Working together to create life-long learning and individual and organizational success

Quality Approachesin Education

Working together to create life-long learning and individual and organizational success

Vol. 8, No. 2 • September 2017

Editor Elizabeth A. Cudney QAEJournal@gmail.com

Copy Editor Janet Jacobsen janetjake@msn.com

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Founding Editor Deborah Hopen

©2017 by ASQ

Quality Approaches in Education (ISSN 2471-1462) is a peer-reviewed publication that is published by ASQ’s Education Division, the Global Voice of Quality, and networks on quality in education. The purpose of the journal is to engage the education community in a discussion of significant topics related to improving quality and identifying best practices in education and workforce development; and expanding the literature specific to quality in education topics.

Quality Approaches in Education grants permission to requestors desiring to cite content and/or make copies of articles provided that the journal is cited; for example, Source: Quality Approaches in Education, Year, Vol. 8, (No. 1), http://asq.org/edu/quality-information/journals/

Questions about this publication should be directed to ASQ’s Education Division, Dr. Elizabeth A. Cudney, QAEJournal@gmail.com. Publication of any article should not be deemed as an endorsement by ASQ or the ASQ Education Division.

The Journal That Connects Quality and Education

@asq.org/edu

IN THIS ISSUE:Note From the Editor 2Elizabeth A. Cudney

Resolving Stakeholder Challenges in the Higher Education System 4Godson A. Tetteh

Structured Creativity for Strategy Development – An Empirical Test of Effectiveness of Template Use in MBA Strategy Classes 16Raghu Tadepalli and Ravi Chinta

A Lean Six Sigma Approach for Improving Utilization of Walk-In Tutors 24Sandra Furterer, Kellie Schneider, Michael B. Key, and Yusheng Zhang

Exploring the Role of Information Technology Leadership in Higher Education: Implications for Total Quality Management 34Louis Hickman and Mesut Akdere

Collaborative Initiatives in Higher Education: A Case Study of Economics Programs 39Casey Abington

2 Quality Approaches in Education Vol. 8, No. 2

asq.org/edu

Quality Approachesin Education

Note From the EditorElizabeth A. Cudney

As education continues to evolve and increase in complex-ity, the case for understanding the customer becomes greater. In addition, the need to create strategic relationships and improve internal operations becomes paramount. This issue highlights methods to capture the voice of the customer, understand leadership roles, create collaborative initiatives, and improve processes within and across education.

This issue is comprised of five articles that illustrate the necessity of continuing to drive quality and continuous improvement throughout all aspects of education. The first article, by Godson Tetteh, addresses the application of the Kano model to understand the voice of the customer (student) and other stakeholders in higher education while also resolving conflicts between the major stakeholders. The research uses a novel approach to incorporate the perspectives from each of the major stakeholder groups including academic leaders, administrators, teachers, and students. The next article by Raghu Tadepalli and Ravi Chinta employs directed learn-ing through the use of templates that guide the development of strategic options. The research assesses the impact on learning outcomes in strategy-options development proj-ects as part of an MBA program. The third article by Sandra Furterer, Kellie Schneider, Michael Key, and Yusheng Zhang applies Lean Six Sigma to improve the utilization of tutors and create a more efficient and effective tutoring center at a university. The case study follows the Define-Measure-Analyze-Improve-Control methodology and provides a framework for conducting similar projects in other areas of education. The next article by Louis Hickman and Mesut Akdere addresses the cross-departmental impact of infor-mation technology leadership on quality initiatives. As continuous improvement projects are implemented, information technology leadership is in a unique position to provide cross-departmental vision to design the most appropriate solutions across a higher educa-tion institution. The final article by Casey Abington introduces an innovative approach to collaboration in higher education for low-enrollment majors, particularly as state budgets are shrinking. By developing a collaborative approach to teaching economics courses across three universities, students are able to access additional faculty and have added opportuni-ties for networking while the universities operate more efficiently.

These five articles illustrate the breadth of quality in education – from gathering and analyzing the voice of the customers to improving learning in the classroom and class projects to innovative collaborative approaches. Quality tools can be used strategically throughout all facets of education from the classroom to campus-wide initiatives.

Elizabeth A. Cudney, Ph.D. is an associate professor in the Engineering Management and Systems Engineering Department at Missouri University of Science and Technology. In 2014, Cudney was elected an ASEM Fellow. In 2013, Cudney was elected as an ASQ Fellow. She was inducted into the ASQ International Academy for Quality in 2010. She received the 2008 ASQ A.V. Feigenbaum Medal and the 2006 SME Outstanding Young Manufacturing Engineering Award. Cudney has published six books and more than 65 journal papers. She holds eight ASQ certifications, which include ASQ Certified Quality Engineer, Manager of Quality/Operational Excellence, and Certified Six Sigma Black Belt, amongst others. Contact her at cudney@mst.edu.

Elizabeth A. Cudney

Associate Editors

Theodore T. Allen, Ph.D., The Ohio State University

Jiju Antony, Ph.D., Heriot Watt University

Ardith Beitel, The Boeing Company

Morgan C. Benton, Ph.D., James Madison University

Marianne Di Pierro, Ph.D., Western Michigan University

Sandra Furterer, Ph.D., University of Dayton

Jamison V. Kovach, Ph.D., University of Houston

J. Jay Marino, Ed.D., Antioch School District

David C. Markward, Ed.D., Iowa Instructional Rounds Network

Henk Mulders, Expertis, The Netherlands

Nicole M. Radziwill, Ph.D., James Madison University

William J. Schell, Ph.D., Montana State University

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Editorial Review Board

Anthony Afful-Dadzie, Ph.D., University of Ghana

Yosef Allam, Ph.D., Embry-Riddle Aeronautical University

Sharnnia Artis, Ph.D., University of California, Irvine

Xuedong (David) Ding, Ph.D., University of Wisconsin-Stout

Julie Furst-Bowe, Ed.D., Chippewa Valley Technical College

Richard Galant, Ph.D., Educational Consultant

Cathy Hall, Ph.D., East Carolina University

Noah Kasraie, Ed.D., University of the Incarnate Word

Kathleen Lynch, Ph.D., Walden University

Leonard Perry, Ph.D., University of San Diego

Michael Schraeder, Ph.D., Troy University

Philip Strong, Ph.D., Michigan State University

Priyavrat Thareja, Ph.D., Rayat Institute of Engineering and Information Technology

Education Division’s Advancing the STEM Agenda BookA collection of conference papers from the 2011 Advancing the STEM Agenda Conference. Available through ASQ Quality Press.

This publication is full of collaborative models, best practices, and advice for teachers, higher education faculty, and human resources personnel on improving the student retention (and thereby increasing the supply of STEM workers). Ideas that will work for both STEM and non-STEM fields are presented. The introduction maps out the current landscape of STEM education and compares the United States to other countries. The last chapter is the conference chairs’ summary of what was

learned from the conference and working with 36 authors to develop this book. This effort is part of a grassroots effort among educators to help more students be successful in STEM majors and careers.

“Veenstra, Padró, and Furst-Bowe provide a huge contribution to the field of STEM education. We all know the statistics and of the huge need in the area of STEM students and education, but what has been missing are application and success stories backed by research and modeling. The editors have successfully contributed to our need by focusing on collaborative models, building the K-12 pipeline, showing what works at the collegiate level, connecting across gender issues, and illustrating workforce and innovative ideas.”

John J. Jasinski, Ph.D. President, Northwest Missouri State University

“Advancing the STEM Agenda provides a broad set of current perspectives that will contribute in many ways to advancing the understanding and enhancement of education in science, education, and engineering. This work is packed with insights from experienced educators from K-12, regional, and research university perspectives and bridges the transition from education to workplace.”

John Dew, Ed.D. Senior Vice Chancellor, Troy University

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Quality Approachesin Education FOCUS AREA:

HIGHER EDUCATION

Identifying

conflicts between

the expectations

of the major

stakeholders in

higher education

institutions

Resolving Stakeholder Challenges in the Higher Education SystemGodson A. Tetteh

AbstractThe purpose of this article is to study how to resolve conflicts among major stakehold-ers using the Kano model so as to improve the quality of higher education. The research presented in this article was part of an action research study. The empirical material was collected by various methods (face-to-face interviews and an electronic survey) in private and public higher education institutions in Accra, Ghana. The respondents included aca-demic leaders, administrators, teachers, and students. The study shows that incorporating a view of major stakeholder expectations in a Kano model could help resolve conflicts and prioritize stakeholder needs. The outcome could help higher education administrators improve existing planning processes, resolve needs and critical-to-quality characteristics of other major stakeholders, and provide some social benefits. This article expounds on applying the Kano model based on major stakeholder expectations in the higher education system to achieve quality. While a number of papers have been published on the applica-tions of the Kano model, none have used the model to resolve conflicts among the major stakeholders in the higher education system. This approach appears to overcome a gap that was identified in earlier research.

