn’t had more of a traditional college experience, or were able to take advantage of professional and social networking options. And nearly all suggested that through all of this, they felt they were truly themselves the most while they were involved in their academic work. Several findings stand out here. First is the degree to which they yearned for community within the academic community and felt powerless to make it happen. While several were able to develop strong ties with their classmates, all regretted not being more involved socially, and several regretted not having had a close circle of classmates who were also friends; however, these same individuals reported that they simply had no time to attend extracurricular events, take advantage of campus facilities, or establish friendships. We both are aware that the program offered opportunities to have formal mentors and that several times a semester, professional/social networking options were offered. Moreover, we know that students had only a six-course (eighteen-credit) core and other courses were in educational foundations and advanced business content. However, perceptions were that such opportunities and others that would introduce them to university life were limited or nonexistent. An implication for Program development is to develop or explore, and better advertise extracurricular options that are either more convenient or more frequent for this population. We were also surprised that despite so many of these individuals having financial support from the company they worked for, they had very limited opportunity to apply what they were learning on the job. Several employers were either indifferent or outright unsupportive in the workplace. On first blush, the odds of this entire group making job changes while studying stood out, but on reflection, their self-confidence and need for relevancy of their degree may have contributed to their search for “something else.” In the one case where the student was moved laterally in her company to an area unrelated to the Learning Department led to job dissatisfaction. Just as Lindell and Stenstron (2005) found, job engagement was highest when there was a match between what was being studied was useful on the job.

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The academic program that these students chose is described in terms that imply relevance to designing and implementing adult learning programs in both academic and corporate environments. In some instances, when students learned what might be considered an ideal way to, for example, conduct needs assessments, but were unable to apply these approaches in the workplace, dissonance occurred. As in other studies (Tracy, Tannenbaum, and Kavanagh, 1995; Egan, Yang, and Bartlett, 2004), these individuals did not find the organizational environment conducive to transferring their learning. In a study of a corporate training environment, locus of control and self-efficacy were the mitigating variables (Cheng and Ho, 1998); here, however, the workplace itself was the obstacle. Other times, what was being learned was perceived as having not much relevance (for example, research), or no direct relevance (for example, group dynamics) and students reported no value in such experiences. An implication here is for academic advisors to manage student expectations better and for managers to be more open to new ideas. As an instructor in this program, Researcher 1 anticipated that interviewees would report preferring classes in which they were expected to share their life and work experiences and their preference for active learning and for instructors who listened to them, challenged them, and gave them opportunities to take control of their learning either through assignment choices or group work. She was surprised, however, that many felt they did not have the peer network that they expected/wanted. The implication here is the desirability of more active mentoring and ensuring that extracurricular activities are accessible and interesting. But perhaps the most meaningful finding for both researchers was the commentary around how much these individuals loved being students. Their selfconfidence and need to achieve was a direct match for a challenging graduate program. When interviewees reported that they felt more alive, more “me” when studying, the researchers knew they had hit upon something interesting. Consistent with Wenger’s (2003) research, it was when those personal characteristics that made them ideal students bumped into work environments that did not take advantage of not only what they were capable of contributing to the organization but, more importantly, their personal being, that the largest disconnect was found.

LIMITATIONS We realize this study does not meet the strict guidelines of phenomenological research in that a considerable number of prior studies in a related field (Learning and Development) were available to help us frame the research questions.

Learning: The Experiences of Adults Who Work Full-tim

Moreover, we were concerned that these interviewees would be reluctant to express any negative experiences to us as they knew one of us quite well. That said, in reviewing the transcripts, neither of us had any inkling of hesitancy to report dissatisfaction on the part of the interviewees. In fact, Researcher 2 found that as he conducted the interviews, the participants saw him as a confederate. In pre-interview discussions, he set expectations for a clear and detailed account of their experiences. All candidates acknowledged and respected the value of this research as professionals, which allowed them to be frank and candid in their responses.

CONCLUSIONS The experiences of students who are working full-time and going to graduate school part-time were the focus of this investigation. As a group of learners, this group has been seldom studied; the literature cited here, for the most part, comes from the learning and development literature. What is clear is that the experiences these individuals report with regard to relevancy and transferability of what is learned is inconsistent with the quantitative findings (Cheng and Ho, 1998; Lim and Johnson, 2002). In this investigation, individuals reported high job involvement and strong career planning, but were often stymied when they attempted to apply new ideas to the workplace. An explanation, perhaps, is the limited degree to which individuals at these levels have power to change work procedures in the workplace. Additionally, a perceived lack of relevance both in the academic setting and in the corporate setting may have added to feelings of dissonance. Academic coaching prior to and after completing a course may have allowed the interviewees to discuss personal and content relevance, while career or workplace coaching may have aided in defining content relevance that may have been overlooked or misunderstood. While this study was exploratory and extremely limited in scope, findings do provide a clear distinction between the role of corporate education and its (usually) focused rationale for planned learning experiences and the role of academia in providing an outlet that provides learners more opportunities to explore what it means to be themselves—in an environment where risk is limited and opportunities to be themselves flourish.

REFERENCES Alvarez, K.; Salas, E., and Garofano, C. M. (2004). An integrated model of training evaluation and effectiveness. Human Resource Development Review, 3 (4), 385–416.

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Bridget N. O’Connor and Robert Cordova Baldwin, T. T., and Ford, J. K. (1988). Transfer of training: A review and directions for future research. Personnel Psychology, 41 (1), 63–65. Brookfield, S. D. (1987). Developing Critical Thinkers: Challenging Adults to Explore Alternative Ways of Thinking and Acting. San Francisco: Jossey-Bass. Cheng, E. W. L, and Ho, D. C. K. (1998). Transfer of training: Some practical thoughts from theoretical studies. International Journal of Management, 15 (1), 14–20. Chism, N. V., and Bickford, D. J. (2002). The Importance of Physical Space in Creating Supportive Learning Environments, volume 92: New Directions for Teaching and Learning. San Francisco: Jossey-Bass. Colaizzi, P. F. (1978). Psychological research as the phenomenologist views it. In R. Vaile and M. King (eds.), Existential phenomenological alternatives for psychology. New York: Oxford University Press. Creswell, J. (1998). Qualitative Inquiry and Research Design: Choosing Among Five Traditions. Thousand Oaks, CA: Sage Publications. Egan, T. M.; Yang, B., and Bartlett, K. R. (2004). The effects of organizational learning culture and job satisfaction on motivation to transfer learning and turnover intention. Human Resource Development Quarterly, 15 (3) 279–301. Illeris, K. (2004). The Three Dimensions of Learning. Malabar, FL: Krieger Publishing Company. Jarvis, P. (2006). Towards a Comprehensive Theory of Human Learning. London: Routledge Press. Lim, D. H., and Johnson, S. D. (2002). Trainee perceptions of factors that influence learning transfer. International Journal of Training and Management, 6 (1), 36–48. Lindell, M., and Stenstrom, M. (2005). Between policy and practice: Structuring workplace learning in higher vocational education in Sweden and Finland. Journal of Workplace Learning, 17 (3/4), 194. Mackeracher, D. (2004). Making Sense of Adult Learning. Toronto: University of Toronto Press. Mathieu, J. E., Martineau, J. W., and Tannenbaum, S. I. (1993). Individual and situational influences on the development of self-efficacy: Implications for training effectiveness. Personnel Psychology, 46 (1), 125–147. McKeachie, W. J., and Svinicki, Marilla (2006). McKeachie’s Teaching Tips. New York: Houghton Mifflin. O’Connor, B. N.; Bronner, M., and Delaney, C. (2007). Learning at Work: How to Support Individual and Organizational Learning. Amherst, MA: HRD Press. Tracey, J. B., Tannenbaum, S. I., and Kavanagh, M. J. (1995). Applying trained skills on the job: The importance of the work environment. Journal of Applied Psychology, 80 (2), 239–252. Wenger, E. (2003). Oral presentation at 2003 Practice-Oriented Education Conference, Boston, MA.

CHAPTER 14

Identifying and Classifying Corporate Universities in the United States1 AMY LUI ABEL, PhD The Conference Board

O

rganizations have historically charged their training departments to ensure that workers possessed appropriate skill sets to do their jobs. Often, employees attended classes focused on specific job skills and did not necessarily understand how the content was connected to the organization as a whole. Training departments were typically reactive, tactical, organizationally disconnected, and focused on specific individual job skills (Meister, 1998). In the last few decades, however, the training department has changed and advanced. Once organized on a school-based model, where the focus of programs was on the instructor in the classroom, training departments have progressed to embrace a learner-based model, where the focus is on learner needs and outcomes, and operates whenever and wherever the learner needs to learn something. Representing this shift and focus on the learner, a new organizational form has emerged describing the

1 This chapter was originally printed in Malloch, Cairns, Evansm and O’Connor (eds.) (2011), The International Handbook of Workplace Learning. Thousand Oaks, CA: Sage Publications. The author would like to acknowledge and thank New York University Professor Emeritus Michael Bronner for his gracious counsel in helping me develop and refine this chapter, as well as his numerous editing reviews. His support is greatly appreciated.

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function of learning and development—the corporate university. The corporate university has become the internal entity of an organization that is responsible for strategic employee development and workplace learning initiatives that would broaden the organization’s competitive advantages. Notable examples of corporate universities are JetBlue University, Motorola University, MasterCard University, Harley-Davidson University, Disney University, and Intel University to name but a few. Despite the dramatic growth of corporate universities across all industries in the United States, they have been difficult to define in the literature and identify in practice as they have varying goals, serve and educate multiple audiences, implement different structures and operations, and rely on a wide variety learning practices and delivery methods (Blass, 2005; Morin and Renaud, 2004; Rademakers, 2005; Shaw, 2005). An extensive review of supporting literature from academia and industry reveals a complex array of corporate universities’ characteristics and dimensions. These characteristics and dimensions do not present a clear picture of what a corporate university is, thus neither help to operationalize the concept for researchers, nor create useful knowledge to assist managers in practice. To further our understanding of corporate universities, this chapter will introduce the corporate university phenomenon and present a summary of dimensions related to corporate universities. Then, a conceptual analysis of these dimensions will help define a corporate university. Finally, an empirical analysis will be presented to move forward to define and identify corporate universities. The analyses here are designed to offer insight into what corporate universities are and how this new organizational form is evolving. With a definition and a foundational base of what a corporate university is, further research can examine issues, differences, effectiveness, and performance related to corporate universities.

1. EVOLVING FORM OF CORPORATE UNIVERSITIES As a relatively new organizational form, corporate universities have been described with varied definitions and characteristics. Jarvis (2001) defined a corporate university as “a strategic umbrella concept for the institution, created for developing and educating employees and the company’s constituents in order to meet the corporation’s purposes. [He noted that such institutions are] systems of teaching and learning rather than universities in the traditional sense” (p. 104). Corporate universities connect learning experiences for the learner and develop competencies that relate to organizational goals (Rademakers,

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2005) and link learning with business results (Shaw, 2005). A corporate university assists companies in building a common culture and is a strategic partner in implementing change throughout an organization. A goal for the corporate university is to direct the learning and development of its members toward innovation and the strategic goals of the firm, which can spur superior competitive advantages. The evolution of the training department to the corporate university is reflected across different aspects of the learning function. Even the name and language of this function and its related terminology has changed. The process of training is now often referred to as the process of learning, and the training department is now often called learning and performance, or increasingly, the corporate university. Employee students are referred to as learners, not trainees. Playing a strategic partnership role in the organization, the trainer is now referred to as workplace learning and performance professional (O’Connor, Bronner, and Delaney, 2007). Of significant importance, the workplace learning professional with overall responsibility for the corporate university is often referred to as the Chief Learning Officer, on par with other C-level management titles such as the CEO, CFO, and COO, which indicates a shift in an organization’s understanding of the strategic importance of employee learning and development. These shifts in terminology are but one piece of evidence that the training department is transforming into a new organizational form. More than simply changing the terminology that describes their work, corporate universities establish objectives that are aligned with strategic organizational goals, such as improving business revenues or changing the culture for innovation. In the corporate university, learning is viewed as a continuous process that supports employees to constantly learn new skills and improve existing competencies. Curricula are designed to connect learning initiatives not just for the job, but for the career trajectory of the employee. Corporate universities offer the ability to customize materials and content, use Internet and technology-enabled delivery of materials, address training demands with speed and flexibility, offer a broad and comprehensive range of content, and meet strategic needs by continuously improving the learning processes of employees (Nixon and Helms, 2002). In the last two decades, the number of corporate universities has increased significantly. Some claimed that from 1988–2001, more than 100 four-year traditional colleges closed in the United States, while the number of corporate universities grew from 400 to 2,000 (Meister, 2001). Corporate University Xchange, a consortium organization of industry members, asserted that over

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1,500 corporate universities existed in 2002 (Hilse and Nicolai, 2004), and that by 2010, the number can grow beyond 4,200, exceeding the number of accredited for-profit and non-profit universities in the United States (Meister, 2006). Additionally, it is estimated that corporate training is a $60 billion market in the United States alone (Friga, Bettis, and Sullivan, 2003) and “there will be approaching 2,000 corporate universities at the turn of the millennium and that the annual budgets in 1998 of each one was on average $10.7 million” ( Jarvis, 2001, p. 104). The growth of corporate universities has been fueled by turbulence in the business and economic environment and demands from senior executives for greater efficiency and more measurable impact from their institutions’ learning initiatives.

2. DIMENSIONS OF THE CORPORATE UNIVERSITY From the literature and practice, dimensions of corporate universities can be documented; these dimensions include mission and strategy, governance and leadership, structure, stages of development, curriculum, learner population, evaluation and measurement, financing sources, technology usage, and partnerships with business line managers, human resources, external vendors, and academia. These 13 dimensions are the foundational clues that reveal what a corporate university is, and each will be explained and summarized.

Mission and Strategy The first dimension, a corporate university’s mission and strategy will determine the approach, leadership and reporting structure, resources available, and programs that will be utilized to execute the learning function. Successful corporate universities have learning strategies linked to business strategies. Learning strategies will determine how learning functions are designed and implemented. A corporate university’s primary mission can be the firm-wide development and execution for the company’s learning function based on the organization’s goals and major initiatives. “The mission of a corporate university is diversified into achieving the corporate strategy objectives, conveying its culture, and providing a systematic curriculum” (El-Tannir, 2002, p. 77). A mission of a corporate university can also focus on objectives, such as, “to systemize the training function, maximize the investment in education… spread common culture and values, develop employability of the workforce and remain competitive” (Morin and Renaud, 2004, p. 297).