KeywordsHigher Education Quality, Kano Model, Stakeholder Expectations, Stakeholder Conflict Resolution

IntroductionThe concept of this research began when the author conducted an exit interview with

a former rector of a higher education institution (HEI) regarding some management chal-lenges during his tenure. The rector is the chief executive officer of an HEI and a member of the council of governors. The exit interview focused on the belief that HEI stakeholders held diverse needs or expectations on quality higher education (Pham and Starkey, 2016). Scholars have disagreed about the definition of quality in terms of the HEIs (Sunder, 2016; UNESCO, 2014). In addition, higher education administrators (HEAs) face a daunting task with persistent demands for rigorous academic quality standards and the necessity of meeting all the needs or expectations of the major stakeholders. Stakeholder (or customer) satisfaction from the conceptual framework in quality management is the leading criterion for determining the quality of the product/service offered (Ganguli and Roy, 2011; Pizam, Shapoval, and Ellis, 2016; Vavra, 1997, 2002). Thus, the HEA is accountable to the major stakeholders to achieve quality.

Previous research shows that as the number of stakeholders increases, there is a likeli-hood of disagreement on the definition of quality of education as well as miscommunication of expectations and priorities (Kreps, 1990; Finch, 1994; Hatami, Rangraz, and Jahromi, 2016). An effective HEA must build consensus with the major stakeholders to improve the quality of higher education (HE). Nevertheless, difficulties in changing the organizational culture and the absence of tools create substantial obstacles in improving the quality of HE (Luxford, Safran, and Delbanco, 2011). To overcome these difficulties, one needs a tool

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that supports an understanding of the major stakeholder needs and expectations (Mazur, 2003).

The exit interview with the former rector revealed that HEAs experience challenges in the process of transforming their insti-tutions, with opposing forces and major stakeholders having competing interests (Mabokela, 2002). What are the needs and preferences of the major stakeholders within the HEIs? What tools are available to address these stakeholder needs and prefer-ences? What are the challenges in implementing some of these tools? This study uses an action research approach to answer these questions.

Literature ReviewIn order to conduct a comprehensive literature review and

understand the challenges, HE stakeholders must be identified. Freeman (1984) defined a stakeholder as “any group or indi-vidual who can affect or is affected by the achievement of an institution’s purpose.” From this definition a stakeholder can be a single person or a group, who can influence, or is influenced by, the achievement of the institutions’ goals and objectives. Kumar, Rahman, and Kazmi (2016) suggested an approach to identify and classify stakeholders in order to recognize the major stakeholders who affect or are affected during the achievement of organizational objectives. Kumar et al. (2016) proposed four categories or classes of stakeholders: economic, social, environ-mental, and regulatory. For an organization, Friedman and Miles (2006) proposed the major stakeholders as customers, employees, local communities, suppliers and distributors, share-holders, media, the public in general, future generations, past generations, academics, competitors, non-governmental organi-zations, activists, trade unions or trade associations, financiers, government, regulators, and policymakers. According to Asiyai (2015), the major stakeholders in HE are made up of internal stakeholders such as the HE governing council, HEAs, students, teachers, and other staff members. External stakeholders include non-governmental organizations, community-based organiza-tions, government oversight commissions, parents, employers of labor, trade unions, the alumni association, industries/firms, HE competitors, development agencies both local and interna-tional, and society as a whole. The expectations by the various HE stakeholders are provided in detail next.

HE Governing CouncilNational governments that own public HEIs are represented

by a governing council. This council performs numerous roles including defining strategic vision, policy formulation, and monitoring to ensure continuous improvement in the quality of HE (Asiyai, 2015). The governing council in private HEIs

performs a similar role. Usman (2014) posits that an effective policy-making decision requires an enlightened governing coun-cil that has a broad view of the impact of HE on society and is cognizant of the strategic direction in terms of quality.

The fundamental purpose of HE policymakers and their expectations is to develop the knowledge and skills that students need for professional, technical, and managerial positions. Brint and Clofter (2016) posit that HE has expanded from an elite to a mass system, and policymakers have taken an interest as well in whether HE opportunities are fairly distributed and accessible to all. Notwithstanding, Goldin and Katz (2008) argued that HE accessibility is an important measure of social mobility to bring greater equality to society. Policymakers have also focused on the volume and quality of HE’s production of basic and applied researchers, who will become the next generation of scholars and scientists (Cole, 2009).

Finally, policymakers would want to expand HE to ensure that human capital development can meet the changing occupa-tional needs of an increasingly knowledge-based society. Thus, Brint and Clofter (2016) suggest the following questions for assessing the quality of HE to meet stakeholders’ expectations: Are students being prepared adequately for the labor market? Is the system accessible to students from all backgrounds? How large are the gaps in success between students from different backgrounds? Is research productivity high and is it contribut-ing to human well-being? Are HEIs producing well-prepared graduate students? Are the new business methods contributing to greater quality and effectiveness in the allocation of resources? Has the emphasis on interdisciplinary collaboration led to a greater capacity to tackle key national problems? How much are students learning? To what extent are the new instructional prac-tices and technologies contributing to student learning?

Higher Education Administrator (HEA)Most HEAs focus on global ranking and accreditation

institutions to determine the quality of HE. According to Sunder (2016), the expectations of HEAs include increases in enrollment, global ranking, number of research papers pub-lished per department, quality of research, HEI maintenance and infrastructure metrics, standard of teaching, reduction in students’ absenteeism, and effectiveness of accreditation pro-cess, among others.

StudentsHEIs’ vision and mission statements focus on the students in

order to provide quality education and create an enabling envi-ronment for students to succeed. Several studies have defined students as the primary customers in HEIs (Gruber, Reppel,

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and Voss, 2010; Mergen, Grant, and Widrick, 2000; Wallace, 1999), and teachers, administrative staff and other employees as a category of customers (Kanji, Malek, and Tambi, 1999). In one study, Sharabi (2013) categorizes major HEI stakeholders into three tiers—students (customer tier), other employees (boundary tier), and HEAs (coordination tier).

The expectation of every student in an HEI is to graduate and obtain a job to improve his or her earnings in consonance with the UNESCO’s Global Education 2030 Agenda Through Sustainable Development Goal 4 (UN Sustainable Development Goals, 2016). Thus, the teaching and learning processes and the outcomes must promote problem solving and creative think-ing, understanding and respect for human rights, inclusion and equity; all of which are essential to the realization of peace, responsible citizenship, and sustainable development. Recent research has identified the expectations of students as access to an e-library or turnaround time for issuing books in the library, turnaround time for admission process, computer systems’ downtime, number of students placed at corporate jobs, salary range of alumni, and residential facilities at hostel rooms, among others (Sunder, 2016).

Conflicts in HE Stakeholder Needs or ExpectationsKotler (2012) posits that quality science, just like marketing

science, establishes the need to clearly define and understand the needs of the customer or stakeholder as a prerequisite for any man-agement philosophy. A variety of literature has been published on the definition of quality HE: as a philosophical concept and elu-sive (Elassy, 2015); as fitness for purpose (Woodhouse, 2006); as a transformation and adding of value to the stakeholder (Chong, 2014); as a context-relative term such as teaching and learning (Elassy, 2015); and as a stakeholder-relative concept including students, academics, employers, non-academic staff, govern-ment, funding agencies, accreditors, and assessors (Burrows and Harvey, 1992). It has been argued that understanding custom-ers’ perceptions can be used to determine appropriate approaches to assure quality, since various stakeholders think about qual-ity in different ways (Elassy, 2015; Udam and Heidmets, 2013). This has led to conflicts among stakeholders (Pham and Starkey, 2016). Razavi, Safari, and Shafie (2012) posit that customer or stakeholder satisfaction is the ultimate goal to achieve quality HE. Hence, stakeholder needs and expectations must be met to achieve quality HE.

HEAs confront an ever-declining student population and an oversupply of capable HE service providers, including growth of the distance education market via the internet (Emiliani, Kensington, and Most, 2005). Most of the degree programs are quickly imitated by other providers, leaving administrators

to compete on the basis of price. Thus, HEAs must focus on increasing enrollments and global ranking, among others for success (Sunder, 2016). Notwithstanding, boosting enrollment could translate into increasing the number of students who have difficulty coping with their studies. A U.S. National Governors Association (1986) study suggests that international competi-tion and the increasing number of students entering HE with lower levels of academic preparation heightened worries about the quality of HE. HEAs, by increasing enrollment, may cause an increase in class size, which conflicts with the teacher’s or student’s definition of quality. HE teachers may prefer a smaller student-to-teacher ratio in terms of quality.