Identifying and Classifying Corporate Universities

Governance and Leadership The second dimension, governance and leadership, may include a learning governance board where the top champions and business leaders of an organization collectively develop and support a shared vision for the corporate university. Senior executives who are committed to the learning function are key elements for the success of a corporate university. According to an industry benchmarking report, 67 percent of corporate universities have a learning governance board in place, and typical functions for this board include “identifying and prioritizing organizational needs, setting learning philosophy, and defining corporate university’s mission and vision” (Todd, 2004, p. 46). The governance board includes members who are actively promoting corporate university capabilities internal and external to the company. Many organizations have established a leader in charge of the corporate university function, the Chief Learning Officer (CLO). Looking beyond training programs, Chief Learning Officers are asked to manage human capital issues for the organization. These issues may include globalization of the learning function, reducing costs of learning delivery, decreasing time of learning for new employees, and “using learning as a strategic weapon to enter new business markets and geographies” (Meister, 2006, p. 70). From the 2006 American Society for Training and Development State of the Industry Report, over 90 percent of high performing learning organizations reported having a CLO position that was responsible for learning initiatives and had learning objectives as part of their own performance measures.

Structure Structure, the third dimension of a corporate university, may range from centralized (focus of authority, decision making, and communication) to decentralized (distributed and shared decision making). In a decentralized learning function, programs and initiatives are managed by disparate business units with little or no coordination of learning activities. Informal coordination of learning functions may be represented by distributed learning units throughout the company, and loose and informal coordination exist between the learning units, although there is no centralized coordination of learning activities. In a formally coordinated learning function, distributed learning groups are managed with structured procedures and processes in place to coordinate efforts between the learning units. A federated model, such as this, can be represented as “business units having responsibility for their own training and are

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supported by a core team that manages some technology and corporate programs, … a shared services support unit may manage the learning technology infrastructure, set e-learning standards, establish uniform processes, and set program evaluation strategies” (Howard, 2006, p. 2). In a centralized corporate university, the learning functions are managed with strong centralized control (i.e., budgets, operational management) and coordination over most aspects of training and learning activities across the entire organization. The structure of a corporate university may be a contributing factor in the support of learning functions. According to the 2006 American Society for Training and Development State of the Industry Report, “standardization of the learning infrastructure, portfolio, and development process was identified as the most critical factor in successful global integration of the learning function,” but organizations continue to grapple with issues of administering global learning investments to cost and allocations (Rivera and Paradise, 2006, p. 15).

Stages of Development The development of organizations, the fourth dimension, can be classified into phases of growth impacted by factors such as age of the organization, size, and rate of change internal and external to the organization (Greiner, 1972). Depending on the current phase the organization, management would apply resources and efforts to different areas for encouraging creativity, management of controls and procedures, and deliberate collaboration and coordination. The stages of development of corporate universities, likewise, can be arranged as those institutions just starting to organize the corporate university function, those who have programs and operations running with participants beginning to recognize the benefit, those who are well established with many programs, processes, and procedures in place and well documented, and finally, those who are considered experts in the industry, defined by receiving industry awards and having frequent media citations and case study articles written about their corporate university.

Curriculum A goal of many corporate universities is to instill and communicate the company’s operations, values, and vision to all employees. This is operationalized through curriculum, the fifth dimension, by the corporate university. Similar to the role of academic universities that instill democratic values and national citizenship to its constituents, corporate universities perform the same function

Identifying and Classifying Corporate Universities

but are replacing this content with corporate values and cultural norms (Blass, 2001, 2005; Jarvis, 2001). Innovative human resources practices “are designed to improve organizational effectiveness by influencing employee attitudes and behaviors” (Tannenbaum and Dupuree-Bruno, 1994, p. 172). Common curriculum programs range in content from customer service, communication and team building, technical or business skills, and leadership capabilities. Curriculum programs can be designed for various competency-based job categories and career paths, instead of specific skills for a particular job. Learning on the job and through experiences is an essential element of learning as adults (Merriam and Caffarella, 1999). Kolb (1984) conceptualized that learning from experience occurs in phases: willingness to learn, observe, and reflect upon what occurred and what was learned. With this new insight, the learner can then plan for a different course of action and carry out the necessary effort. In many companies, programs such as job-rotations are developed with the goal of increasing the experiential learning of employees. Programs such as mentoring and coaching offer employees valuable insight and assistance from another, typically more experienced, individual. A coach or mentor can aid the employee in reflecting and learning from what occurred in the workplace and how to do things differently to improve within the context and culture of the work environment.

Learner Population Corporate universities vary in their program offerings and curriculum offered to different learner population, the sixth dimension. Corporate universities may design programs to target specific groups, such as new hire employees, existing employees, and executive management development (Storey, 2004). This is especially important given the predicted demographic shifts in the population, current skill gaps, and the resulting lack of managerial talent (Friga et al., 2003; Kranz, 2007). The focus of corporate university programs is typically limited to employees within the company as the primary audience, although some have extended this reach to suppliers, external partners, and customers (Meister, 1998). One such example is Toyota University. In addition to training other non-automotive businesses on its expertise of continuous improvement, Toyota University has worked with Los Angeles Police Department and the Defense Department. Disney University also enrolls students who are not employees, including customers, suppliers, and even the public.

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Evaluation and Measurement The seventh dimension, an important function for corporate universities, is the evaluation and measurement of learning programs. Training effectiveness and evaluation is a complex and difficult process for any organization to understand. Kirkpatrick’s four-level model of training evaluation appears to be one of the most widely used in practice today (Alliger and Janak, 1989; Morin and Renaud, 2004). The first two levels include measuring initial reactions and satisfaction of the learner (Level 1) and testing the skills and knowledge attained (Level 2). The higher, and more difficult, two levels of the Kirkpatrick model attempt to measure actual transfer of learning to the job (Level 3) and impact of learning to the business (Level 4). While traditional training departments typically measure the two lower levels of evaluation, corporate universities are attempting to increase learning evaluations to Level 3 application of learning on the job and Level 4 bottom line business impact. A 2002 American Society for Training and Development Industry Report found that most training organizations measure primarily Level 1 (78% of respondents) and Level 2 (32% of respondents) only. The more difficult levels to measure were found with less frequency (i.e, Level 3 with 19% of respondents and Level 4 with 7% of respondents). In a qualitative study of four corporate universities and their evaluation methods, Kirkpatrick’s Four Level Model was found to be the primary source in assessing effectiveness of their educational offerings (Allen, 1999). Using corporate and higher education’s principles of evaluation, the study offered more insight into evaluation frameworks that corporate universities use to measure their own effectiveness. In another study, training evaluation within corporate universities examined four corporate universities (Bober and Bartlett, 2004). Using a case study approach, the results identified corporate universities that used training evaluation data and how the data were used to improve or influence training programs.

Financing Sources The source of funding, the eighth dimension, influences the strategy and dayto-day operations of a corporate university. Historically, training department funds were allocated exclusively by corporate budgets. While many corporate universities are still funded by this method, another model has recently appeared. Many corporate universities are moving toward self-funded models

Identifying and Classifying Corporate Universities

or a “pay for service” strategy (Meister, 1998; Vanthournout et al., 2006). In essence, the corporate university operates as a profit center, similar to that of a product or service group. Business units are “charged” for learning services rendered and funds are reallocated via internal budget distributions. Corporate universities in this model must remain profitable and fund their own expenses or expansion, rather than solely depending on corporate funds. The financing of corporate universities in the learning marketplace continue to evolve with multiple practices demonstrated.

Technology Usage Significant changes in the delivery of learning programs are made possible with the evolution of technology in the workplace, the ninth dimension. In contrast to traditional training departments, corporate universities view multiple delivery methods of learning programs as a key aspect to their success (Anderson, 2003). Programs can be delivered in many different methods, such as, classroom, online via the internet, CD/DVD, video/VHS, pod-casts, web-casts, video-conferencing, etc. With the growth of online learning, organizations have been able to reduce training budgets and save money, while delivering training to more employees. Another benefit cited was the customization of content and delivery of training at point of need (Douglas, 2003). According to the 2006 American Society for Training and Development State of the Industry Report, approximately 40 percent of learning programs were delivered with the use of technology amongst Fortune 500 companies and public sector organizations. “E-learning has reached a high level of sophistication, both in terms of instructional development and the effective management of resources” (Rivera and Paradise, 2006, p. 4). Corporate universities can offer courses from academic universities through the company website to employees’ desktops (Pollitt, 2005), and “e-learning environments have the potential to support cognitive, social, motivational, and affective processes of learning” (Tynjala and Hakkinen, 2005, p. 330). One new and growing technology trend that is growing significantly in the learning industry is the use of learning management systems (LMS) to track, manage, and deliver learning programs to end-users. “A good learning management system (LMS) produces a practical environment in which learners can find the content they need, managers can develop their team to improve performance and the learning staff can evaluate training effectiveness” (Alvarado, 2007, p. 18). LMS applications give end users flexibility to manage their own

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training schedules, sign up for programs, and learn about upcoming mandatory or elective training sessions. The system also helps the organization track the participants of training sessions, manage and review costs of programs, and reduce administration overhead typically done by other personnel.

Partnership with Business Units Corporate universities tend to have high involvement with business leaders in determining learning requirements and programs for business units, whereas in the past, many training departments would make assessments and develop learning programs with little assistance or interaction with their business leaders. The tenth dimension, partnering with businesses units, is valuable to assessment, development, and evaluation of learning programs (Meister, 1998; O’Connor, Bronner, and Delaney, 2002). “Corporate learning functions must understand the business dynamics and propose how learning can drive significant improvements in revenue and speed to market” (Meister, 2006, p. 32). In aligning learning efforts, metrics of business values need to be taken into consideration. Business unit leaders are typically concerned with issues, such as, “what is the revenue generated per employee?,” “how long does it take for a new hire to achieve the desired level of competency?,” and “what are the customer service indicators like?” (Ellis, 2002). Corporate universities that do not align well with business needs may face the danger of becoming a bureaucratic organization with little connection to senior management strategies. The value and connection to the business must remain the core focus of corporate universities.

Partnership with Human Resources Management In addition to employee development, the Human Resources Department typically focuses on processes such as hiring, conducting annual performance reviews, managing employee benefits and payroll, and termination of personnel. Corporate universities focus exclusively on processes related to the training and learning development of employees. Supporting the eleventh dimension, a recent benchmarking survey of corporate universities (Todd, 2004) reported that corporate universities typically work closely with human resources counterparts to improve employee performance. For example, corporate universities may analyze employee development needs from the human resources competency management system to create new learning programs, or develop reward systems with human resources to recognize employee learning accomplishments.

Identifying and Classifying Corporate Universities

Corporate universities can also be viewed as a critical component to the development of human capital in an organization. Using an in-depth case study of one corporate university, researchers found that the corporate university’s goals were linked to the strategic objectives of the organization overall in order to sustain competitive advantages. To create competitive advantages, “the management and development of human resources can be linked to the deliberate promotion of corporate universities as a catalyst for strategic human resource development” (Holland and Pyman, 2006, p. 20).

Partnership with External Vendors/Outsourcing As the complexity of supporting the learning function has increased, corporate universities have realized that they cannot provide all services and programs alone. To be successful, corporate universities require the ability to develop and manage multiple relationships, internal and external, in order to successfully meet learning demands. Illustrating the twelfth dimension, many corporate universities outsource and partner with external vendors and institutions to bring content and delivery to learners to better serve the needs of their audience. Due to increasing focus on cost control and complex learning technologies in educating adults in the workforce, companies realize that in-house development and management alone are insufficient. Business units that require specialized training or expertise, such as leadership training or technical skills, may need to go to external vendors or programs (Storey, 2004). In fact, outsourcing needs for learning services are predicted to grow dramatically. “A recent study from IDC estimated the US learning outsourcing marketplace was approximately $1.3 billion in 2005 (approximately 7 percent of the marketplace). The number is expected to increase over the next four years to $3.3 billion or about 13 percent of the total learning marketplace” (Meister, 2006, p. 70). An example is Avaya University, which outsourced 1800 product, technical, and business courses to Accenture consulting company in a high-priced, multi-year contract (Oakes, 2003).

Partnership with Academia As the complexity and diversity of training requirements have increased, corporate universities have partnered with academic universities, the thirteenth dimension, to deliver the appropriate content to learners (Thompson, 2000). These partnerships have resulted in greater customization of content from academic universities (Meister, 2003) and specialized degree programs, such as

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the adapted MBA program from Indiana University to General Motors employees, or specialized technology training to learners from Motorola University China. Babson College has partnered with Intel Corporation to offer an online MBA program (Anderson, 2003). Faculty exchange programs are another way for corporate universities to partner with a academic institution (Blass, 2005).

3. CONCEPTUAL ANALYSIS FOR DEFINING THE CORPORATE UNIVERSITY Given the complexity and variety of these dimensions of corporate universities, no two corporate universities look exactly alike, thus making them difficult to define and identify. To reduce this complexity and attempt to define and operationalize the corporate university phenomenon, a conceptual look of the 13 dimensions is useful as grouping dimensions in a systematic manner can offer a descriptive lens that may help broaden our understanding of corporate universities in practice today. The following discussion will review existing literature of how learning functions are organized, and build upon this knowledge to present a new conceptual framework for defining corporate universities. Management development, including training, can be defined as “any process whereby managerial knowledge and skills are attained from non-credit programs or on-the-job experiences” (Keys and Wolfe, 1988, p. 205). Organizations that focus on management learning and development have three critical aspects—the content that includes the delivery of ideas, concepts, or skills, the experience that permits the learner to apply the content in appropriate context, and the feedback that the learner receives as a result of the content and experience application (Keys, 1977). Content delivery, not necessarily content creation, relates to issues of selection of target populations (i.e., executive development or line managers), the competency based programs or curriculum developed, and delivery mechanisms, including technology tools. Experience can be demonstrated by opportunities for learners to apply new content through case studies, simulations, on-the-job learning programs, mentoring, and other action learning techniques. Feedback is critical for the learner to understand the relationship between new content learning and the resulting performance. Assessment of the learner is a key part of the feedback dimension. These elements are similar to other learning models, such as Kolb’s learning model of concrete experience, reflective observation, conceptualization, and active experimentation.

Identifying and Classifying Corporate Universities

Prince and Stewart (2002) proposed a conceptual model for relating the processes of a corporate university. Based on concepts of knowledge management and organizational learning, a corporate university was defined as a learning system primarily concerned with four distinct processes. The first was knowledge systems and processes, which focused on the technology, databases, decision tools, other organization structures that support learning. Network and partnership processes related to the internal and external partnerships that a corporate university developed in support of learning needs. This element of a learning organization was crucial and “likely to increase as the trend to outsource training and development activities continues” (Prince and Stewart, 2002, p. 806). The third was people processes, which related to the ability for human resources management to enhance and execute learning processes with the goal of building shared meaning, culture, and skills across an organization. And last, the learning processes, which directed efforts at building a learning culture with programs, curriculum, and other training courses. These learning processes required commitment from leadership across the organization. The key function of a corporate university was the integration and coordination of these processes to support organizational learning. Building upon Prince and Stewart’s process model, a conceptual framework for defining corporate universities leads us to describe how the corporate university is organized and how it functions, which can provide an expansion to the definition of this emerging organizational form. For this view, the dimensions of corporate universities from the literature, research, and practice are grouped into four profile areas representing key organizational functions. The four profile areas, shown in Figure 1, are the organizational profile representing corporate university size, years in existence, structure, stage of development, governance and leadership, and their strategy and mission; learning delivery profile representing curriculum offered, target learner population, and evaluation of learning programs; operational profile consisting of technology usage in learning and financing sources; and, partnership profile representing relationships with business areas, human resources, external vendors, and academic institutions. Similar to other types of organizations, this framework provides a conceptual perspective in examining corporate universities. As an analogy, an organization focused on creating and selling a new product might have similar groupings in operations and functions. Instead of a learning delivery profile, the organization might have a product development profile, which would include

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Figure 1.  Conceptual framework for defining corporate universities

functions of research and development, product testing, and product manufacturing. The partnership profile for this product group might include functions of marketing and product distribution. Corporate universities may demonstrate greater knowledge and expertise in one or more profile areas, while other corporate universities may demonstrate expertise in multiple dimensions across several functional profiles. The functions of a corporate university grouped in this manner present a way to articulate the key attributes of a corporate university, and offers a sense of how they function and focus on their internal operations. Additionally, the conceptual framework suggests a foundational base and a systematic method to investigate, compare, and test different dimensions and profile areas across differing corporate universities.

Identifying and Classifying Corporate Universities

4. EMPIRICAL ANALYSIS FOR DEFINING THE CORPORATE UNIVERSITY These conceptual functional groupings assist in our understanding of what corporate universities do operationally; however in varying degrees, all corporate universities exhibit capabilities in any or all of the dimensions, across the four functional profiles. For the casual observer, it is not readily apparent which dimension may be more significant or has been adopted by a vast amount of corporate universities. For further in-depth examination, the following analysis highlights the dimensions that are significant in identifying corporate universities empirically. To analyze these dimensions empirically, factor analysis research was conducted by this author, Lui-Abel (2008), in her study of corporate universities. Factor analysis aids in data reduction by taking a wide set of variables and eliminating those with high correlations to result in a refined set of composite elements that still retain the essence of the original variables. In this case, the factor analysis identified and emphasized five significant key component factors that serve to define corporate universities, all of which are distillates from the foregoing discussion. They are: strategy and execution with HR, developing skills to support business needs, evaluation of learning, partnerships with academia, and the use of technology to support learning initiatives. The five component factors represent 70% of the variance from the numerous original variables and empirically identify corporate universities in practice today. The five component factors will be summarized further with corporate university examples provided as illustrations. Strategy and Execution with HR, the first factor, describes the overall corporate university’s strategy and ability to execute learning efforts with the Human Resources department in support of the learning function. This factor represents functions such as having a well-defined strategy for executing the company’s learning function; articulating a clear vision and mission for supporting learning performance in the organization; partnering with Corporate Human Resources to analyze employee development needs for new learning programs; and creating learning programs aligned with Corporate Human Resources talent performance appraisal processes. Nestle University, the food and chocolate company, worked closely with HR for key talent management initiatives the company had embarked on. To improve the leadership pipeline for the top 130 executives of the company, the corporate university, along with HR, implemented performance management

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processes, 360-degree reviews, and programs for succession planning. Having organizational processes in place for succession planning was viewed as a critical factor for the future success of the firm. The second factor, Developing Skills to Support Business Needs, emphasizes the collaboration with business units to focus on educating employees for specific job-related skills. Corporate universities working alongside business unit leaders help to identify those skills and knowledge that are the priority for the business unit’s function. This factor represents tasks, such as, providing skill-based and/or job-based programs customized for specific business units; providing competency-based curricula for entry-level employee learning; developing programs for specific employee groups; and working together with line managers to determine requirements and design learning programs. The machine manufacturing global firm, Ingersoll Rand University, worked closely with the learning governance to determine key learning initiatives that are aligned to specific business goals and skills. The learning governance board was comprised of the CEO, executive business leaders, HR leaders, high-potential senior business leaders, and the Ingersoll Rand University team. Together, they set directives for learning programs around business objectives of customer intimacy, product innovation, strategic marketing, and Lean Six Sigma for process improvement. Evaluation of Learning, the third factor, highlights the importance of measurement and evaluation of learning programs by corporate universities. The evaluation of learning programs continues to receive significant attention as companies allocate more resources to the learning function. Executives are demanding more “proof ” from the learning function that this allocation is well utilized (Bober and Bartlett, 2004; Philips and Philips, 2007). This factor looks at evaluating learning programs by measuring organizational-level results and/ or impact to the specific business units; evaluating learning programs by measuring a return-on-investment for learning efforts; and evaluating the transfer of learning to the job role/tasks at some point following the completion of learning programs. ManTech International Company, a software and support services company for US Government agencies, looks to measure financial and nonfinancial objectives for their learning initiatives. For example, the Chief Learning Officer developed a Return-On-Investment evaluation for every course that is delivered, which includes a post training evaluation 30 days later, by the employee to reflect upon the impact of training on the job. ManTech also measures cost savings of learning programs by improving coordination of

Identifying and Classifying Corporate Universities

training efforts and leveraging their purchasing power with vendors for course discounts. The fourth factor, Partnerships with Academia, stresses the need for corporate universities to supplement internal staff and their knowledge with external resources and expertise. Academic institutions are a likely source, especially for developing skills in specialized functions such as finance, accounting, technology, etc. Partnerships with academic institutions have grown in frequency (Meister, 2003) and many corporate universities now offer customized degrees available to employees, accredited by the academic institution (Anderson, 2003; Friga et al., 2003). This factor includes partnering with academic universities for customized design and/or delivery of non-credit learning programs, for credit and/or degree programs, and for faculty exchange and/or faculty development programs. One example of a corporate university and academia partnership is the relationship between insurance company, MassMutual University, and the University of Massachusetts-Amherst. All managed by the corporate university, the two institutions have developed innovative programs such as “Evening University” and “University Without Walls” that permit employees of MassMutual to attain degrees or learn new skills. Additionally, the relationship offers internships to current UMass-Amherst students, as well as corporate sponsorships for university arts and athletic programs. Finally, the fifth factor, Use of Technology to Support Learning, indicates the significant use of technology by corporate universities to extend the reach of their learning programs, especially across geographic locations (Douglas, 2003; Tynjala and Hakkinen, 2005). With the growth of online learning, organizations have been able to reduce training budgets and save money, while delivering training to more employees. Another benefit cited was the customization of content and delivery of training at the point of need (Douglas, 2003). This factor includes supporting learning programs via online (distance learning) technologies to employees and using a comprehensive learning management system to monitor, track, and administer learning programs. The technology firm, Sun, discovered significant gaps in their sales force skills, which related directly to the department’s performance. As a result, Sun Sales University realized the need for learning technologies to support their employee developmental efforts. One technology implemented was a learning management system to store, track, deliver, and report on learning activities by employees. A second technology adopted was a knowledge management

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platform used as a repository of key pieces of information, such as video recordings of successful sales presentations and how to maintain servers. These five empirically derived factors are key defining criteria for corporate universities. These factors can be used to distinguish corporate universities from other types of learning organizations. These factors identify differences between typical training departments and what corporate universities now allocate significant resources to. Managers of corporate universities can use these factors as criteria in developing their own learning strategy, and provide guidance on allocating resources. In specifying evaluation measurements per individual factor, managers can also assess their own performance over time in terms of operational efficiency of resource allocation and effectiveness of the learning function. For researchers, these component factors can be used to both measure and compare corporate universities in similar size or industry and over time.

5. CONCLUSIONS Future research can draw upon rich sources of organization theory, strategy, and management literature to expand our knowledge and effectiveness of corporate universities and compare their differences and similarities to other types of learning organizations. This chapter presented a number of views for identifying and defining corporate universities. The conceptual framework provides a basis for drawing upon existing research to examine corporate universities, and empirical analysis presents another perspective to identify specific factors as variables for further analysis of corporate universities. The discussion presented here provides “starting points” and can serve as a research base to developing our understanding of this evolving and exciting organizational form.

REFERENCES Allen, M. (1999). Assessing effectiveness in four corporate universities. Unpublished doctoral dissertation, University of Southern California. Alliger, G., and Janak, E. (1989). Kirkpatrick’s levels of training criteria: Thirty years later. Personnel Psychology, 42, 331–342. Alvarado, P. (2007, February). Effective business requirements for the LMS. Chief Learning Officer, 6, 18–21. Anderson, L. (2003, March 24). Collaboration, not rivalry, is best way ahead—corporate universities v business schools. Financial Times.

Identifying and Classifying Corporate Universities Blass, E. (2001). What’s in a name? A comparative study of the traditional public university and the corporate university. Human Resource Development International, 4 (2), 153–172. Blass, E. (2005). The rise and rise of the corporate university. Journal of European Industrial Training, 29 (1), 58–74. Bober, C., and Bartlett, K. (2004). The utilization of training program evaluation in corporate universities. Human Resource Development Quarterly, 15 (4), 363–388. Douglas, M. (2003). E-volution at corporate u. Learning and Training Innovations, 4 (1), 36–41. El-Tannir, A. (2002). The corporate university model for continuous learning, training and development. Education + Training, 44 (2), 76–81. Ellis, K. (2002, September 1). Corporate U’s: High value or hot air? Corporate universities come in all shapes and sizes, but only those that enable business objectives earn the highest marks from senior management. Training, 39. Friga, P., Bettis, R., and Sullivan, R. (2003). Changes in graduate management education and new business school strategies for the 21st century. Academy of Management Learning and Education, 2 (3), 233–249. Greiner, L. E. (1972). Evolution and revolution as organizations grow. Harvard Business Review, 50 (4), 37–46. Hilse, H., and Nicolai, A. (2004). Strategic learning in Germany’s largest companies. Journal of Management Development, 23 (4), 372–398. Holland, P., and Pyman, A. (2006). Corporate universities: A catalyst for strategic human resource development? Journal of European Industrial Training, 30 (1), 19–31. Howard, C. (2006). Striking a balance with shared learning services: Scotiabank establishes a federated system for global learning (Case Study). Oakland, CA: Bersin and Associates. Jarvis, P. (2001). Universities and corporate universities. London: Kogan Page Limited. Keys, B. (1977). The management of learning grid of management development. Academy of Management Review, 2 (1), 289–297. Keys, B., and Wolfe, J. (1988). Management education and development: current issues and emerging trends. Journal of Management, 14 (2), 205–229. Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice Hall. Kranz, G. (2007, June 11). Corporate universities getting refresher. Workforce Management, 21–25. Lui Abel, A. (2008). The development of a conceptual framework and taxonomy for defining and classifying corporate universities. Unpublished doctoral dissertation, New York University. Macpherson, A., Homan, G., and Wilkinson, K. (2005). The implementation and use of e-learning in the corporate university. Journal of Workplace Learning, 17 (1/2), 33–48. Meister, J. (1998). Corporate universities: Lessons in building a world-class work force (2nd ed.). New York: McGraw-Hill, Inc. Meister, J. (2001, February 9). The brave new world of corporate education. The Chronicle of Higher Education, B10. Meister, J. (2003, October). The latest in corporate-college partnerships. Training and Development, 53–58.

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Amy Lui Abel Meister, J. (2006, March). Corporate universities: What works and what doesn’t. Chief Learning Officer, 5, 28–33. Merriam, S., and Caffarella, R. (1999). Learning in adulthood. San Francisco, CA: Jossey-Bass Publishers. Morin, L., and Renaud, S. (2004). Participation in corporate university training: Its effect on individual job performance. Canadian Journal of Administrative Sciences, 21 (4), 295–306. Nixon, J., and Helms, M. (2002). Corporate universities vs higher education institutions. Industrial and Commercial Training, 34 (4), 144–150. Oakes, K. (2003, July 1). Will-e-learning be the catalyst for outsourcing? Training and Development, 57, 17–21. O’Connor, B. N., Bronner, M., and Delaney, C. (2007). Learning at work: How to support individual and organizational learning. Amherst, MA: HRD Press. Philips, J., and Philips, P. (2007). Next-generation evaluation. In M. Allen (ed.), The next generation of corporate universities. San Francisco, CA: John Wiley and Sons. Pollitt, D. (2005). Heineken toasts successful recipe for management training. Training and Management Development Methods, 19 (2), 13–15. Prince, C., and Stewart, J. (2002). Corporate universities—an analytical framework. Journal of Management Development, 21 (10), 794–811. Rademakers, M. (2005). Corporate universities: Driving force of knowledge innovation. The Journal of Workplace Learning, 17 (1/2), 130–136. Rivera, R., and Paradise, A. (2006). State of the industry: Trends in workplace learning and performance. Alexandria, VA: American Society for Training and Development. Shaw, S. (2005). The corporate university. Journal of European Industrial Training, 29 (1), 21–39. Storey, J. (2004). Leadership development through corporate universities. Training and Management Development Methods, 18 (4), 41–49. Tannenbaum, S., and Dupuree-Bruno, L. (1994). The relationship between organizational and environmental factors and the use of innovative human resource practices. Group and Organization Management, 19 (2), 171–202. Thompson, G. (2000). Unfulfilled prophecy: The evolution of corporate colleges. The Journal of Higher Education, 71 (3), 322–341. Todd, S. (2004). Corporate University Xchange sixth annual benchmarking report. New York, NY: Corporate University Xchange. Tynjala, P., and Hakkinen, P. (2005). E-learning at work: Theoretical underpinnings and pedagogical challenges. The Journal of Workplace Learning, 17 (5/6), 318–336. Vanthournout, D., Olson, K., Ceisel, J., White, A., Waddington, T., Barfield, T., Desai, S., and Mindrum, C. (2006). Return on learning. Evanston, IL: Agate Publishers.