Marginson and Van der Wende (2007) criticized HEAs for focusing on global rankings to achieve quality. They argued that global rankings by Shanghai Jiao Tong University and the Times Higher Education (2015) neither provide guidance on the quality of teaching nor recommend a “clean” ranking, which is transpar-ent, free of self-interest, and methodologically coherent, to improve the quality of HE (Marginson and Van der Wende, 2007).

HEAs have also been criticized for developing good specialist professionals, yet unable to produce well-rounded graduates and, in particular, those who understand business-process orienta-tion and cross-functional integration (Kavanagh and Drennan, 2008). HE teachers are promoted based on their research, teach-ing, and service to the community. Employers may need to retrain the less well-rounded and trained graduates at a higher cost (Green, 1994). The nature of HE instruction will need to become not only more varied and versatile, but will also have to be very high quality to exceed stakeholder expectations.

Research suggests that despite the calls for accountability and reform in HE, there is insufficient stakeholder dialogue and consensus (Bogue and Hall, 2012; Morse, 2014; Zemsky, 2009). Although stakeholders agree that HE is in need of reform, there is insufficient knowledge about the extent to which major stake-holders align or differ on various characteristics of accountability (Bogue and Hall, 2012). From these perspectives, the needs and expectations of the major stakeholders (HE governing council, HEAs, students, and teachers) should create the needed envi-ronment for institutional change and improvement (Hess and Benjamin, 2015).

Brint and Clofter (2016) suggested that most studies are principally interested in how HEIs work and what forces in their environments lead them to change. However, most poli-cymakers do not want to simply understand HEI systems, but rather to know how to make them work better to achieve qual-ity HE. An HEI must focus on the needs or expectations of its stakeholders to achieve quality HE. Consequently, the goals, objectives, and focus of some of the major stakeholders in HEIs

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that are conflicting must be resolved. The aim of this study is to identify a tool to resolve some of these conflicts within stake-holder expectations. To achieve this aim, the question “To what extent do HEAs meet the major stakeholders’ expectations?” was investigated.

Tools Available for Managing Stakeholder Conflicts and Challenges in Implementation

In this competitive HE environment, the survival of the insti-tution depends on the ability to meet and exceed stakeholder expectations. Hence, the HEA must identify new tools, technol-ogies, and systems to improve the quality of HE by translating the voice of the customer (stakeholder expectation) into critical to quality (CTQ) characteristics.

Studies have found that HE stakeholders hold diverse perspec-tives on quality and are reluctant to use the results of accreditation evaluation reports because of conflicts of interest (Fenwick, 2016; Pham and Starkey, 2016; Miller, 2016). Challenges in imple-menting the quality initiatives to resolve some of these conflicts include resistance to change by administrators, teachers, and staff members; lack of time; short-term thinking; stuck on tradi-tion; what is in it for me? mentality; and lack of support from team members (Akao, 1990; Aly and Akpovi, 2001). According to Vazzana, Backmann, and Elfrink (1997), quality initiatives are widely practiced in HEIs, for example, there are several criteria required for HEIs to fulfil for the Malcolm Baldridge National Quality Award. Though, Karapetrovic, Rajamani, and Willborn (1999) indicated that without a methodical approach to improv-ing quality, the initiatives to improve HE may be doomed for failure. Venkatraman (2007) posits that in HEIs, service quality focuses on the students, time of delivery of programs, intangi-bility (for example, the learning process being challenging to measure), and difficulty in measuring successful output and pro-ductivity in quality. However, Hwarng and Teo (2001) state that a critical step in implementing quality in HE is to identify cur-rent and potential stakeholders. Thus, stakeholders’ focus must provide direction for HE quality improvement initiatives.

Other studies measuring the quality of HE have used the SERVQUAL method (Parasuraman, Zeithaml, and Berry, 1985; Tuan, 2012), Higher Education Performance (HEdPERF) (Abdullah, 2006), and Higher Education Service Quality (HiEdQual) (Annamdevula and Bellamkonda, 2012) mod-els. Notwithstanding, a long-term Harvard study found that institutions which blindly fulfill stakeholders’ expectations did worse than institutions which balanced the interests of all their stakeholders (Caulkin and Black, 1994; Kotter and Heskett, 1992). Nonetheless, Abidin (2015) argued that the differences in SERVQUAL, HEdPERF, and HiEdQual models show that

service quality varies, depending on the research objective and the stakeholder group and, therefore, are unsuitable for the pur-pose in this study. Hence, the tool must help the HEA improve the existing processes by balancing the interests of all stakehold-ers to ensure maximum results in quality HE.

Quality function deployment (QFD) (Akao, 1997) and the Kano model (Kano, Seraku, Takahashi, and Tsuji, 1984) are tools used extensively to identify and translate the voice of cus-tomer, CTQ, or stakeholder expectations to improve quality (Al-Bashir, 2016; Tetteh, 2015). Previous research acknowledges the risk of the HEA solely relying on his/her expectations to achieve quality HE (Keller et al., 2014). Although QFD (Yeh, 2010) and SERVQUAL (Sulisworo and Maniquiz, 2012) meth-odologies have been used to improve quality, the Kano model has been shown to be more beneficial (Paraschivescu and Cotirlet, 2012; Sulisworo and Maniquiz, 2012). Also, Lo, Shen, and Chen (2016) state that it is a challenge for traditional QFD to accurately recognize customer expectations. The Kano model, and its related theory and methodology, is well-established and has been applied extensively in the field of education (Tetteh, 2015; Witell, Löfgren, and Dahlgaard, 2013). Kano, Seraku, Takahashi, and Tsuji (1984) stated that blindly fulfilling stake-holder expectations has risk associated with it, if the product or service provider is not aware that there are different types of stakeholder requirements. Lately, research has been published on practical applications of the Kano model in translating the voice of customer to improve quality (Mitrabasu, 2013; Paraschivescu and Cotirlet, 2012; Sulisworo and Maniquiz, 2012). While a number of papers have been published on the applications of the Kano model, relatively few have used the model to resolve con-flicts among major stakeholders in the HE system (see Chang and Chang, 2012; Gustavsson, Gremyr, and Sarenmalm, 2016; Keller et al., 2014; Shahin et al., 2017). The Kano model is use-ful for incorporating stakeholder expectations into the design of processes (Mikulic and Prebezac, 2011). As also concluded by Walden (1993), the Kano model analysis has the potential to increase confidence in the analysis of stakeholder expectations. Thus, by choosing the Kano model from the review, this research will overcome the gap in terms of focusing on a sole stakeholder and blindly fulfilling stakeholder expectations.

Method: Kano ModelThe Kano model is employed to identify the stakeholder

expectations that are CTQs and the functional requirements (FR) to help improve the quality of HE. To that end, Sunder (2016) proposed CTQ stakeholder expectations to generate what the stakeholder needs or expects. The traditional Kano model is an approximate estimate of the stakeholders’ expectations, which

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only allows attributes of qualitative assessment of the expecta-tions (Wassenaar, Chen, Cheng, and Sudjianto, 2005). This research employed several quantitative measures to assign scales in terms of the levels of stakeholder satisfaction or dissatisfaction (Berger et al., 1993; Matzler and Hinterhuber, 1998).

Based on the Kano model, the FR of each variable were ini-tially classified using the functional and dysfunctional form of the Kano model questions (Kano et al., 1984) as Exciter or Attractive (A), Must-be (M), One-dimensional (O), and Indifferent (I) as depicted in Table 1.

For each variable, contingency output was generated (between functional and dysfunctional questions) and the frequencies of respondents were summed according to the classification structure (where the letters represent the stakeholder groups). A functional question captures the stakeholders’ response if an expectation has a certain attribute, and a dysfunctional form question captures the response if an expectation does not have that attribute. A Questionable (Q) category is not included in the averages, and a Reverse (R) category can be transformed out of the category by reversing the sense of functional and dys-functional questions (Berger et al., 1993). To fully exploit these insights, all the needs and the expectations of the major stake-holders must be analyzed and ranked as Dissatisfier – Must be; Satisfier – More is better; and Exciter – Latent need by using the Kano model (Tetteh, 2015).

Following the research of Xu, Jiao, Yang, and Helander (2009), this study adopts a scoring scheme that defines stakehold-ers’ satisfaction (using functional questions) and dissatisfaction (using dysfunctional questions) as depicted in Table 2. The scale is designed to be asymmetric because positive answers are considered to be stronger responses than negative ones (Tetteh, 2015; Xu, Jiao, Yang, and Helander, 2009).