CHAPTER 15

Business School Extended Learning: Perspectives on Non-Degree Executive Education—The Case of “Looking Good” versus “Being Good” STEVEN S. MEZZIO, PhD CPA Pace University

ABSTRACT

A

digital revolution is underway, characterized by a fusion of technologies,  transformation of business models and the blurring of traditional industry boundaries. To survive this disruption, organizations are rapidly retraining workers across geographic, generational, and sector boundaries. Business schools are playing a major role internationally in this skills transformation by operating autonomous profit centers that sell and deliver praxis-driven, androgogy-based extended learning. For example, the commercial market for business school-based non-degree executive education is so large and global in scope, it is profiled annually by the Financial Times in their ranking of global business school providers of non-degree executive education.

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At the same time, the market for vendors selling executive education to the workforce is in the midst of disruption, fueled in large measure by changing needs on what, how, and when clients want to learn, shrewd, and selective buyers pressuring price and quality, and low barriers to entry fueling competition. While the opportunities for business schools to sell executive education are compelling, such transformative changes in the marketplace challenge success. In this context, this study examines success factors associated with business schools that sell non-degree executive education to the workforce. Resource dependency theory, boundary theory and signaling theory were used as a unified lens to construct two primary dimensions of success dependencies: first, the role press rankings play in attracting new customers (that is, “looking good”). Second, the role quality management conditions at the executive education profit center-level plays in retaining existing customers (that is, “being good”). Findings suggest that business schools that achieve a high rank order in press rankings in executive education (that is, “looking good”) may not necessarily deliver higher quality training and client service (that is, “being good”), and vice versa. That is, actions that contribute to convincing a prospective customer to buy services for the first time, may differ from actions needed to retain the new customer as a long term customer. Focusing efforts on only one of these success dependencies may create an imbalance that threatens success.

INTRODUCTION Fourth Industrial Revolution technologies are truly disruptive—they upend existing ways of sensing, calculating, organizing, acting and delivering. They represent entirely new ways of creating value for organizations and citizens. They will, over time, transform all the systems we take for granted today—from the way we produce and transport goods and services, to the way we communicate, the way we collaborate, and the way we experience the world around us. Schwab et al., 2018, Foreword.

A Fourth Industrial Revolution is underway—a digital revolution characterized by a fusion of technologies, transformation of business models and the blurring—and in some cases, elimination—of traditional industry sector boundaries. In this context, organizations globally are trying to keep pace with the speed of change in products, services, enabling technologies, big data and

Business School Extended Learning

fickle customer and employee expectations. To survive this disruption, workplace skills and roles must also transform (Schwab et al., 2018; Weber and Feintzeig, 2018; Manyika et al., 2017). Organizations internationally are, therefore, prioritizing strategies to rapidly retrain and hire workers across geographic, generational, and industry sector boundaries. In this context, it is noteworthy to observe that corporate expenditures for workplace learning are substantial and growing dramatically. For example, According to Training Magazine’s 2017 Training Industry Report, expenditures for training in the United States for 2017 were estimated to have increased 32.5% over 2016 to $90.6 billion, with $7.5 billion associated with fees for vendors and products. Business schools are playing a major role in this skills transformation through the sale and delivery of praxis-driven, androgogy-based extended learning, such as the provision of non-degree executive education. For the purposes of this study, “business school-based non-degree executive education” is defined as business school profit centers responsible for marketing, selling, designing, and delivering short-term training for industry customers. The commercial market for business school sales of non-degree executive education is substantial and rapidly growing. For example, Harvard Business School (HBS) reported $176 million in revenue was earned from their non-degree executive education profit center, representing an approximate 5% increase from the prior year, and a whopping 23% of total HBS revenues for 2016. HBS executive education enrollment for 2016 was approximately 10,900 students (Nohria, 2016). While such compelling opportunities exist to sell executive education to the workforce, formidable challenges exist for some business schools. For example, a highly competitive landscape and dramatic changes in what, how, and when individual and corporations expect to learn. As a result, shrewd buyers are demanding high quality training programs targeted at solutions to real-world problems, exemplary customer service, and high returns on their investment in training. Attracting and retaining customers is therefore critical to the success of business school providers of non-degree executive education. Informed by this dynamic context, this study explored the factors influencing the success of international business school-based profit centers selling non-degree executive education to the workforce. Specifically, this study examined the differences between the factors that help to initially attract new customers, and factors that help to retain existing customers.

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CONTEXT The current dynamic state and historical context of the commercial market for business schools selling non-degree executive education set the stage for embarking upon this study.

The Commercialization of Higher Education Commercialization of higher education is a symptom of the widespread shift to an academic capitalist regime across US colleges and universities, wherein institutions exhibit increasingly market-based behavior, and the public good mission takes a backseat to revenues and market share. Kezar and Bernstein-Sierra, 2016.

A commercial ethos has emerged as a force in higher education, according to some scholars and pundits (Perkmann et al., 2015). Critics assert that since the 1980s, commercial forces have transformed faculty “know-how” and research into commercial products, such as university patents and corporate employee training. This transformation has been referred to as the commercialization of higher education (Plewa et al., 2013; Etzkowitz, 2003). Critics argue that this commercialization of higher education exploits the free flow of academic knowledge and threatens academic norms (Perkmann et al., 2013). Advocates believe that such commercial linkages between higher education and industry are critical contributors to economic innovation and growth, while at the same time contributing much needed supplemental funds to colleges and universities (Tuunainen, 2005). In this context, this study examines such commercial linkages between higher education and industry, with a focus on workforce training.

Commercial Linkages between Higher Education and Industry Commercial linkages between higher education and industry have existed for some time. Consider the ubiquitous sports drink Gatorade; it is estimated that the University of Florida (UF) has received more than $150 million in licensing royalties since it was first patented by UF in 1965 (Destler, 2008). What is new today, however, is the unprecedented diversity, size, global scope, and financial magnitude of such university commercial linkages with industry – transformed from informal, ad-hoc events into contractual, large-scale sales activities (Plewa

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et al., 2013). The Bayh-Dole Act of 1980 is often cited as the impetus of this dramatic escalation (Washburn, 2005). The United States faced economic problems during the 1970s, with particular competitive pressures from Japan. In response, the US government put policy measures in place to spur economic development. Cited as the centerpiece of these measures, the Bayh-Dole Act of 1980 gave universities, small businesses, and nonprofit firms—for the first-time—the right to own and patent inventions funded by grants or contracts from federal agencies (Perkins and Tierney, 2014). The Economist (2002) reacted with the following assertion, “More than anything, this single policy measure helped to reverse America’s precipitous slide into industrial irrelevance” (p. 3). The Bayh-Dole Act ushered in an era of unprecedented growth in intellectual property creation and university patenting revenue (Perkins et al., 2014). For example, university patenting grew over 1,000% between 1980 and 1999 (Sampat, 2006). The fees associated with such licenses can be substantial. For example, The Wall Street Journal (Clark, 2016) reported that Carnegie Mellon settled a patent dispute with a corporate licensee for $750 million. On the heels of this growth in university patenting, universities expanded the scope of their non-patent related commercial linkages with industry, selling a range of services to industry, such as proprietary rights to academic research and the sale of non-degree executive education (Brenneneraedts et al., 2006). See Appendix A for additional examples. As a result, in just 20 years following the enactment of the Bayh-Dole Act of 1980, non-patent university-industry commercial ventures, such as business school sales of non-degree executive education to industry has grown substantially (Agrawal and Henderson, 2002).

Business Schools Selling Non-Degree Executive Education to the Workforce The tuition for a two week course is about half of that of an entire year’s MB. Kirp, 2003, p. 139.

For the purposes of this study, business school-based non-degree executive education is defined as business school profit centers responsible for marketing, selling, designing, and delivering short-term training programs for industry customers. Such profit centers are generally structured as autonomous profit centers within a business school, as depicted by Figure 1.

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Market and Customers

Business School

Non-Degree Executive Education Profit Center

Figure 1.  Diagram of a business school selling non-degree executive education

Before 1980, a small cadre of schools sold non-degree executive education to corporations. By the early 2000s, these services generated approximately $800 million annually, and roughly 80% of the providers were business schools (Lloyd and Newkirk, 2011). Today, the commercial landscape in which business school-based nondegree executive education profit centers operate is rich with opportunities informed, in part, by the need for new skills in the digital economy. Business schools are also motivated to pursue the potentially substantial revenue opportunities associated with sales of executive education to supplement revenue from traditional degree granting programs (Kirp, 2003). As a result, a growing number of business schools internationally have established autonomous profit centers that sell and deliver praxis-driven, androgogy-based non-degree executive education. In fact, the demand for such training is global in scope, as profiled by the Financial Times annual ranking of global business school providers of non-degree executive education (see Appendix C). Importantly, the sale of non-degree executive education can potentially be a lucrative revenue-producing endeavor for individual business schools. Table 1 presents examples published in The Wall Street Journal (2008) of tuition ranging from $30,000 to $58,000 per student charged for training that only ranges in duration four to eight weeks (Glazer, 2008).

$30,000

$54,000

Dartmouth

Stanford

Evanston, IL

$39,000

$39,000

Northwestern

Univ. Chicago

Durham, NC

$43,000

Duke

Boston, MA

Stanford, CA

Hanover, NH

Chicago, IL

Philadelphia, PA

$58,000

$50,000

Harvard

Univ. of PA

Norwalk, CT

$44,500

Columbia

Location

Cost

School

6.5

3

6

4

4

5

8

4

Length (weeks)

5

6

5

5 to 6

6

6

6

6 to 7

Days/week

44

44

43

45

53

45

46

48

Median age

Table 1.  Examples of business school non-degree executive education tuition costs, 2008

12-15

13

22

15+

15+

21

20

17

Management experience (years)

% with an MBA

15%

11%

20%

23%

40%

21%

29%

30%

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THE COMMERCIAL MARKET FOR EXECUTIVE EDUCATION: OPPORTUNITIES, CHALLENGES AND SUCCESS The sophistication, adaptability, and, opportunities for alignment of corporate, universities and centers of excellence with the emerging specific needs of their corporate sponsors are beginning to outstrip the capabilities of many business schools to meet individual corporate client needs. Executive Core (2015). Future Trends in Business Education, p. 4.

Emerging trends and recent studies suggest that opportunities for robust international growth continue in the non-degree executive education sector. In this context, business schools possess a unique and compelling value proposition. Some schools also bring a legacy of success in the executive education market along with a recognized and trusted brand (such as, Harvard). At the same time, the market for vendors selling executive education to the workforce is in the midst of disruption and transformation. This disruption is fueled in large measure by changing needs on what, how, and when clients want to learn, shrewd and selective buyers pressuring price and quality, and low barriers to entry fueling competition. While the opportunities for business schools to sell executive education are compelling, such transformative changes in the marketplace challenge success—and even survival. Four major challenges are noteworthy. The first major challenge for business schools is driven by the voice of the customer, which is transforming the executive education market (Executive Core, 2015). Shrewd and selective buyers are demanding relevant, just-in-time solutions to real-world business problems, high quality programs and service and high returns on their financial investments in training. For example, buyers are emphasizing greater client intimacy to drive precise definitions of learning topics focused on solving real-world problems (action learning). Discerning buyers are also demanding measurable outcomes from learning interventions (for example, evidence of transfer of learning). Changes in demographics (such as the appearance of the millennial generation, the new diverse employee base, and the popularity of telecommuting) are also influencing the executive education market. Some of the answers to these changes are programs that offer learning anytime, anyplace, just in time (for example, mobile learning), and in short bursts (for example, nano-learning). The second major challenge for business schools is a highly competitive landscape crowded with a diverse range of executive education vendors

Business School Extended Learning

(Executive Core, 2015). Some of the competitors are traditional consultancy firms with large budgets, international reach, trusted brands and a deep bench of subject matter experts in peer-oriented learning networks. A case in point is seen in McKinsey Academy’s executive education value proposition, “Our combination of business and learning expertise uniquely positions us to support both private and public-sector clients.” In this context, discerning buyers of executive education are in a formidable position, demanding high quality, customized service, and high returns on their investments in executive education. The third challenge faced by business schools is pressure from key stakeholders to focus less on academic theory and more on relevant and practical business application needs. This pressure has fueled tension with respect to meeting the dual demands of business relevance and academic rigor. That is, some professors are expected to publish scholarly research, while at the same time align their curriculum and teaching to relevant business needs (Lloyd and Newkirk, 2011; Doh and Stumpf, 2007; Kirp, 2003). Such dual roles may create a conflict of commitment for some faculty (Kirp, 2003). Figure 2 presents a tongue-in-cheek depiction of this role conflict. The fourth challenge faced by business schools is managing the transformation necessary to respond to the aforementioned (and other) challenges. According to Executive Core’s 2015 report, Future Trends in Executive Education (Executive Core, 2015, p. 56), [w]e seem to be approaching a tipping point in many of these programs: either find the courage to dramatically shift how learning services are provided to a rapidly changing marketplace and meet or beat the competition; or be displaced by increasingly favored and powerful competitors and be relegated to a much more narrow purpose or mission, focused more on academic research, theory, topic-specific just-in-time learning, and occasional consulting contingent on achieving real business outcomes.

In summary, this context reveals emerging opportunities and formidable challenges to the success—and potentially the economic survival of business school profit enters selling non-degree executive education. This dynamic context inform a need for studies, such as this study, to better understand the factors influencing success in the domain of university-industry commercial ventures generally, and business school-based executive education profit centers, specifically.

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Figure 2.  Depiction of dual-role conflict (Perkmann and Salter, 2010)

PURPOSE OF THIS STUDY This study was conducted to explore factors influencing the success of international business school-based profit centers selling non-degree executive

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education to the workforce. The present chapter discusses the results of the investigation of the following research question from this study: are quality management conditions within a business school-based non-degree executive education profit center, associated with that same business school’s reputational prominence, as measured by press rankings in the field of non-degree executive education? The independent variable is a construct of the quality conditions of a business school’s profit center responsible for selling non-degree executive education to the workforce. This variable was measured using a quality management survey instrument (see Appendix B). The dependent variable is a construct of the reputational prominence of a business school in the field of non-degree executive education. This variable was measured by the published press ranking results of the Financial Times Top 50 Ranking of International Business School-Based Non-Degree Executive Education Programs, 2014 (see Appendix C).

“LOOKING GOOD” VERSUS “BEING GOOD” CONCEPTUAL LENS: SIGNALS OF QUALITY IN EXECUTIVE EDUCATION Most companies aspire to design goods and services that encourage repeat business. Yet businesses often invest in expensive features without adequately understanding how the features that attract new customers may differ from those that will retain existing ones. Hamilton et al., 2017, p. 79.

In the context of the purpose of this study, boundary theory, signaling theory, and resource-dependency theory were used in this study as a unified lens to construct and explore success factors associated with business schools that sell non-degree executive education to the workforce. Boundary theory explains the structure and roles of boundaries within organizations. For example, boundaries function as perimeters, protecting the organization from intrusion; as a demarcation, distinguishing one organization from another; and as an interface internally and externally (Yan and Louis, 1999). Boundary theory was used in this study to explain the structure of business schools operating non-degree executive education units and the boundary spanning commercial relationship between business schools and the workplace, as depicted by Figure 1.

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Signaling theory’s central proposition is that buyers look to pre-purchase signals of quality to inform perceptions of latent and unobservable qualities, reduce uncertainty, and inform buying decisions (Connelly et al., 2011). Spence (1973) applied signaling theory to labor markets, positing recruiters as buyers, job applicants as sellers, and resumes as pre-hiring signals of quality. Not until after hiring would the legitimacy of the resume be verified. Signaling theory was used in this study to explain how prospective customers would look to pre-purchase and post-purchase signals of quality to inform buying decisions associated with executive education programs. Resource dependency theory was formalized in a landmark study conducted by Pfeffer and Salancik (1978). It explains an organization’s dependencies on external resources for survival. Such dependencies affect behaviors and priorities (Hillman et al., 2009). Two propositions from resource dependence theory were used to explain variables associated with success. First, resource dependency theory was used to explain how attracting new customers is a resource that executive education profit centers depend upon for success. Second, resource dependency theory was used to explain how retaining existing customers in order to sell them additional services is a resource upon the executive education profit center also depends on for success. Perspective from resource dependency theory and signaling theory were then combined to posit the question of “success” as a construct emerging at the intersection of two important goals for business school administrators of non-degree executive education profit centers. The first goal is attracting new customers by achieving a prominent reputation in the field of executive education (that is, “looking good”). The second goal is retaining existing customers through the delivery of high-quality training and customer service (that is, “being good”). Some signals of quality attract new customers, while other signals of quality increase customer retention. The notion of “looking good” centers on a creating and sustaining a reputation that stands out as one of the best in a given field. Reputational prominence is generally informed by trusted and observable signals of legitimacy, expertise, trust, esteem, and exemplary know-how, as well as the ability to create greater value relative to competitors. Accordingly, potential buyers actively seek pre-purchase signals of reputational legitimacy to inform buying decisions. Such signals of quality are crucial to continuously attracting new customers in a market that is crowded with competitors and demanding buyers (Bowman and Bastedo, 2011; Connelly et al., 2011; Lloyd and Newkirk, 2011).

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Annual press rankings have been found to be strong, trusted signals of reputational quality and legitimacy that shape pre-purchase buying decisions ( Jeremic, Bulajic, Martic, and Radojicic, 2011). While prospective customers in the field of non-degree executive education expect to achieve a range of benefits, many rely on press rankings as primary signals of quality associated with reputational prominence (that is, “looking good”) in the marketplace. As a result, many business schools have posited such published press ranking as a quality-signal to the marketplace. See Figure 3 for an example of a business school’s profiling of their executive education ranking in their open-enrollment executive education programs.

Figure 3.  Adapted from UVA (2013).

Once prospective buyers are attracted and secured, retaining these customers becomes critical to the success of non-degree executive education profit centers. How best to do so? Some studies have found that department or profit center-level quality management, such as Total Quality Management (TQM), designed to deliver high-quality products and services are strongly and positively associated with customer satisfaction and retention (Corredor and Goñi, 2011). For the purposes of this study, “quality management” is defined as strategies, practices, and conditions designed to optimize product, service, and operating quality (Corredor and Goñi, 2011). The notion of “being good,” therefore, relies on continuously keeping customers satisfied with the quality of their education, service, and return on their investment in training. Satisfied customers are more likely to remain customers (Lloyd and Newkirk, 2011; Doh and Stumpf, 2007). In summary, boundary theory, signaling theory and resource dependency theory were used in this study as a unified lens to construct two primary

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dimensions of success factors associated with business schools that sell nondegree executive education to the workforce. The first success dimension is the role business school press rankings play in attracting new customers (that is, “looking good”). The second success dimension is the role quality management conditions at the executive education profit center-level play in retaining existing customers through the delivery of high-quality training and services (that is, “being good”). The notion is that to build a sustainable presence in this market you must not only attract and convince a customer to buy your services for the first time, but also deliver high-quality training and service to retain customers so they continue buy training programs.

RESEARCH DESIGN AND DATA ANALYSIS This was a quantitative correlational study, exploratory in nature, designed to illuminate the variables of interest concerning success, reputational prominence, and quality management. The primary research question investigated was, are quality management conditions within a business school-based non-degree executive education profit center associated with the same business school’s reputational prominence, as measured by press rankings in the field of non-degree executive education? The first construct of success used in this study is informed by quality management conditions associated with the design and delivery of programs and services within a business school’s non-degree executive education profit center (the independent variable). A previously validated survey instrument was used to gather data on quality management conditions in business-schoolbased non-degree executive education profit centers. See Appendix B for the survey. The second construct of success used in this study is associated with is the same business school’s press ranking of their non-degree executive education function (the dependent variable). This variable was measured using the results of the Financial Times ranking of the top fifty international providers of non-degree executive education for 2014. See Appendix C for the ranking results. Given that this exploratory study was designed with a purposive selection of a population of fifty business schools comprising the Financial Times ranking of the top fifty international providers of non-degree executive education for 2014, the result was a relatively small sample size. Consequently, establishing cause-and-effect inferences for observed patterns was not statistically feasible. Instead, a correlation method was used. Correlation design is appropriate to

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explore the degree of association between or among variables of interest (Creswell, 2003). From this cohort population, the sample size of respondents to the quality management survey administered in this study was approximately 44 percent of the population.

RESULTS Results from the survey indicated no statistical associations were indicated between quality management conditions in the survey responses at the business school non-degree executive education profit center-level, and the reputational prominence of that same business school in the field of non-degree executive education, based on the rank order reflected in the Financial Times ranking of the top fifty international providers of non-degree executive education for 2014. These results should be considered in the context of limitations in the methodology used. The aim of this study was to explore success constructs associated with a large international population of business schools selling nondegree executive education programs. In order to place boundaries around this large population, the primary and unique characteristic of interest for this study was a business school’s membership in a prominent cohort of best-in-class international business school providers of non-degree executive education. Accordingly, a purposive sampling method was used to define the population of interest for this study as the cohort of fifty business schools comprising the Financial Times top-fifty ranking of non-degree executive education programs for 2014. Smaller sample sizes may limit the generalizability and validity of results.

DISCUSSION AND IMPLICATIONS No statistical associations were indicated between a business school’s quality management conditions at the non-degree executive education work unit level (that is, “being good”), on the one hand, and the reputational prominence of that same business school in the field of non-degree executive education (that is, “looking good”), on the other hand. This result suggests that business schools that achieve a higher press ranking in non-degree executive education rankings (that is, “looking good”) may not necessarily reflect higher quality education programs and customer service conditions in their executive education profit center (that is, “being good”), and vice versa. One important factor influencing this lack of association is the existence of important differences between the criteria used to measure quality. That is,

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important differences exist between the ranking-criteria used by the Financial Times press rankings of business schools, and the criteria used to define, measure and weight constructs of quality in the standardized quality management survey used in this study. A closer look at each set of criterion sheds light on the major factors informing these important differences.

“Being Good”: Quality Management Success Criteria In line with prior studies, customer satisfaction has a consistent negative effect on churn (a positive effect on retention). Gustaffsson et al., 2005, p. 216.

In summary, important differences emerged in this study between traditional quality management perspectives on quality, on the one hand, and media press rankings perspectives on quality, on the other hand. Such differences are also at the center of a long-standing debate over the methods used to define and measure quality in criteria used in college press rankings. A closer look at the criteria used in the quality management survey instrument used in this study, and the criteria used by the Financial Times in their press rankings sheds light on the major factors informing these important differences. First, a look at the criteria used in the validated quality management survey instrument used in this study. This survey instrument was designed specifically to measure best-in-class categories of quality conditions that have been found to positively affect product and service quality in a range of industries, including higher education. The survey criteria are presented in Table 2. Table 2.  Categories of Quality Management Conditions and Criteria Categories Definition 1. Product/service quality Degree to which the department1 strives for accuracy, completeness, conformation, and innovation. 2. Financial effectiveness Degree to which the department receives a return on investment. 3. Operational efficiency Measure of how efficient the department is. 4. Public responsibility Degree to which the department is a steward of the environment. 5. Customer satisfaction Degree in which the department communicates with customers in order to maximize customer service. 6. Employee satisfaction Degree to which the employees in the department feel valued and enjoy their work.

1

For this study, “department” equals “profit center”.

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Favorable quality management conditions have been found to be strongly and positively associated with customer satisfaction and retention (Corredor and Goñi, 2011). In this context, criteria informing the survey instrument used in this study were designed to focus on products and service quality conditions that satisfy and retain existing customers (Grandzol and Gershon, 1998). Furthermore, these conditions tend to be behavioral, context-dependent and experienced-based; experienced by customers post-purchase after they receive the services.

“Looking Good”: Press Ranking Success Criteria The most telling criticism of the rankings are that the existing criteria are ill-chosen, incomplete, and arbitrarily weighted. Gioia and Corley, 2002, p. 117.

On the other hand, for the same business schools participating in the quality management survey, signals of their reputational prominence (that is, “looking good”) were measured by the rank that they achieved in the Financial Times 2014 rankings of top fifty non-degree executive education programs. This rank order was determined by the criteria created by the Financial Times (2014). The Financial Times criteria places substantial weight on factors associated with characteristics unique to the business school, as opposed to the educational programs (Ortmans, 2004). For example, the number of international locations the school has in place, faculty diversity, and the school’s international accreditation are emphasized. Additionally, the Financial Times (2014) categorizes executive education program offerings as strategic, general, or functional. These offerings—as opposed to the quality of training programs aimed at organizational strategy are very heavily weighted and have the greatest impact on ranking (Ortmans, 2014). These ranking criteria appear to be a mix of criteria associated at the business school-level (for example, number of international locations) and criteria associated at the training program and service quality levels. Higher education press rankings are generally perceived as legitimate measures of quality and prominence in a field of expertise and accurate measure of status hierarchy amongst business school competitors (for instance, MBA programs rankings). As a result, students and industry are likely to gravitate toward highly ranked business schools. As a result, press rankings have gained a foothold, wielding influence and reshaping the normative environment

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(Bastedo and Bowman, 2011). For example, some scholars assert that dependencies on press rankings have influenced changes in higher education solely to improve or maintain rank, at times to the detriment of curriculum, teaching and basic research (Bastedo and Bowman, 2011; Jeremic et al., 2011). Other studies raise questions as to whether press rankings are a true reflection of quality. Overall, since the first appearance of business school rankings in the 1980s, critics have argued that press rankings are merely reputational window dressing, not a legitimate, accurate, comprehensive measure of school quality. Some studies question the statistical validity of ranking methods, while others advance a scathing critique, arguing that rankings are misleading measures of quality that create a false sense of precision (Bastedo and Bowman, 2011).

Implications: “Looking Good” Versus “Being Good” Some features may be valuable because they attract new customers, while others are valuable because they retain existing customers. Hamilton et al., 2017, p. 80.

The results of this study provide some directional support for the assertion that important differences exists between the “looking good” versus “being good” propositions advanced by the conceptual framework used in this study. The notion of “looking good” is associated with continually attracting new customers by standing out in a crowd by signaling to the market a reputation as one of the best in the field of non-degree education. Press rankings play an important role in this process. “Being good” is associated with keeping existing customers happy so that they remain customers and buy additional training programs. Quality management conditions at the profit center-level play an important role in the process of “being good.” These differences have an impact on success. Therefore. acknowledging and attending to these differences is central to the success of business schoolbased profit centers selling non-degree executive education. As a consequence of these important differences in quality criteria used for press rankings versus profit center-level quality management criteria, business schools profit centers selling non-degree executive education must make choices as to how best to balance resource investments concerning quality. That is, how best to strike the right balance in investing limited resources to maximize the rank order achieved in press rankings to attract new customers (that is, “looking good”), while at

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the same time, improving profit-center-level quality management conditions to retain existing customers as repeat buyers (“being good”).

CONCLUSION The business learning market space for customized solutions is continuing to grow, the needs diversify, and the needs vary significantly by prospective client. In response to these needs, many business schools continue to lose competitively to professional services firms. Investment and change will likely be required for many. Executive Core (2015). Future Trends in Business Education, p. 2

A digital revolution is underway, characterized by a fusion of technologies, transformation of business models, and the blurring of traditional industry boundaries. To survive this disruption, organizations are rapidly retraining workers across geographic, generational and sector boundaries. Business schools are playing a major role internationally in this skills transformation by operating autonomous profit centers that sell and deliver praxis-driven, androgogy-based executive education. At the same time, the market for vendors selling executive education to the workforce is in the midst of disruption, fueled in large measure by changing needs on what, how, and when clients want to learn, shrewd and selective buyers pressuring price, return on investments in training. While the opportunities for business schools to sell executive education are compelling, such transformative changes in the marketplace challenge success. Administrators of business school-based non-degree executive education profit centers aspire to attract new customers from the workforce and retain existing customers. With the confluence of a highly competitive market with low barriers to entry, and shrewd and demanding customers, success depends on understanding how factors that contribute to attracting new customers (“looking good”) may differ from those that contribute to retaining existing customers (“being good”). The implications of this study suggest that business schools that overly emphasize their investments, resources, and promotional efforts on only one of these two success-dependencies (that is, “looking good” versus “being good”) may create an imbalance that threatens success and, potentially, the economic survival of business school-based non-degree executive education profit centers.