ParticipantsThis study settled on a cross-sectional survey design to exam-

ine the expectations of the major stakeholders (academic leaders, HEAs, teachers, and students) to achieve quality HE leading to the formation of the four groups (Creswell, 2012). This cat-egorization was done through a brainstorming session with the academic leaders and administrators, as in the Emery and Tian (2002) study. To reduce coverage and sampling error, a list of the target population (sometimes called the sampling frame), was obtained from five HEIs (public and private) in Accra, Ghana, and they were randomly selected to become participants (Salant and Dillman, 1994). HEAs participated in this study, as their positions make them rich sources of information on how quality of HE was perceived. This aimed at ensuring “the maximum variation sampling” (Patton, 2002; Pham and Starkey, 2016). Two hundred participants were randomly selected after a pas-sive consent procedure was employed. None of the participants were pressured to participate, and all were assured that it was a voluntary activity. The major stakeholders were represented by 20 (10%) academic leaders, 38 (19%) HEAs, 37 (19%) teachers, and 105 (53%) students. Of the 200 participants, 106 (53%) were males and 94 (47%) were females.

The author acted as an action researcher, conducting research within the Ghanaian HEIs (Coghlan and Brannick, 2008). Two sources were used for data collection. The first was an email from which 113 responses were used. The second source was face-to-face interviews, which lasted about 45 minutes, that were recorded and transcribed. The use of multiple data sources could

Table 1: Kano Evaluation Table (Kano et al., 1984)

Dysfunctional Questions

I like it that way

It must be that way

I am neutral

I can live with it that way

I dislike it that way

Func

tiona

l Que

stio

n

I like it that way

Q E E E O

It must be that way

R I I I M

I am neutral R I I I M

I can live with it that way

R I I I M

I dislike it that way

R R R R Q

E: Exciter or Attractive, O: One-dimensional, M: Must be, I: Indifferent, R: Reverse, Q: Questionable

Table 2: Scores for Functional/Dysfunctional Features (Xu et al., 2009).

Functional form questions

Dysfunctional form questions

I like it that way 1.00 −0.50

It must be that way 0.50 −0.25

I am neutral 0.00 0.00

I can live with it that way −0.25 0.50

I dislike it that way −0.50 1.00

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be considered triangulation, which serves to strengthen the find-ings (Bryman and Bell, 2007). A reflective dialogue between the researcher and the stakeholders was used to sort the expectations, which increased the understanding, credibility, and internal validity of stakeholder expectations (Eisenhardt, 1989).

The data for this research were collected through participa-tive observations and interviews with the major stakeholders. An overlap between data collection and data analysis allowed the researchers to iteratively collect and analyze data (Coghlan and Brannick, 2008; Meredith, 1998). A qualitative content analysis (Flick, 2014) was carried out focusing on practical implications of

the Kano model and the relation to different stakeholder expec-tations to improve the quality of HE. Thus, the data were related to the theoretical framework through a second-order analysis of the empirical material (Gustavsson et al., 2016; Reason and Bradbury, 2009; Tetteh, 2015).

Instrument. The Sunder (2016) and Kano et al. (1984) questionnaires were slightly modified to fit the present study and measure the major stakeholder expectations as depicted in Table 3.

For each question, respondents could answer in five different ways following a 5-point Likert scale (Likert, 1932): (l) I like it

Table 3: Questionnaire (Sunder, 2016)

Stakeholder Expectations (“What”) How do you feel if ...

Importance 9-point Likert scale1 = Never important 2 = Not very important 3 = Occasionally important 4 = Sometimes important 5 = Fairly important 6 = Quite often important 7 = Very often important 8 = Continually important 9 = Always important

Choose either ①, ②, ③, ④, or ⑤ only

I like it that way

It must be that way

I am neutral

I can live with it that way

I dislike it that way

1a. Pass percentage of students in a class ① ② ③ ④ ⑤

2a. Turnaround time for issuing books in the library ① ② ③ ④ ⑤

3a. Turnaround time for admission process ① ② ③ ④ ⑤

4a. Overall student satisfaction score ① ② ③ ④ ⑤

5a. Computer laboratory equipment availability ① ② ③ ④ ⑤

6a. Computer systems downtime at the university ① ② ③ ④ ⑤

7a. Number of students placed at corporate jobs ① ② ③ ④ ⑤

8a. Salary range of passed students from the university ① ② ③ ④ ⑤

9a. Residential facilities at hostel rooms ① ② ③ ④ ⑤

10a. Facilities for gymnasium and sports center ① ② ③ ④ ⑤

11a. Increase in students’ enrollment ① ② ③ ④ ⑤

12a. Improvement in university ranking ① ② ③ ④ ⑤

13a. Increase in research papers published per department ① ② ③ ④ ⑤

14a. Quality of research ① ② ③ ④ ⑤

15a. University maintenance culture ① ② ③ ④ ⑤

16a. Food wastage in university cafeteria ① ② ③ ④ ⑤

17a. Standard of teaching ① ② ③ ④ ⑤

18a. Student’s absenteeism ① ② ③ ④ ⑤

19a. Accuracy of medical prescriptions at university’s clinic ① ② ③ ④ ⑤

20a. Paper consumption in the university ① ② ③ ④ ⑤

21a. Accreditation process ① ② ③ ④ ⑤

22a. Accreditation would ensure quality ① ② ③ ④ ⑤

10 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

that way, (2) It must be that way, (3) I am neutral, (4) I can live with it that way, and (5) I dislike it that way. The categorization was done through a brainstorming session with the academic leaders and adminis-trators, as in the Emery and Tian (2002) study. The attributes were then placed in the Kano model based on their influence on stakeholder satisfaction.

Study design relevance – Reliability and validity of outcome measures. The reliability of a scale indicates how the design is free from random error. The aspect of reliability assesses the internal consistency of major stakeholder expectations. A total of 88 items were selected to identify these expectations. In determining the reliabil-ity of the instrument, a general rule is that the indicator should have a Cronbach’s alpha of 0.60 or more (Nunnally, 1978). The Cronbach’s alpha for the 88 items was 0.891 as depicted in Table 4, indicating that the instrument was reliable and suit-able for analysis.

Based on the findings of Tetteh (2015), the level of importance of the functional requirements was determined by the application of factor analysis (principal component technique). The use of the fac-tor analysis method demands the existence of correlation among the variables of inter-est and also the adequacy of the sample in order for the factors formed to account for higher deviations in the variables. To achieve construct validity, the data were examined using prin-cipal component analysis as the extraction technique and the varimax as the method of rotation. With a cutoff loading of 0.50 and an Eigen value greater than 1.0, none of the items were dropped. The assumption of using the factor analysis method conformed to McNaught, Caputi, Oades, and Deane’s (2007) test of the validity of the Recovery Assessment Scale (RAS).

The high statistics of Bartlett’s Test of Sphericity (18679.340) with the corresponding small significant value (0.0005) con-firmed the existence of strong correlation among the responses and the Kaiser-Meyer-Olkin (KMO) statistics of 0.967, which is greater than 0.500 and indicated strong sampling adequacy. Hence, the reliability of the data (sample) for the factor analysis technique is adequate as depicted in Table 5.

ResultsThe focus of this study was to resolve the conflicts with the

expectations of the major stakeholders in the HEIs using the Kano model. The Kano indices were computed to obtain the configuration index for each of the major stakeholder expecta-tions as Exciter or Attractive, Must-be, One-dimensional, or

Table 5: KMO and Bartlett’s Test

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.967

Bartlett's Test of Sphericity

Approx. Chi-Square 18679.340

df 4095

Sig 0.000

Table 4: Reliability Statistics

Reliability Statistics

Cronbach’s Alpha

Cronbach’s Alpha based on standardized Items

Number of items

0.891 0.842 88

Summary Item Statistics

Mean Minimum Maximum Range Maximum/ Minimum

Variance N of Items

Item means 4.693 1.855 7.510 5.655 4.049 3.669 88

Item variances

1.935 0.462 4.635 4.173 10.040 1.783 88

Inter-item correlations

0.002 −0.763 0.814 1.577 −1.067 0.306 88

ANOVA

Sum of squares

df Mean square

F Sig

Between people 1304.591 199 6.556

With

in

peop

le Between items 63836.979 87 733.758 389.981 0.000

Residual 32574.839 17313 1.882

Total 96411.818 17400 5.541

Total 97716.409 17599 5.552

Grand Mean = 4.69

Hotelling's T-Squared Test

Hotelling's T-Squared

F df1 df2 Sig

93985.893 613.435 87 113 0.000

11 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

Indifferent based on a model proposed by Berger et al. (1993) as depicted in Figure 1.