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REFERENCES Agrawal, A., and Henderson, R. (2002). Putting patents in context: Exploring knowledge transfer from MIT. Management Science, 48, 44–60. Bastedo, M. N., and Bowman, N. A. (2011). College rankings as an interorganizational dependency: Establishing the foundation for strategic and institutional accounts. Research in Higher Education, 52, 3–23. Bowman, N. A., and Bastedo, M. N. (2011). Anchoring effects in world university rankings: Exploring biases in reputation scores. Higher Education, 61, 431–444. Brennenraedts, R. M. F., Bekkers, R., and Verspagen, B. (2006). The different channels of universityindustry knowledge transfer: Empirical evidence from biomedical engineering. Unpublished manuscript. Clark, D. (2016, 17 February). Marvell to pay $750 million in settlement with Carnegie Mellon. The Wall Street Journal. Retrieved from http://www.wsj.com/articles/marvell-to-pay-750-million-in-settlement-with-carnegie-mellon-1455746246. Connelly, B. L., Certo, S. T., Ireland, R. D., and Reutzel, C. R. (2011). Signaling theory: A review and assessment. Journal of Management, 37, 39–67. Consortium, A. E. (2016, April 07). Future Trends in Business Education. Retrieved from https://www.uniconexed.org/content-hub/research-archives/. Accessed February 7, 2019. Corredor, P., and Goñi, S. (2011). TQM and performance: Is the relationship so obvious? Journal of Business Research, 64, 830–838. Creswell, J. W. (ed.) (2003). Research design: Qualitative, quantitative, and mixed methods approach (2nd ed.) Thousand Oaks, CA: Sage Publications. Destler, B. (2008). A new relationship. Nature, 453, 853–854. Doh, J. P., and Stumpf, S. A. (2007). Executive education: A view from the top. Academy of Management Learning and Education, 6, 388–400. Etzkowitz, H. (2003). Research groups as “quasi-firms”: The invention of the entrepreneurial university. Research Policy, 32, 109–121. Executive Core (reprinted 2015). Future Trends in Business Education, 1–64. Retrieved from https://www.uniconexed.org/future-trends-in-business-education/. Gioia, D. A., and Corley, K. G. (2002). Being Good Versus Looking Good: Business School Rankings and the Circean Transformation from Substance to Image. Academy of Management Learning and Education, 1 (1), 107–120. DOI:10.5465/amle.2002.7373729. Glazer, E. (2008, 30 September). It’s intense at the top. The Wall Street Journal. Retrieved from http://www.wsj.com/articles/SB122245005298479309. Gomes, J. F. S., Hurmelinna, P., Amaral, V., and Blomqvist, K. (2005). Managing relationships of the republic of science and the kingdom of industry. Journal of workplace learning, 17 (1), 88–98. Grandzol, J. R., and Gershon, M. (1998). A survey instrument for standardizing TQM modeling research. International Journal of Quality Science, 3, 80–105.

Business School Extended Learning Gustaffsson, A., Johnson, M., Roos, I., (2005). The Effects of Customer Satisfaction, Relationship Commitment Dimensions, and Triggers on Customer Retention. Journal of Marketing (October), 69 (4), 210–218. Hamilton, R. W., Trust, R. T., and Dev, C. S. (2017). Increase Customer Retention?—MITIndustry-Home. Retrieved from http://ilp.mit.edu/media/news_articles/smr/2017/58202. pdf. Accessed February 19, 2018. Hillman, A. J., Withers, M. C., and Collins, B. J. (2009). Resource dependence theory: A review. Journal of Management, 35, 1404–1427. Jeremic, V., Bulajic, M., Martic, M., and Radojicic, Z. (2011). A fresh approach to evaluating the academic ranking of world universities. Scientometrics, 87, 587–596. Kezar A., Bernstein-Sierra S. (2016) Commercialization of Higher Education. In T. Bretag (ed.), Handbook of Academic Integrity. New York: Springer. Kirp, D. L. (2003). Shakespeare, Einstein, and the bottom line: The marketing of higher education. Cambridge, MA: Harvard University Press. Lloyd, F. R., and Newkirk, D. (2011). University-Based Executive Education Markets and Trends. Unpublished manuscript. Retrieved from UNICON (University Consortium for Executive Education), http://192.185.166.193/2011/research/UNICON-whitepaper-markets-trendsLloyd-Newkirk-08-2011.pdf. Manyika, James, Lund, Susan; Chui, Michael, Bughin, Jacques, Woetzel, Jonathan, Batra, Paul, Ko, Ryan and Sanghvi, Saurabh (2017, November). What the future of work will mean for jobs, skills, and wages. Retrieved from https://www.mckinsey.com/global-themes/ future-of-organizations-and-work/what-the-future-of-work-will-mean-for-jobs-skills-andwages. Acessed February 15, 2018. McKinsey Academy (n.d.). Retrieved from https://www.mckinseyacademy.com. Accessed February 17, 2018. Nohria, N. (2016). From the Dean. HBS (Harvard Business School) Financial Report 2015. Retrieved from https://www.hbs.edu/about/annualreport/2016/Pages/default.aspx. Ortmans, L. (2014). How the executive education programme rankings were compiled. FT Business Education (May 12), 30–31. Perkins, J. F., and Tierney, W. G. (2014). The Bayh–Dole act, technology transfer and the public interest. Industry and Higher Education, 28, 143–151. Perkmann, M., Fini, R., Ross, J., Salter, A., Silvestri, C., and Tartari, V. (2015). Accounting for universities’ impact: Using augmented data to measure academic engagement and commercialization by academic scientists. Research Evaluation, 24, 380–391. Perkmann, M., and Salter, A. (2010). Entrepreneurial academics need support. Financial Times (December 20). Retrieved from http://www.ft.com/cms/s/2/9466629e-09fa-11e0-9bb400144feabdc0.html. Perkmann, M., Tartari, V., McKelvey, M., Autio, E., Broström, A., D’Este, P., Sobrero, M. (2013). Academic engagement and commercialisation: A review of the literature on university–industry relations. Research Policy, 42, 423–442. Retrieved from http://dx.doi.org/10.1016/ j.respol.2012.09.007.

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Steven S. Mezzio Plewa, C., Korff, N., Johnson, C., Macpherson, G., Baaken, T., and Rampersad, G. C. (2013). The evolution of university-industry linkages—A framework. Journal of Engineering and Technology Management, 30 (1), 21–44. Sampat, B. N. (2006). Patenting and US academic research in the 20th century: The world before Bayh-Dole. Research Policy, 35, 772. Spence, M. (1973). Job market signaling. The Quarterly Journal of Economics, 355–374. Schwab, K., Davis, Nicholas, D, and Nadella, S (2018). Shaping the Fourth Industrial Revolution. S.l.: World Economic Forum. The Economist (Technology Quarterly, Q4) (December 12, 2002). Opinion: Innovation’s golden goose. Retrieved from http://www.economist.com/node/1476653. Training Magazine (November 9, 2017). 2017 Training Industry Report. Retrieved from https:// trainingmag.com/trgmag-article/2017-training-industry-report. Accessed February 15, 2018. Tuunainen, J. (2005). Hybrid practices? Contributions to the debate on the mutation of science and university. Higher Education, 50, 275–298. UVA (2013). Retrieved from http://www.darden.virginia.edu/executive-education. Washburn, J. (2005). University, Inc.: The corporate corruption of higher education. New York: Basic Books. Weber, Lauren, and Feintzeig, Rachel (2018). To Fill Jobs in a Tight Labor Market, Employers May Need to Get Creative. Wall Street Journal (February 15). Retrieved from https:// www.wsj.com/articles/to-fill-jobs-in-a-tight-labor-market-employers-may-need-to-get-creative-1518616800\. Yan, A., and Louis, M. R. (1999). The migration of organizational functions to the work unit level: Buffering, spanning, and bringing up boundaries. Human Relations, 52, 25–47.

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APPENDIX A: NON-PATENT UNIVERSITY-INDUSTRY VENTURE EXAMPLES •  Examples of Non-Patent Ventures • Publications •  Participation: Conferences, Boards •  Mobility of People

•  Other informal Contacts/Networks •  Research and Development

•  Sharing Facilities •  Cooperation in Education and Training

•  Contract Research and Advertisement •  Spin-Offs and Entrepreneurship

Examples of Related Activities Scientific publications of companies Co-publications Consulting for publications Participation in conferences Participation in fairs Participation in governmental organizations Graduates:   mobility between knowledge institutes;  mobility from public knowledge institutes to industry Trainees | Double appointments  mobility from industry to public knowledge institutes; Temporary exchange of personnel Networks based on friendship Alumni Networks and Other boards Joint RandD projects Presentation of research (vice versa) Supervision of a trainee or PhD student Financing of PhD research Sponsoring of research Shared laboratories Common location or building (science parks) Purchase of prototypes (vice versa) Retraining of employees Influencing curriculum of university programs Contract education or training Providing scholarships Contract research Contract advisement Spin-oils Start ups Incubators at universities Stimulating entrepreneurship

Adapted from Brenneneraedts, Bekkers, and Verspagen, 2006.

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APPENDIX B: GRANDZOL AND GERSHON (1998) STANDARDIZED SURVEY FOR QUALITY MANAGEMENT RESEARCH USED IN THIS STUDY I. Demographic Information Your position in the organization:

( ) Manager (2nd level or above) ( ) Supervisor (1st level) ( ) Non-supervisory

II. Quality Management Outcome Measures Please respond to each of the following statements by marking 1 for “strongly disagree,” 2 for “disagree,” 3 for “somewhat disagree,” 4 for “somewhat agree,” 5 for “agree,” or 6 for “strongly agree,” or N for “not applicable,” Please respond to every statement. The following statements pertain to different Measures of Quality. While all statements may not always apply to a particular organization, most will. Please read each and every statement and then decide whether it applies to your organization and mark the appropriate response.

This set of statements is about “Product Service Quality” in your organization. Product service quality is the degree to which the organization strives for accuracy, completeness, conformance and innovation. 1. Our products/services usually have some kind of mistakes, defects, or errors. 2. Our products/services have all necessary parts, features, or elements. 3. Our products/services meet customers’ requirements. 4. This organization doesn’t develop new ideas or methods in its products/services.

This set of statements is about “Financial Effectiveness” in your organization. Financial effectiveness is the degree to which the organization receives a return on investment. 5. This organization’s return on investment reflects sound investments. 6. This organization’s market position enables it to resist losses to other organizations providing the same products/services. 7. This organization rarely reinvests in the processes it uses to provide products/services

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This set of statements is about “Operational Efficiency” in your organization. Operational efficiency is a measure of how efficient the organization is in its use of energy and material usage. 8. Productivity, in terms of yielding desired results, benefits, or profits, is continuously improving. 9. The amount of scrap or waste this organization produces, whether in material, time, or employees’ capabilities, is continually decreasing. 10. This organization wastes energy utilities, resulting in costs that are needlessly inflated. 11. The processes used in this organization are very efficient in terms of converting inputs (labor, data, raw material), into desired outputs (products/services). This set of statements is about “Public Responsibility” in your organization. Public responsibility is the degree to which the organization is considered a steward of the environment and a good neighbor. 12. This organization rarely receives notice of dissatisfaction, formal or otherwise, from government, industry, or local parties about its physical, chemical, or biological impact on the surrounding community. 13. This organization practices “good neighbor” relationships, participating in many community-enhancing activities. This set of statements is about “Customer Satisfaction” in your organization. Customer satisfaction is the degree to which your organization communicates with your customer in order to provide them with better service. 14. This organization doesn’t bother collecting information from its customers to measure their satisfaction. 15. Customer satisfaction results show improvement over time. 16. This organization lacks a process to provide satisfactory responses to customer inquiries. 17. This organization has processes in place to listen to and resolve customer complaints. This set of statements is about “Employee Satisfaction” in your organization. Employee satisfaction is the degree to which employees in your organization fell valued and enjoy their jobs.

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18. This organization has very low employee turnover, that is, most employees choose to remain here rather than work somewhere else. 19. Very few employees in this organization ask to be transferred from their present jobs because of dissatisfaction with their supervisors. 20. Absenteeism, that is, chronic absence from work, is high in this organization. 21. Employees file very few grievances/complaints against management in this organization. 22. This organization collects pertinent information from employees to measure their satisfaction 23. Employee satisfaction results show improvement over time. III. Please indicate your organization’s position on the following total quality scale. Mark ONLY ONE of the possible responses (A, B, C, D, or E). The list of characteristics under each response should help you determine the most accurate position for your organization. A. Short-term focus organization • Revenues and budgets are a higher priority than quality. • No mission about quality exists. • Little or no quality data are available or used. • Only skill-related, on-the-job training is provided for employees. • Quality of incoming materials is not controlled. • High incidence of scrap or rework exists. • Customer complaints are frequent. • Repeat business is relatively low. B. Product focus organization • Quality is viewed as “meeting specifications.” • Statistical analysis is used very little or not at all. • Strategic quality plan is short-term (less than 2 years). • Employee involvement in quality activities is selective. • Training is limited to skills. • Quality indicators for products are tracked. • Some customer complaints still exist. • Senior executives only meet key customers.

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C. Product and service focus organization • Some statistical analysis is performed. • Financial, product, and product quality plans are long-term. • Job-related and basic-quality training is available for all employees. • Supplier qualification and certification programs exists. • Production processes are statistically controlled. • Periodic customer surveys determine expectations. • Customer complaints are rare. • Senior executives meet many customers, but sporadically. D. Process or system focus organization • Widespread internal and some external quality data exist. • Effective long and short-term quality plans are based on benchmarking. • Cross-functional quality teams are functioning. • Considerable quality training is available for all employees. • Analytical design tools are used consistently. • Quality indicators are driven by customer requirements. • Senior executives drive customer partnering. • Continual, real-time customer input is sought. E. Continuous improvement focus organization • Employees are completely empowered to fulfill the organization’s quality mission. • The organization’s quality mission is totally customer driven. • Expanded partnering exists with all key suppliers. • Continuous improvement and optimization of all processes is occurring. • The total organization is experiencing world-class total quality results. • Customer needs and services are anticipated. • Products and services are benchmarked again.

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APPENDIX C: FINANCIAL TIMES RANKING OF NON-DEGREE EXECUTIVE EDUCATION: THE TOP FIFTY SCHOOLS IN 20142  EXECUTIVE EDUCATION The top 50 schools in 2014 Rank

School

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. 47. 48. 49. 50.