By comparing the prioritized stakeholders’ expectations into Exciter or Attractive, Must-be, One-dimensional, or Indifferent using the Kano model, the HEA could intuitively make a deci-sion as shown in Figure 1 (Jeon, Kim, Lee, Lee, and In, 2012). The results indicate that strategies to minimize student absentee-ism would excite students, while these must-be qualities require consideration to avoid student dissatisfaction.

DiscussionThe uniqueness of this study lies in the application of the

Kano model to resolve conflicts by incorporating a perspective of understanding the criticality of needs or expectations from the major stakeholders such as academic leaders, HEAs, teachers, and students (Bate and Robert, 2007; Jeon et al., 2012; Lengnick-Hall, 1995). The various roles of a student, for example, treated as a customer (Gruber et al., 2010) in the HE process, would ensure quality of HE and improve institutions.

This study supports what is argued by Sulisworo and Maniquiz (2012) that the Kano model is a practical tool for the quality of HE to classify different stakeholder expectations,

monitor those expectations, and prioritize the various action plans required to improve the system. As an example, in the Kano model, both the spoken (one-dimensional) and unspoken (attractive and must-be) expectations of stakeholders are visu-alized. However, the same methods cannot be used to collect data on spoken and unspoken expectations. Direct methods such as interviews can aid in identifying spoken expectations, whereas indirect methods like observations are necessary to iden-tify unspoken expectations. Earlier studies (Keller et al., 2014; Paraschivescu and Cotirlet, 2012) indicated a challenge in using only stakeholder input from surveys or interviews when collect-ing expectations, as the unspoken expectations will be missing.

The study confirms this challenge, but also points to a way of overcoming it. That is, the challenge can be met by not only col-lecting stakeholder input through methods such as surveys, but also allowing HE internal and external stakeholders to provide input (Gustavsson et al., 2016; Lengnick-Hall, 1995). Hence, it is not only critical to use a variety of methods to collect stakehold-ers’ expectations, but it is also important to involve a variety of respondent groups in providing input on expectations related to the various stakeholder roles.

Theoretical and Practical Implications

This study suggests that HEAs must concentrate on strategies that reduce or minimize student absenteeism as an exciter or attractive quality, rather than global ranking, which is an indiffer-ent quality (Balfanz and Byrnes, 2013). Attractive quality is an attribute that provides satisfaction when achieved fully, but does not cause dissatisfaction when not fulfilled. On the other hand, indifferent attributes refer to aspects that are neither good nor bad, and they do not result in either customer satisfaction or customer dissatisfaction.

This study confirms the conclusion of Kano et al. (1984) that blindly fulfill-ing stakeholder/customer expectations has risks such as providing superfluous quality. That is wowing the stakeholder/customer in one area and driving them to competitors in another; and focusing only on what stakeholders/customers say, and not what they think (Kano et al., 1984; Woodham, Williams, and McNeil, 2017).

Func

tiona

l (sa

tisfa

ctio

n)

1

Attractive or Exciter18. Student’s absenteeism

One-Dimensional11. Increase in students’ enrollment14. Quality of research15. University maintenance culture16. Food wastage in university

cafeteria17. Standard of teaching20. Paper consumption in the

university21. Accreditation process22. Accreditation would ensure quality

0.5

Indifference 1. Pass percentage of students 2. Turnaround time in the library 4. Overall student satisfaction score 5. Laboratory equipment availability 6. Computer systems downtime 9. Residential facilities12. University ranking19. Accuracy of medical prescriptions

at university’s clinic

Must Be 3. Turnaround time for admission 7. Number of students placed at jobs 8. Salary range of alumni from the

university13. Number of research papers

published

0 0.5 1

Dysfunctional (dissatisfaction)

Figure 1: Stakeholder Expectations with Kano Model IndicesNote that stakeholder expectation number 10 was not selected based on the responses of the stakeholders.

12 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

ConclusionsThe results of this study found that student absenteeism is

an attractive quality. Indeed, out of 15 different types of reasons for student absenteeism from an earlier study, factors relating to courses and teachers were found to be the least significant (Longhurst, 1999). Consequently, students just go through the motions because of the dearth of reasonably attractive jobs available to them, and parental and peer-group pressure (UN Sustainable Development Goals, 2016).

The main contribution of this study is to resolve the major stakeholders’ conflicts in the HEIs using the Kano model. Looking at the various roles is a way to realize the necessity of cap-turing input from various stakeholders (such as academic leaders, HEAs, teachers, and students). Further, it is important to apply different methods in collecting data when assessing stakeholder expectations, as some of the expectations are explicit (expressed or spoken) and some are implicit (implied or unspoken). This study contributes to knowledge on how to combine the stakeholder expectations to resolve conflicts using the Kano model.

Limitations and Directions for Further ResearchThere are a number of limitations to this study. It has drawn

conclusions based on responses from stakeholders in private and public HEIs in Accra, Ghana; hence, the outcome cannot be generalized. Notwithstanding, the findings could provide valu-able insights to HEAs in HEIs.

Further studies could address how to initially obtain stake-holder expectations as an input before becoming a stakeholder. In order to capture these types of expectations, data collection from other respondent groups, such as external stakeholders (national university commission, non-governmental organiza-tions, community-based organizations, parents, employers of labor, trade unions, alumni association, and industries/firms) might be a way forward in future research.

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Godson A. Tetteh, Ph.D., is an executive management consultant, distinguished fac-ulty, and a Lean Six Sigma expert. He has proven success in planning and implement-ing improvement processes to increase productivity using Lean manufacturing, product design and development, as well as Six Sigma principles for innovative business strategy execution. He is currently a lecturer at the Ghana Institute of Management and Public Administration. Tetteh earned the enviable 2016 Distinguished New Faculty Award at the 27th Annual International Conference on College Teaching and Learning. His research interests are in the areas of optimizing business models and production planning, supply chain manage-ment systems, and total quality management systems. He has authored more than 15 jour-nal and conference papers. Tetteh is an ASQ-certified Six Sigma Black Belt and can be contacted at tettehgo@yahoo.com.

Godson A. Tetteh

16 Quality Approaches in Education Vol. 8, No. 2

asq.org/edu

Quality Approachesin Education FOCUS AREA:

HIGHER EDUCATION

Evaluating the

use of templates

for structured

creativity

Structured Creativity for Strategy Development – An Empirical Test of Effectiveness of Template Use in MBA Strategy ClassesRaghu Tadepalli and Ravi Chinta

AbstractThis article outlines the design and testing of a template-based assignment that emulates structured creativity in developing a strategy for a given firm. Learning by doing is accom-plished in this course by employing directed learning through the use of templates to guide the development of strategic options. However, the use of templates is optional, and some students with work experience choose not to use them. Learning outcomes for this applied course are assessed by a rubric that closely tracks the structured creativity process enabled by the template in use. The impact of template use and work experience on the final proj-ect performance is empirically tested. The findings show that templates can enhance the quality of strategy options created in the strategy-development process for all levels of work experience with a pronounced effect on those with higher levels of experience. Therefore, template-based pedagogy in strategy-options development projects is recommended as it provides the students a richer learning experience in applying strategy concepts leading to enhanced learning outcomes.

KeywordsTeaching Strategy, Templates in Pedagogy, Learning by Doing, Bridges to Practice, Strategy Projects

IntroductionBusiness education has evolved as it adapts to marketplace needs. Business schools have

made significant advances in the substantive content of their MBA and executive offerings during recent years, according to Mitchell (2007). While these efforts have taken root in all functional areas of management, the how-to (practical) aspects in strategy formulation are largely seen as more art than science. Gioia (2002) laments business education’s role in the crisis of corporate confidence because current offerings in academia do not promote the creativity required in strategy development. Hambrick and Fredrickson (2001) ask the simple questions, despite all the knowledge imparted in academia, “If one does have the right strategy? Or can our MBA students really do strategy practice?” Mintzberg (2004) makes a dramatic argument for reframing management education as a practical art. Datar, Garvin, and Cullen (2011) call this a crisis in business education that can only be solved with greater “integration” with reality outside of universities.

Many in academia seem to yearn for alternative pedagogical techniques by first sug-gesting that management education in the United States tends to be too structured around case analysis, scenarios, simulations, strategy games, best practices, and linear summaries of relevant research. Hence, management education should be supplemented by the use of other techniques, such as serious play (Burgi, Jacobs, and Roos, 2005; Statler, 2005; Roos, 2006), biographical writing (Jacobs, 2007; Learmonth, 2007), or evidence-based instruc-tion (Rousseau and McCarthy, 2007; Klimoski, 2007). Learning by doing is one of the alternative options for pedagogy in strategy. In this article, we propose a template-based approach for strategy development that emulates a structured creativity process for effective

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and efficient use of the limited time available to senior execu-tives. This approach has been used for more than a decade in strategic management courses taught at graduate and undergrad-uate levels at three universities in the United States. A rubric that allows an assessment of the output ensures that strategy options appropriate to the firm are developed.