HEC Paris Iese Business School IMD Center for Creative Leadership Esade Business School University of Chicago: Booth Standford Graduate School of Business London Business School Harvard Business School Insead University of Virginia: Darden Cranfield School of Management Thunderbird School of Global Management Unversity of Oxford: Said Essec Business School Washington University: Olin University of Michigan: Ross Northwestern University: Kellogg SDA Bocconi University of Pennsylvania: Wharton Funda�āo Dom Cabral IE Business School Ashridge UCLA: Anderson University of Toronto: Rotman Columbia Business School ESMT - European School of Mgt and Technology Western University: Ivey Ceibs Edhec Business School MIT: Sloan University of St Gallen Stockholm School of Economics Vlerick Business School Henley Business School Universidad de los Andes Melbourne Business School, Mt Eliza IAE Business School Insper EMLyon Business School York University: Schulich University of Pretoria, Gibs ESCP Europe Incae Business School Catolica-Lisbon School of Business and Economics Xiamen University School of Management Australian School of Business (AGSM) Aalto University NHH Eada Business School Barcelona

Custom rank 2 3 5 4 6 15 8 9 18 21 32 7 22 23 25 24 33 28 11 26 27 14 16 36 42 37 51 45 34 19 31 43 29 38 50 47 40 39 52 41 57 53 56 55 61 46 59 54 71 66

Opon rank 3 6 1 9 9 2 8 13 6 5 3 26 14 15 12 17 11 16 31 19 23 35 33 20 20 25 18 22 29 46 30 27 37 36 31 34 43 47 38 50 39 42 41 43 40 53 50 52 45 57

Footnotes This table is compiled from the scores underlying the Financial Times Executive Education 2014 open enrolment and custom rankings, rather than the printed rankings. Schools must feature in both rankings to qualify for this table. Both sets of data are given equal weight, but the overall result is therefore not equal to the average of the two printed figures for each school.

FT.COM/BUSINESSEDUCATION



2 Retrieved from: http://im.ft-static.com/content/images/dc40a4f2-d6b7-11e3-b25100144feabdc0.pdf.

Closing Thoughts: Sustainability SABRA E. BROCK, PhD Touro College PETER J. MCALINEY, PhD Montclair State University

E

ducation is a process of building skills, changing minds, and creating pathways that make more fulfilling lives. PhD programs especially focus on training students to be disciplined scholars who will create knowledge and communicate it not just through teaching but also in writing and publishing. This collection of articles, covering research conducted during nearly two decades by PhD graduates of the NYU Business Education program, shows great diversity in not just what is taught, but how it is taught. Some of the key points made are the following. • Collaboration between teachers, which can develop into co-teaching and co-writing, showed to widen knowledge of resources and development of new project and assignments. • An active learning environment (including student presentations, simulations and game play, peer feedback, development of on-line portfolios, use of media resources, reflective writing exercises, engagement in class discussions, and group work) can produce higher exam scores and course satisfaction levels as well as negate any student learning style biases. • Pre-departure cultural competency preparation for East Asian students studying in the United States increases initial semester adjustment more than after-arrival training and reduces the feeling of being alone in a foreign land without knowledge or friends.

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• Financial literacy training and support consisting of a freshman personal finance course, advice from financial counselors, infusing financial literacy into freshman orientation, financial literacy workshops in collaboration with local businesses, engaging students to promote financial literacy to their peers, adding financial education to the college website, and a fund to assist students encountering financial emergencies, is proposed as a means to reduce the increasing stress students feel from needing to work full-time while in school, using credit cards or private loans instead of government student loans for tuition and other educational expenses. • The emotional journey of a woman through the glass ceiling includes stresses but in net is largely positive. Creating more ways to build confidence in young girls and women may increase the numbers of women embarking on this pathway and succeeding. • Successful teams require good communication among members, specifically, effective listening, effective raising of conflict and its resolution, as well as debate, discussion, flexibility, trust, and cohesiveness, as well as knowing each other’s strengths and weaknesses and giving credit. • Corporate universities go through five prominent processes: alignment and execution, developing skills that support business needs, using technology to support the learning function, learning and performance evaluation, and partnership with academia. • A digital social awareness game can increase not just knowledge but also interest in learning more about the social issue covered. • Applying new ideas from classes to the workplace is difficult even among students with high job involvement and strong career planning. Strong social/family support decreases stress in this transition, as does learning experiences where students are active and have more control. Academic learning allows more personal risk taking than corporate training. • Students can support the transition between their higher education experience and into the workforce through the creation of a portfolio of their work. This serves as a tool for the student to view their education reflectively from a meta-perspective and to inform potential employers about what skills and capabilities they can bring to a role through the use of concrete, topical examples that were developed in coursework. • The distinction between degreed master’s programs and professional education has become less clear. Institutions that wish to successfully

Closing Thoughts: Sustainabilit

address the professional education market may initially attract participants as a result of their established brand, but they also need to deliver quality learning experiences as well. The needs of students in professional programs and requirements to deliver these programs are different than delivering traditional degree programs. Institutions looking to serve this market have to make conscious resource allocation decisions. Throughout these chapters, some common themes emerge. • An active learning environment has intrinsic learning value. • It is important to deliver education at a specific time in a student’s life. • As students’ lives become more complex and stressed, support systems are key. • Effective educational process takes steps. • Women continue to increase their role in the workplace. • Needs and expectations of students are changing significantly; teaching and learning practices must adapt. • Needs and expectations of the workplace are altering dramatically; teaching and learning practices must adapt. Understanding the use of technology is important for business success. The authors raise concerns about the current state of higher education, some of which are reflected in the following list. • Delivering education through the lens of traditional higher education will not yield the results that businesses will demand of graduating students. • The possession of “soft skills” cannot be assumed—higher education must explicitly address introduction and training in these skill areas. • Learners have to be advised early in their education—before they arrive on the doorstep of higher education institutions—that in order to be successful, they must look at education not from a transactional perspective (that is, earning a bachelor’s degree and/or master’s degree that defines a terminal educational accomplishment), but rather from a lifelong learning perspective. • As technology plays an ever-increasing role in both higher education and the workplace, adequate resources need to be allocated to assure that learners understand its role and consequently how they can use it.

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All being said, there is a sense of optimism amid dramatic changes in workforce demand, the changing demographics of students and teachers, and the rapid availability of new educational technologies, as seen below. • As generation Z starts to dominate in the higher education student body, their greater ease and skill in technology will further close the gap of technology’s promise in supporting education. • There will be continued advances in learning technologies, including contributions from artificial intelligence and virtual reality. • Increasing globalization and increased translation capabilities will create new ways for students from across the world to learn with and from each other while staying in their home location. • The learning environment will be characterized by greater integration of the formal academic learning environment and the workplace through the increased presence of cooperative learning partnerships between higher education and business. • The academy will become more diverse, better reflecting the underlying demographics of the student population, as more minority students enter the academic workforce. The question of sustainability is how far the influence of these scholars will radiate out to their students and readers. There is an intrinsic paradox: while business infrequently looks to academia for direction, it depends on colleges to train the next generations of workers. It is hoped that by seeing the richness of insights and the patterns emerging, these scholars and their readers and students will be inspired to continue the quest.

Authors’ Biographies Amy Lui Abel, PhD is managing director of human capital at The Conference Board and leads research efforts focusing on leadership development, human capital analytics, organizational learning, talent management, diversity and inclusion, executive coaching, human resources, and employee engagement. Abel was previously a director of leadership development with Morgan Stanley, supporting high-potential senior leaders globally. She has also held roles at Accenture, Adobe Systems, and JPMorgan Chase, and led a private consulting organization performance practice. Abel was recently published in The Handbook of Coaching in Organizations by CCL, People + Strategy Journal, The Handbook of Workplace Learning by Sage Publications, Human Resources Development Quarterly Journal, and ATD’s T+D (Training and Development) Magazine. She holds several degrees, including a PhD from New York University, in information technology, business education, and organizational learning and performance. Ellen Bartley, PhD CMA is currently an assistant professor of accounting at Farmingdale State College, in the State University of New York system. Prior to beginning at Farmingdale, she taught at St. Joseph’s College in Patchogue, New York for twelve years. She has taught introductory, intermediate, and managerial accounting. She earned her PhD in higher and post-secondary education at New York University in 2016. She is a Certified Management Accountant and a member of the Institute for Management Accountants. She is also a member of the American Accounting Association, where she participates in the Teaching, Learning, and Curriculum section, as well as serves as Secretary/Treasurer for the Gender Issues and Worklife Balance section of the association. Prior to entering academia, Dr. Bartley held management accounting positions at International Business Machines Corporation. William (Bill) Black, PhD CPA is a professor of accounting at Raritan Valley Community College in Branchburg, New Jersey. Prior to his tenure in academia,

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Bill held various professional positions in the private sector for companies including Schering-Plough and Lever Brothers and was an internal auditor at the accounting firm of Price Waterhouse Coopers. Bill earned his PhD in Business Education at New York University in 2008. Bill’s research interests include comparing learning styles of practicing accountants in various geographic regions including mainland China, Hong Kong, and the United States. Sabra Brock, PhD has been Interim Dean at the Touro Graduate Business School since 2012 and taught at Touro since receiving her PhD in business education from New York University in 2007. Dr. Brock has published widely in scholarly journals. Her book, At the Intersection of Communication, Marketing, and Transformation, was published by the Touro Press in 2013. She is now completing a study of the emotional journeys of female CEOs in the US and Mainland China. She also writes self-help books on gender relationships with Men Head East Women Turn Right translated to five languages. Prior to entering academia Dr. Brock held global leadership positions at Citicorp, ColgatePalmolive, DuPont, and Young & Rubicam. Robert G. Brookshire, PhD is a Professor in the Integrated Information Technology Department at the University of South Carolina, Columbia, SC. He is the director of the Master of Health Information Technology program. He holds an AB from the University of Georgia, an MEd from Georgia State University, and a PhD from Emory University. He has taught at New York University, North Texas State University, the University of Virginia, and James Madison University. He is the co-author of Using Microcomputers for Research (Sage Publications, 1985), and his articles have appeared in the Journal of Computer Information Systems, BYTE, Social Science Computer Review, Legislative Studies Quarterly, The European Journal of Operational Research, and other journals. He is past president of the Organizational Systems Research Association and editor of the Information Technology, Learning, and Performance Journal from 2001 to 2011. Judy Caouette, PhD earned a PhD in Business Education from New York University in 1995. While studying, she was also teaching at Pace University in the School of Computer Science and Information Systems. Dr. Caouette became tenure-track faculty in 1995 and received tenure and promotion in 2000. In 2001 she moved to London with her husband where for five years she studied interior and gardening design at the KLC School of Design in Chelsea Harbour as well as English and European Art and Antiques at London’s Sotheby’s School

Authors’ Biographies

of Art. Following London they moved to San Francisco and began planning and building their home and garden in Carmel, California, where she resides today. Rob Cordova, MS is an in-demand educator across the world, known for transforming corporate learning into dynamic, impactful experiences. Since receiving his master’s in business education from New York University in 2007, Rob accelerated his training career in such heavily regulated industries as pharmaceuticals, energy, and financial services. He maintains an impressive portfolio of Fortune 100 clients by bringing his passion and expertise to his practical, accessible, and unboring learning solutions. In addition to his corporate work, Rob currently teaches the Innovation and Resilience course for Gabelli School of Business at Fordham University in New York City. Enrollment in his mixed-delivery format class has tripled in size, and he was nominated for Fordham’s 2017 Beacon Exemplar Award. Kara Hobbs (Lybarger), BA has a bachelor’s degree in liberal arts from Murray State University and a master’s degree in art history from the University of South Carolina. Her work experience is primarily in the nonprofit sector with a focus on fundraising, grants administration, community outreach, and volunteer management. She currently serves as Fund Development Executive Director for Texas CASA (Court Appointed Special Advocates) in Austin, Texas. Lynn Bacon Keane, PhD is a business and technology educator with twentyfive years’ experience teaching computer applications, social media, business education, instructional technology, and information technology training courses. She has taught in a variety of higher education institutions including Lehman College and Pace University in New York, at the University of South Carolina (Columbia) where she was also supervised candidates for teachers of business education degrees, and currently teaches at Grossmont-Cuyamaca Community College District and Palomar College. Her research interests include social media, professional development, community learning, service learning, online learning, emerging technology, and open source technology. Daniel Basil Kerr, PhD CPA is an intercultural solutions consultant. He partners with leading organizations and universities to develop cultural competence and inclusive work and study environments. Dan is a CPA (New York) and holds a master’s degree in Accounting from the CW Post School of

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Accountancy and a PhD in Business Education/Cultural Studies from New York University. He is also an adjunct faculty member at the College of Business at Stony Brook University where he pioneered the design and delivery of Financial Accounting on a “blended basis” (combining live and virtual classroom) within the MBA program. Chunhui Ma, PhD has lived and worked in three countries (China, Canada, and the United States). Her experience includes higher education program management, professional training and development, cross-cultural communication training and consulting, media events coordination, and teaching. Chunhui worked as the director of EMBA program in International Leadership at Roosevelt University, Chicago. Most recently, Chunhui was the director of the training program at China Center, University of Minnesota, Minneapolis. Bilingual in English and Mandarin Chinese, Chunhui has liaised between North American and Chinese cultures in various positions. Chunhui did her undergraduate study in China. She holds a MA in anthropology from Ball State University, an MBA from University of Toronto, and a PhD in higher education administration from New York University. Tara Madden-Dent, PhD designs higher educational programs that foster cross-cultural and academic adjustment skills in students preparing for international study. As Director of Global Programs at Sierra Nevada College, Dr. Madden-Dent manages an array of international services but is known for developing study abroad readiness courses and transitional courses to aid with post arrival integration at the high school and university level. Central to her work and research is the advancement of credit-based coursework that empower students to navigate diverse school and community environments, increase intercultural communication skills, and foster global leaders. Peter J. McAliney, PhD is currently Executive Director of Continuing and Professional Education at Montclair State University. He has informed his academic research agenda and teaching practices with his early experience in the private sector working in a variety of functional roles in private sector organizations and subsequently as a management consultant to C-level executives in industries such as professional services, banking, insurance, consumer goods, entertainment, pharmaceutical, energy, and transportation. He is the co-author of Painless Project Management (Wiley, 2007). His current research focus is on identifying those skills and competencies that educators need to impart on