Template as a Tool For Structured CreativityA template is like a jigsaw puzzle that one needs to solve.

There is an underlying (latent) structure that straitjackets the amount of deviance from the overall task. Template assignments are analogous to “those old dance lessons for which the instruc-tor pasted footsteps on the floor” (Bean, 2011, p. 155). Others have likened templates to the sheet music that guides musicians. However, such metaphors may be too limiting to describe the utility of templates. Templates allow for structured creativity just as clear goals allow for diverse strategies in organizations. Straitjacketing so as to minimize waste without stifling creativ-ity is a balance that good design ensures in templates. A process of brainstorming divergence followed by a process of evaluative convergence in a structured process maximizes targeted creative solutions that are goal-oriented.

Literature Review on Link Between Structured Creativity and Outcomes

Before discussing the specifics of using a particular template as a structured creativity tool and its effects on learning outcomes, a review of the literature is presented to provide a theoretical underpinning for the linkage between structured creativity and outcomes. In a very broad sense, Drucker defines innovation as “an application of knowledge to produce new knowledge” (Drucker, 1993). That is, new knowledge, excluding serendipitous discover-ies, is structured by and emerges from extant knowledge. Such a view is consistent with Dewey’s (1938) theory of education, which suggests that structured experience and prior knowledge form the basis of education. Vygotsky (1978) contended that structure leads to better focus and coherence in student learning outcomes. Building on Bloom’s (1956) taxonomy, Anderson and Krathwohl (2001) presented a structured framework, comprised of two major dimensions—the Knowledge Dimension, which repre-sents a range from concrete (factual) to abstract (metacognitive) and the Cognitive Process Dimension, which promotes inno-vative learning outcomes. A closer scrutiny of their framework reveals an underlying structure that guides the gradual movement toward higher levels of learning called metacognition combined with creation. In short, structure promotes creativity and better outcomes for students with the latest pedagogical trends mani-festing in the use of simulations (Aldrich, 2005; Anderson and

Lawton, 2009) and games to structure creative thinking (De Freitas, 2006; Zagal, 2010).

Structured frameworks to promote engineering creativity as well as research and development (R&D) innovations have been in use within firms for a long time (Savransky, 2000; Rantanen and Domb, 2010). For example, Quality Function Deployment and TRIZ are structured processes for inventive solutions (Yamashina, Ito, and Kawada, 2002). In discussing problems in managing innovation in firms, Van de Ven (1986) suggests that structure and framing tend to provide focus and better results. Having definitive screening criteria can promote rather than inhibit product innovation in large firms (Dougherty, 1992). Hamel (2006) discusses twelve innovations that shaped mod-ern management ranging from the old time-and-motion studies to current strategic, formalized analytical frameworks, which have one thing in common—an underlying structure that brings focus and promotes high quality options to solve the problem at hand. Deliberate structured creativity is manifested in prod-uct development templates (Ny, Hallstedt, Robèrt, and Broman, 2008); project-network templates to streamline innovations (Shenhar and Dvir, 2007; Larson and Gray, 2011); protocols in drug discovery (Karin, Yamamoto, and Wang, 2004); analytical frameworks to screen out designs (Keast and Hampson, 2007); control charts to determine process improvements (Langley, 1999; Goetsch and Davis, 2014); and even in strategic planning processes (Eden and Ackermann, 2013).

Our review of the literature reveals that templates are widely used to bring focus and improved outcomes in developing higher quality options in problem solving. Thus, templates are meta-level process constructs that are generalizable across con-texts (Anderson and Krathwohl, 2001) allowing simultaneous achievement of meta-cognition and creativity. However, the use of templates has not been without criticism (Chari, Rao, and Rohatgi, 2003). While we recognize the extensive prevalence of structured creativity and its consequent benefits in the business world, this research focuses on the strategic management process (SMP) template and its consequent benefits. Specifically, this study empirically tests the expected a-priori linkage between the use of SMP templates and outcomes.

Further, this research also examines the impact of experience on the use of templates and, hence, the benefits that accrue from their use. Studies have shown that experience can sometimes lead to an illusory confidence that is dismissive of the use of templates or instructions to follow (Fellner, Güth, and Maciejovsky, 2004; Jee, Wiley, and Griffin, 2006). Experienced managers use uncon-scious routines, called heuristics in the literature, to cope with complex situations in decision making (Hammond, Keeney, and Raiffa, 2006; Michalewicz and Fogel, 2013); e.g., they do not use

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templates or rely on structured analyses. However, other studies have shown that when experts use templates, the outcomes were better (Linn, 1985; Riss, Cress, Kimmerle, and Martin, 2007). In fact, Karrer (2007) contends that the emerging field of arti-ficial intelligence is based on experts using templates. Thus, the effect of work experience on the use of templates and benefits from their use is an unsettled issue that deserves further research. This study attempts to fulfill that gap in existing literature.

In summary, the literature review reveals that structured cre-ativity (e.g., use of templates) is related to outcomes, and that work experience can also have an effect on the use of and bene-fits from templates. The research questions and hypotheses were developed on the use of the SMP template, which is described next in detail with a rubric for its evaluation. The SMP template and its rubric form the bedrock of this study.

Use of Template For Strategy Options Development and Evaluation

Strategic management is a capstone course that integrates all functional areas of management such as marketing, operations, finance, accounting, global supply chain, business law, business ethics, economics, and statistics. The emphasis is on developing strategic options to manage the current business to survive and also to create tomorrow’s business for growth and advancement. Much of this strategy-development work requires significant analysis and integration of all areas of management within a given firm and sensing the external environmental changes to adapt to as a firm.

There is no best strategy to showcase to students since strat-egy is highly contextual and the best strategy depends on the specific firm being analyzed and the precise situation in which the firm is imbedded. Good strategies result from the use of a strategic management process for a given firm in a specific situ-ation. This is essentially a structured creativity process that the students have to demonstrate in developing the best strategy for a given firm. Such an approach has been successfully used in teaching finance curriculum (Carrithers, Bean, and Ling, 2008).

The template strategy for the written assignment is best-suited to the strategy assignment, which is about developing a thoroughly analyzed strategy for a given firm in a specific situation. The template shows all of the steps in the strategic management process that must be followed to come up with the options, which then will be evaluated to arrive at the recom-mended strategy. The template also serves as a scaffolding to build the final paper for the students (Cho and Schunn, 2007). A rubric that was used for the final paper grading, as noted in this article, follows the template. However, the rubric was not shared with the students.

Strategic Management ProcessThe strategic management process involves the following 12 steps:

1. Determine the organization’s mission, vision, values, and goals

2. Internal analysis leading to strengths and weaknesses (SW) of the firm

3. External analysis leading to opportunities and threats (OT) in the external environment

4. SWOT matrix enumeration and creative dialogue to develop options

5. Develop S + O options (at least two options in this category)

6. Develop S + T options (at least two options in this category)

7. Develop W + O options (at least two options in this category)

8. Develop W + T options (at least two options in this category)

9. Assess the options generated using the decision criteria

10. Evaluate options to create a rank-ordered list of the options

11. Recommend strategy with rationale on why it was chosen

12. Develop implementation plan

Students are given the following assignment: Imagine that you are a highly paid strategy consultant from McKinsey, Bain, Boston Consulting Group or Mercer, etc., hired by a firm to execute the SMP to recommend a strategy for implementation. For the firm that hired you, write an eight-page analytical report (double-spaced, 12-point font), excluding any supporting appendices, with a final recommendation for a strategy to be implemented. You are expected to follow the SMP process and touch on all the steps outlined above. Write “not applicable” if you are skipping any step with some expla-nation why that step ought to be skipped.

In the above analytical paper, students are expected to learn the critical lesson that strategy is essentially based on marrying an internal aspect to an external aspect of the firm’s environment with the objective of sustainably creating and capturing value. That is why strategy consultants are so highly paid. Students are told to follow the template (the SMP process) but ensure the generation of value-creating options that are significant and con-text-specific. Simply stated, students are advised not to stay in the conceptual clouds but instead be specific to the firm analyzed. They are taught how to compose strategy from its essential com-ponents and also how to decompose a strategy into its essential elements. In doing so, the intent is to help students understand that they can apply the SMP process to any system that they will manage. See Table 1 for the rubric used.

To what extent does template-driven pedagogy improve learning outcomes in a strategy class that is oriented toward the creative development of strategy options for a given firm?

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Relative to students with no work experience, those who have work experience intuitively know that structured processes can lead to the generation of more relevant options to solve a prob-lem. Thus, the level of work experience among students impacts the use of structured templates (Alexander, 2003). Therefore, the following research questions and hypotheses were developed for this study as shown in Table 2.

Four sections of an MBA strategy course with a total of 110 students comprised the sample for this study. In two sections, the 12-step strategic planning process was introduced at the begin-ning of the course to all students with instructions that use of the process template is optional but useful. In the other two sections, the template was not introduced, although the same strategic plan-ning process was described as a concept without the structure of a template. That is, two sections had the templates and two did not. The rubric for grading the final paper was not provided to the stu-dents before but was available to them after the final papers were graded. The assignment for each student was to analyze a firm and recommend a strategy. The final strategy recommendation paper was due at the end of the semester. Students must describe the strategic analyses and evaluation before recommending a strategy. Work-experience data on students were collected at the begin-ning of the course on an index card in which each student also described his/her expectations of the course.

The dependent variable is the final paper scores that were based on the rubric described earlier. This score is a proxy measure for

the learning outcomes for the students. The final paper score was a maximum of 20 points with a bonus of 10% for outstanding work. While grading the final paper for each student, the instructor could easily identify those students who did not use the template even in the sections where the template was introduced. The work-experience data from the index cards were used to categorize the students into four groups on the work-experience variable: (1) none, (2) low (< 3 years), (3) medium (< 8 years) and (4) high (> 8

Table 1: Rubric Used

Rubric (Evaluative criteria with weights)

Poor (far below

expectations) 0%

Inadequate (below

expectations) 50%

Adequate (meets

expectations) 75%

Excellent (exceeds

expectations) 100%

Mission, vision, values and goals 5%

Internal analysis leading to strengths and weaknesses (SW) 10%

External analysis leading to opportunities and threats in the external environment (OT)

10%

SWOT matrix enumeration for creative dialogue on options 5%

S + O options (at least two options in this category) to create value 10%

S + T options (at least two options in this category) to create value 10%

W + O options (at least two options in this category) to create value 10%

W + T options (at least two options in this category) to create value 10%

Decision criteria to assess the options generated 10%

Options evaluation leading to a rank-ordered list of the options 10%

Recommended strategy with rationale why it is chosen 5%

Implementation plan 5%

Table 2: Research Questions and Corresponding Hypotheses

Research Questions Null Hypotheses

RQ1: Is there a difference in learning outcomes between students who use the strategic management process template and those who do not?

H01: Learning outcomes do not differ between students who use the strategic management process template and those who do not.

RQ2: Is there a difference in learning outcomes between students who have work experience and those who do not?

H02: Learning outcomes do not differ between students who have work experience and those who do not.

RQ3: Is there a difference in learning outcomes based on work experience and use of the strategic management process template?

H03: Learning outcomes do not differ based on work experience and the use of the strategic management process template.

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years). The composition of the sample of 110 students in terms of the variables in the study is shown in Table 3. The sample was comprised of 14.5% of students with no work experience, 31.8% of students with less than three years of work experience, 28.1% of students with less than eight years of experience, and 23.6% stu-dents with more than eight years of work experience. Further, the sample was comprised of 55.4% of students who used the process template and 44.6% of students who did not use the template.

Results and DiscussionThe two-way analysis of variance was conducted to investi-

gate the main effects of template use and work experience on the final paper scores. ANOVA results, presented in Table 4, show a significant main effect of template use [F(1,100) = 32.7, p = 0.00, partial eta square = 0.246] and work experience [F(3,100) = 5.23, p = 0.02, partial eta square = 0.136]. Interaction between

the template use and work experience is also significant [F(3,100) = 4.53, p = 0.05, partial eta square = 0.12].

The line plots (final exam scores versus work-experience graphs), provided in Figure 1, show that the two lines do not cross for the two groups that used and did not use the template. However, the interaction term in ANOVA shows that the interac-tion between the template use and work experience is statistically significant. This demonstrates that there is ordinal interaction between template use and work experience. Ordinal interaction is a situation where the main effects still hold even when the fac-tors interact with each other significantly. Disordinal interaction exists when the lines cross each other and when this happens, the main effects do not make any sense (Mertler and Vannatta, 2013). In summary, the results show that the main effects and interaction effect are all statistically significant. That is, the three hypotheses (H1, H2, and H3) are all supported.

The Scheffe post-hoc test was conducted to determine which levels of work experience were significant. The results revealed that the students with no work experience did not differ from students with low levels of work expe-rience (less than three years of experience) but differed significantly from students with medium (between three and eight years of experience) and high (more than eight years of experience) levels of work experience. This find-ing is in line with Alexander (2003), who posits that the journey from application to proficiency does take time.

The support for hypothesis 3 in Table 5 and Figure 1 show a statistically significant and posi-tive effect of the interaction between work experience and template use on outcomes. What is more interesting is that the effect of the interaction is more pronounced at the two ends of work experience. That is, those with low work experience and also those with high levels of work experience achieve a higher level of outcomes when tem-plates are used.

ConclusionThe capstone course, strategic man-

agement, has been globally taught in business schools after the Association to Advance Collegiate Schools of Business made it a requirement to emphasize integration across the business curricu-lum. As the world transitions toward an increasingly interconnected global

Table 3: Frequency Tabulation of Respondents

Value Label N %

Process template use 1 Used process template 61 55.4%

2 Did not use process template 47 44.6%

Work experience 1 None (0 years) 16 14.5%

2 Low (< 3 years) 35 31.8%

3 Medium (< 8 years) 31 28.1%

4 High (> 8 years) 26 23.6%

Table 4: ANOVA Summary for Main Effects and Interaction of Template Use and Work Experience

Tests of Between-Subjects EffectsDependent variable: Final paper score (max=22)

Source Type III Sum of Squares

df Mean Square

F Sig Partial Eta Squared

Corrected model 744.971a 7 106.424 8.129 .000 .363

Intercept 22806.805 1 22806.805 1742.133 .000 .946

Process template use 427.586 1 427.586 32.662 .000 .246

Work experience 205.502 3 68.501 5.233 .002 .136

Interaction effect (Process template use * work experience)

177.913 3 59.304 4.530 .005 .120

Error 1309.131 100 13.091

Total 28971.000 108

Corrected total 2054.102 107

a. R Squared = .363 (Adjusted R Squared = .318)

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society, a knowledge economy is surfacing (Spring, 2008), whereby students must be well-educated to prepare them for the global workplace. In seeking global competitive differentiation, business schools have employed many approaches to incorporate both the theory and prac-tice of strategy into capstone courses. Some have introduced a common com-pany case for use in all functional area courses, and that company would then be subjected to an in-depth, strategy-development exercise in the strategy course. Alternative pedagogical tech-niques structured around case analysis, scenarios, simulations, strategy games, best practices, and linear summaries of relevant research are among the ways in which students have been exposed to the real-life practice of strategy (Chinta, 2009). Mang (2000) suggests that strat-egy is an evolving mosaic that is also experiential and proposes that students should be given a learning opportunity to understand the intricacies of strategy

by actually doing it. The integrative strategy course, while cumu-lative in its essence, can benefit from structured approaches to promote creative thinking. As Rindova and Kotha (2001) suggest, continuous morphing and adaptation to changing contexts (hence attaining an enhanced knowledge level) becomes a normal part of the learning process for MBA students in a structured creativity assignment that generates different strategies for various contexts. Jiang and Murphy (2007) dispel the popular myth that business educators are ineffective managers in the real world.

To be sure, the proposed structured creativity tool using a template in one strategy course is not a panacea, but it is cer-tainly a step in the right direction. Its strength comes from actual and sustained use in the real work of strategy practitio-ners. Its simplicity stems from students learning by doing. Its tenacity results from its flexibility to be molded in accordance with the constantly evolving context. Its intelligence comes from students experiencing “strategy concepts in play.” In conclusion, structured creativity tools such as the template employed in our pedagogy is an integral and required part of an MBA curriculum.