Authors’ Biographies

workers as they enter the Fourth Industrial Age, characterized by artificial intelligence, robotics, and the Internet of Things. Kevin E. McEvoy, PhD has been on the Marketing Department faculty at the University of Connecticut since 2004. He received his PhD from New York University in 2010 and his MBA in Marketing from Boston College. His dissertation, Creating A Learning Environment: A Case Study of an Innovative Marketing Internship Program, was awarded Best Dissertation by the American Education Research Association Workplace Learning Special Interest Group. He has been awarded numerous distinctions for teaching and teaching innovation, and was named a Teaching Scholar in 2010 by University of Connecticut Institute of Teaching and Learning. His pre-academic professional experience includes marketing and sales management positions within divisions of General Foods, Colgate-Palmolive, Campbell Soup, Pillsbury and several entrepreneurial organizations. He has also consulted at a number of other Fortune 500 companies. Steven S. Mezzio, PhD CPA is a former Partner with PwC, and is currently an educator, practitioner, speaker, and influencer in the fields of Public Accounting, Governance, Higher Education, and Workplace Learning. He received his PhD in Education and Workplace Learning from New York University and currently serves as an Associate Professor of Accounting for Pace University and as Director of the Business School’s Center for Excellence in Financial Reporting. He is a National Instructor, AICPA COSO Internal Control Certificate Program and is a Certificate Program Developer in Data Analytics for the NYU School of Professional Studies. He is on the AICPA Journal of Accountancy Editorial Advisory Board, is President of the Board of Trustees for the NYSSCPA Foundation for Accounting Education, is an Audit Committee Advisor for the Ovarian Cancer Research Fund, and is on the Community Board of Advisors Member of PBS Channel Thirteen. He is a frequent speaker, including a Symposium on Sustainability Development Goals (SDGs) at Columbia University and the NYSSCPA series titled Voices of the Profession. Bridget N. O’Connor, PhD is Professor of Higher Education and Business Education in the Steinhardt School of Culture, Education, and Human Development at New York University, where she teaches courses including higher education curriculum development and workplace learning. She is co-editor of Learning and Teaching in Higher Education (Sage Publications, September

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2016) and The Sage Handbook of Workplace Learning (Sage Publications, 2011). She has coauthored six college-level textbooks related to end-user computing and corporate education. She is a past chair of the AERA SIG Workplace Learning. She has consulted for JetBlue Airways and has taught in the Penn Executive Doctorate Program for Chief Learning Officers. In 2006, she was a Fulbright Senior Specialist at Victoria University in Melbourne, Australia. Sharon Rowlands is CEO and President of Web.com. She was President at USA Today Marketing Solutions and also CEO of ReachLocal. Prior to this, she has been CEO of Altegrity, a risk analytics company, Penton Media, and Thomson Financial. Her experience in business spans thirty years with an emphasis on transformations and change management. She was educated in the UK. Nancy Burns Sardone, PhD received her PhD in Business Education from New York University in 2008. She has taught at Georgian Court University since that time and served as department chair. Dr. Sardone has presented to international audiences and published in international scholarly journals on topics related to technology integration in the teaching and learning process that includes game-based learning, assistive technologies, and ePortfolio development. She has also conducted research on college students’ development of IT fluency and written an experience-based article on co-teaching in the college classroom. She teaches courses in instructional design and instructional technology for inclusive classrooms.

Index AACSB. See Association to Advance Collegiate Schools of Business ACADEMIA, partnership, 259–260 active learning, 67, 69–70, 73, 81, 83–85, 235, 246, 297, 299 adult learning experiences, 223–247 analysis of covariance (ANCOVA), 77–80 Arden, Elizabeth, 45 Ash, Mary Kay, 45 Association to Advance Collegiate Schools of Business, 36 Bandura, perceived self-efficacy, 209 Bartley, Ellen, 1–15, 18–22 Bay, Josephine, 45 Bayh-Dole Act of 1980, 273 Black, William (Bill), 23–33 boundary theory, 270, 279, 281 Brock, Sabra, 44–56, 94–101, 104–106, 297 Brookshire, Robert G., 162, 175 budgets (budgeting/budget skills), 23, 25, 27–30, 33, 252, 254, 256–257, 265, 277, 294 CAI. See computer-aided instruction Canfield’s Learning Style Inventory, 73 Caouette, Judy, 107–128, 132–136 CCSSE. See Community College Survey of Student Engagement

CGPA. See cumulative grade point average Chief Learning Officer (CLO), 253 class discussions, 81–82, 84–85, 144, 297 CLO. See Chief Learning Officer co-teaching, 297 co-writing, 297 Collaborative Technology (CT), 108, 109 college administrators, 23–24 college students, 7, 13, 23–28, 30–32, 62, 65, 149 communication skills, 140, 143–144, 180–18 Community College Survey of Student Engagement (CCSSE), 24 computer support for cooperative work (CSCW), 108 computer-aided instruction (CAI), 163 computer-supported collaborative learning (CSCL), 165 constructivism, 66–67 constructivist learning, 63, 66–68, 76–77, 82–84 consumer protection, 27 content relevance, 225–226, 247 Cordova, Rob, 223–247 corporate universities, US, 250–266 COI. See cultural orientation indicator credit card, 25, 29

308

Index CSCL. See computer-supported collaborative learning CSCW. See computer support for cooperative work C-Suites, 44, 49 CT. See collaborative technology cultural competency, 140–141, 297 cultural knowledge, 137–138, 140–145 Cultural Orientation Indicator (COI), 141 cultural transition (East Asian undergraduate students), 137–146 cumulative grade point average (CGPA), 71, 75 Departmental Final Exam Scores, 72, 74, 76 development coding sheet, 133 digital revolution, 270, 287. See also technology Dunn Learning Styles Model, 73 ECAR. See EduCause Center for Applied Research EduCause Center for Applied Research (ECAR), 65 e-learning, 163–164, 166–167, 169, 171, 173, 204, 254, 257 electronic meetings systems (EMS), 108 ELT. See experiential learning theory EMS. See electronic meetings systems Evaluation of Teaching Effectiveness Scale, 72–75, 81, 92–93 experiential learning theory (ELT), 183 explorative learning, 67 Felder-Soloman Index of Learning Styles, 73 female CEOs, 46–49, 56 female leaders, 44, 47, 49, 51, 53–56 female leadership, 44–56

financial aid, 23, 25, 28–33 financial education. See financial literacy financial literacy, 23–33, 298 financial pressures, 24 FIRO. See Fundamental Interpersonal Relations Orientation first accounting course, 1–21 Fundamental Interpersonal Relations Orientation (FIRO), 97 game play, 81, 84–85, 150, 155–156, 158, 297 game-based learning, nuclear awareness, 148–159 GDSS. See group decision support systems GMAC See Graduate Management Admission Council Gorbachev, Mikhail, 151 Perestroika: New Thinking for our Country and the World, 159 governmental agencies, 23–24 Graduate Management Admission Council (GMAC), 201 group decision support systems (GDSS), 108 group support systems (GSS), 108–126 group work, 69, 70–71, 81–82, 84–85, 236, 240, 246, 297 GSS. See group support systems Harvard Business School (HBS), 271 HBS. See Harvard Business School higher education, 24, 27, 63–65, 67, 69, 74, 84, 140, 182–183, 226, 234, 284–286 commercialization, 272–273 current state, 299 IT curriculum development, 64 Hobbs, Kara (Lybarger), 162 Holt, Josephine, 45

Index IMI. See intrinsic motivation inventory information technology (IT), 62, 63, 84, 164–165, 197, 226 definition, 63 fluency, 62–72 IPOS cycle. See Input-ProcessingOutput-Storage Institute for College Access and Success, 25 Institutional Review Board (IRB), 9 instructional methods, 67–70, 81, 83, 152, 235 intention to transfer, 201–218 TPB’s relevance, 204–206 interns, learning and productivity, 179–197 life style, 182–183 organization and university’s role, 195 organizational affordances, 185–186 skill development, 184 themes, 189–193 work environment and marketing skills, 194 intrinsic motivation inventory (IMI), 148, 153 IPOS cycle (Input-Processing-OutputStorage), 85 IRB. See Institutional Review Board IT. See information technology job involvement, 224–227, 298 Jumpstart Coalition for Personal Financial Literacy, 25–26 Keane, Lynn Bacon, 162 Kerr, Daniel Basil, 137–146 KLSI. See Kolb’s Learning Style Inventory knowledge, skills, and abilities (KSAs), 96 Knox, Rose, 45

Kolb Learning Styles Inventory, 72–73, 75–76, 85 KR-20. See Kuder-Richardson 20 KSAs. See knowledge, skills, and abilities K-12, 27, 149, 153 Kuder-Richardson 20 (KR-20), 74 Lauder, Estée, 45 learner characteristics, 70–72, 74–75, 84, 183 questionnaire, 76, 78–80, 93 transfer of learning, 225–226 learning environments, 3, 62–63, 66–68, 70, 76, 84 learning management systems (LMS), 257 learning style, 39, 70–81, 83–86 learning technology, 254 LMS. See learning management systems Lui Abel, Amy, 249–250, 263 Ma, Chunhui, 200–218 macro plan, 132 Madden–Dent, Tara, 137–146 MANCOVA. See multivariate analysis of covariance marketing, 36–39, 41, 169, 180–181, 184, 186–190, 193–194, 197, 229, 243, 262, 264, 273 mathematical ability, 70–72, 74–79 cumulative grade point average (CGPA), 71 SAT score, 71 mathematical background, 10, 12–13, 66, 70–80, 231 MBTI. See Myers-Briggs Type Indicator McAliney, Peter J., 94, 297 media resource, 44, 46, 50, 52–53, 56, 64, 68, 73, 81–82, 84–85, 90, 92, 164, 254, 284, 297 McEvoy, Kevin E., 36–41, 179–197 Mezzio, Steven S., 269–287

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Index micro plan, 132 multivariate analysis of covariance (MANCOVA), 77 Myers-Briggs Type Indicator (MBTI), 97 Myers-Briggs’ Type Inventory, 73 Nation at Risk report, 67 non-degree executive education adapted from UVA (2013), 281 commercial linkages, 272–273 concept, 279–282 dual-role conflict, 278 quality management, 284 success criteria, 285–286 tuition costs, 275 non-patent university-industry venture, examples, 273, 291 Obama administration, 27–28 O’Connor, Bridget N., 107–128, 132–136, 223–247 on-line portfolios, 297 Peace Doves, 149, 151, 153–159 peer feedback, 81–82, 84–85, 297 personal relevance, 225–226 Pinkham, Lydia, 45 players, 70, 150–152, 154, 156, 195, 201 policymakers, 23–24 President’s Advisory Council on Financial Literacy, 26–27, 32 private loans, 25, 32, 298 problem-solving, 67, 81, 152, 180, 182 productivity, 95, 108, 111, 115, 117, 124–126, 135, 179, 293 quality management, 292–295 questionnaire, 50, 74–76, 99–100, 104, 212–214, 228 quizzes, 2, 11, 19–20, 22, 81–82

reflective writing exercise, 84–85, 297 research adult learning, 227–244 challenges in studying abroad, 140–144 corporate university, 263–266 on female leadership, 45–55 game-based learning, 153–159 group support system, 114–116 interns, learning and productivity, 186–189 IT fluency, 72–83 quality management, 282–287, 292 teamwork skills, 99–101 TPB based model, 212–215 virtual learning, 167–171 research questions adult learning, 227 female leadership, 49 first accounting course, 10–12, 22 game-based learning, 153 group support system, 116–117 interns, learning and productivity, 186 IT fluency, 71–72 resource dependency theory, 270, 279–281 role models, 55, 138 Rowlands, Sharon, 44–56, 60 Rubenstein, Helena, 45 Sardone, Nancy Burns, 62–86, 92, 148–159 saving, 27, 30, 33 scholars, 23–24, 272, 286, 297, 300 self-efficacy, 86, 172, 174, 178, 185, 205, 209–210, 226, 246 signaling theory, 270, 279–281 simulation, 68, 85, 173, 175 small and medium enterprises (SMEs), 169

Index SMEs. See small and medium enterprises social awareness, 148–150, 153–154, 156–159, 298 social awareness games, 149–151, 159 soft skills, 181, 187, 191, 201, 206–211, 216, 218, 241, 299 software, 52–53, 63–70, 76, 85, 109, 149, 156, 168–169, 170, 172, 229, 264 Southeast Community College, 30 Southwestern Oregon Community College, 30 stress, 2, 11, 48–49, 139–140, 142–143, 173, 224, 298 student loan, 25, 29 student presentation, 27, 39, 123, 181, 187–188, 190, 237–238, 291 student training, key points, 297–300 Students In Free Enterprise (SIFE), 29 students’ learning experiences, 4–5. See also first accounting course teaching environment effectiveness scale, 92–93 first accounting course, 4 team building, 52, 52, 103, 107, 111, 121, 130, 201, 255 team development, 110, 112–114, 117, 119, 122–127 team leaders, 122, 127 team meetings interview guide questions, 134–136 technology, impact on, 134–136 teamwork skills, 94–106 scoring table, 106 usefulness, 96 teamwork skills, 94–97, 99, 101, 104, 179, 187, 200–218 technology computer, 62, 65, 113, 162, 164 fusion of, 269–270, 287 usage, 252, 257–258, 261

theory of planned behavior (TPB), 202, 204, 215–216 determinants, 214 interventions, 217–218 questionnaire construction guidelines and examples, 212 theory-based model, teamwork skills, 200–218 Thomas-Kilmann Conflict Mode (TKI), 97 time management, 2, 11, 13, 19–20, 22, 69 toolbox current need for, 36–37 effectiveness, 40–41 flexibility, adaptability and potential limitations, 41 introduction, 37–38 marketing education and practice, 36–41 model, 43 overview, 36 showcasing, 39 value and effectiveness, 39–40 working, 38–39 top fifty schools, executive education 2014, 296 Total Quality Management (TQM), 281 TPB. See theory of planned behavior traditional environment, 66, 68, 77, 79, 81–82 trainees, 172, 205, 207, 209–210, 215, 217–218, 251, 291 training programs, 162, 205, 207, 216–218, 226, 253, 256, 271, 282, 285–286 transfer of learning, 184, 200, 204–205, 207, 209, 225, 226, 256, 264, 276 transitions, initial, 141–142, 144–145 transmission model theory, 67 Tuckman, B

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Index inclusion of conflict, 101 team stages, 99, 107, 110 group study, 110–111, 116 undergraduate students, 8, 25, 37, 63, 65, 70–71, 72, 137, 141, 153 United States Government Accountability Office, 26 University of Arizona, 28, 33 University of Florida (UF), 272 University of Hawaii, 29 University of North Texas, 29 US culture, 134–135, 137–138 US Department of Education, 24 US Department of Labor, 64 virtual workplace learning benefits, 165–167 challenges, 167–171 description, 163–165 success factors, 171–174

WADOBEs, 45 Westchester Community College, 30 Wilcoxon Matched-Pairs Signed-Rank test, 157 women, 44–50, 53–59. See also female leaders workers, 64, 96, 168, 171–172 workforce. See also virtual learning diversity in, 165, 167, 174 employability, 252 executive education, non-degree, 270–271, 274, 276, 278–279, 282 new educational technologies, impact on, 300 productive, 96 skilled, 64 training, 272 workplace support, 233–235 writing exercise, 19, 21, 69, 81, 84–85, 99, 108, 123, 180, 231, 233, 238, 297