The limitations of this study include the lack of an experi-mental design, cross-sectional data, a student sample, and a relatively small sample size. Our study results possess limited generalizability due to the non-experimental design (Shadish,

Table 5: Scheffe Multiple Comparisons for Levels in Work Experience

Dependent variable: Final paper score (max=22)

(I) Work Experience

(J) Work Experience Mean Difference (I-J)

Std. Error

Sig 95% Confidence Interval

Lower Bound

Upper Bound

None (0 years)

Low (<3 years) −2.82 1.092 .091 −5.92 .29

Medium (<8 years) −4.38* 1.114 .002 −7.55 −1.21

High (>8 years) −3.34* 1.150 .043 −6.61 −.07

Low (< 3 years)

None (0 years) 2.82 1.092 .091 −.29 5.92

Medium (<8 years) −1.56 .892 .385 −4.10 .97

High (>8 years) −.53 .937 .957 −3.19 2.14

Medium (< 8 years)

None (0 years) 4.38* 1.114 .002 1.21 7.55

Low (<3 years) 1.56 .892 .385 −.97 4.10

High (>8 years) 1.04 .962 .761 −1.70 3.78

High (> 8 years)

None (0 years) 3.34* 1.150 .043 .07 6.61

Low (<3 years) .53 .937 .957 −2.14 3.19

Medium (<8 years) −1.04 .962 .761 −3.78 1.70

Error based on observed means is Mean Square (Error) = 13.091.*The mean difference is significant at the .05 level.

20

15

10

5

0None

(0 years)Low

(< 3 years)Medium

(< 8 years)High

(> 8 years)

Used process templateDid not use process template

Proc

ess

tem

plat

e us

e

Work experience

Because the lines do not cross each other, only an ordinal interaction exists between template use and work experience (Kennedy and Bush, 1985;Newman et al., 2005: Mertler and Vannatta, 2013).

Figure 1: Visual Representation of Interaction Between Template Use and Work Experience

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Cook, and Campbell, 2002). One significant limitation of this study is the size and nature of the sample. Cohen (1992) sug-gested that at significance levels of 0.05 and a power of 0.80, one would need a sample size of 783 respondents to detect a small effect (r=0.10), 85 respondents to detect a medium effect (r=0.30), and 28 respondents to detect a large effect (r=0.50). Our sample size of 110 students makes detecting small effects difficult. Additionally, student sample size limits the generaliz-ability of the findings to organizational contexts.

Multiple avenues exist for future research using the tem-plate approach tested in this article. An increasing number of MBA programs are admitting students with little or no work experience. The template approach can be used to assess the extent to which the strategic management course enhances their integration of business material. Similarly, many graduate pro-grams admit large numbers of international students. Many of these students come from countries where the lecture method of instruction is dominant. Students are seen as passive learners who regurgitate material during exams. Many of these students often have little or no work experience. The template approach can be used to determine if these students are better able to integrate material after learning this approach. Additionally, a before-after measure in all of the above cases would help assess whether there is statistically significant improvement in learning from using the template approach. Finally, as MBA programs work to increase the number of minority and female graduates, it is necessary to determine whether the teaching approaches used in business classes (especially quantitative courses such as finance, accounting, and quantitative methods) impact enroll-ment of women and minorities. It would be interesting to test whether the template approach, which emphasizes learning by doing, enhances the ability of women and minority students to integrate across functions and thereby enhances their learning and eventual success in the courses.

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Spring, J. (2008). Research on globalization and education. Review of Educational Research. 78(2), 330-363.

Statler, M. (2005). Practical wisdom and serious play: Reflections on management understanding. In Schrat, H. (Ed.), Sophisticated Survival Techniques/Strategies in Art and Economy. Berlin: Kulturverlag Kadmos.

Yamashina, H., Ito, T., & Kawada, H. (2002). Innovative product devel-opment process by integrating QFD and TRIZ. International Journal of Production Research. 40(5), 1,031-1,050.

Van de Ven, A. H. (1986). Central problems in the management of innovation. Management Science. 32(5), 590-607.

Vygotsky, L. S. (1978). Mind and society: The development of higher psy-chological processes. Cambridge, MA: Harvard University Press.

Zagal, J. P. (2010). Ludoliteracy: defining understanding and supporting games education. ETC Press.

Raghu Tadepalli, Ph.D., is professor of market-ing and dean of the Martha and Spencer Love School of Business at Elon University, Elon, NC. He has published extensively in such journals as Psychology & Marketing, European Journal of Marketing, Journal of Managerial Issues, and Managerial and Decision Economics. Contact him via email at rtadepalli@elon.edu.

Ravi Chinta, Ph.D., is professor and chair, department of management at Huizenga Col-lege of Business and Entrepreneurship, Nova Southeastern University, Fort Lauderdale, FL. He worked in venture-capital industry; business start-ups; and large, multi-billion global firms including: IBM, Reed-Elsevier, LexisNexis, and Hillenbrand Industries. Chinta has more than 58 peer-reviewed publications in journals such as Academy of Management Executive, Jour-nal of Small Business Management, Long Range Planning, Management Research News, Jour-nal of Technology Management in China, and International Journal of Strategic Business Alli-ances. Contact him at ravichinta@hotmail.com.

Raghu Tadepalli

Ravi Chinta

24 Quality Approaches in Education Vol. 8, No. 2

asq.org/edu

Quality Approachesin Education

Increasing

efficiency and

effectiveness

of tutoring

through process

improvement.

A Lean Six Sigma Approach for Improving Utilization of Walk-In TutorsSandra Furterer, Kellie Schneider, Michael B. Key, and Yusheng Zhang

AbstractThe purpose of this study was to improve the utilization of walk-in tutors at the University of Dayton. The Lean Six Sigma methodology is used to identify factors that contribute to the use of walk-in tutors, identify opportunities for improvement, and ensure process improvements are maintained. The goal of this case study was to identify factors that improve walk-in tutor utilization to allow for more efficient and effective tutor staffing and assignment procedures. The methodology and processes outlined in this case study may be implemented at other higher education institutions to improve the efficiency and cost effectiveness of their walk-in tutoring programs and as a guide for improving other processes within institutions.

KeywordsLean Six Sigma, Engineering Education, Higher Education

IntroductionMany higher education institutions (HEIs) struggle to stabilize the fluctuating opera-

tional costs and justify idle time apparent in walk-in tutoring services. This case study is an example of adopting Lean Six Sigma (LSS) within HEIs to improve tutoring center operations, specifically hiring, scheduling, managing, and collecting data within a walk-in tutoring model. Analysis of recommended improvement strategies showed successful modifications to a walk-in tutoring model to forecast utilization and decrease idle time.

This case study is only one example of the vast applications of LSS for enhancing the knowledge and skills of program coordinators, directors, and administrators in higher edu-cation. Institutions of higher education are beginning to discover more applications of LSS, such as combining the principles of Six Sigma and quality management (Adina-Petruţa and Roxana, 2014); improving online education (Bandyopadhyay, 2014); assessing student surveys (Al Kuwaiti and Subbarayalu, 2015); as well as pedagogy and professional develop-ment (Tetteh, 2015). Additionally, a special journal issue on LSS in higher education was published (Antony, 2015). This special journal issue included papers discussing the spe-cific issues faced by HEIs when implementing LSS (Balzer, Brodke, and Kizhakethalackal, 2015; Waterbury, 2015); implementation of LSS in King Abdullah University of Science and Technology (Svensson, Antony, Ba-Essa, Bakhsh, and Albliwi, 2015); as well as the differences in implementing LSS in further educational institutions compared to HEIs (Thomas, Antony, Francis, and Fisher, 2015). The journal also discussed applying Lean wastes to HEIs as well as 5S, point-of-use storage, process mapping, value-stream mapping, and level scheduling (Douglas, Antony, and Douglas, 2015).

Furterer and Crumpton-Young (2005) incorporated LSS experiential learning oppor-tunities into a graduate industrial engineering and management systems course at the University of Central Florida. The students performed real-world LSS projects to improve the university’s processes. The student projects focused on teaching and learning. An LSS project improved a WebCT course development and design process (Sharawi, Sha, Rajendran, and Furterer, 2007). Another LSS project designed a process management model to achieve operational excellence using Six Sigma tools (Rodrigues et al., 2006).

FOCUS AREA: HIGHER EDUCATION

25 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

The faculty accreditation process was improved (Furterer et al., 2006a). Asset management processes were also improved at the university (Martinez et al., 2006). Another LSS project used a balanced scorecard in a Six Sigma academic improvement proj-ect (Akinrefon et al., 2005). A graduate student management program was improved using LSS (Nahmens et al., 2005). LSS was used by another student team to improve education delivery system processes (Sharma et al., 2005). Other projects performed by students focused on administrative processes. For example, an LSS project improved web development and design processes within the university (Furterer et al., 2006b) and National Panhellenic Conference recruitment processes at the University of Central Florida were improved (Jenness et al., 2006). A univer-sity LSS team developed a framework to incorporate Six Sigma problem solving to achieve operational excellence in the univer-sity (Furterer et al., 2005). Finally, the recruiting of university students was improved through the application of the Six Sigma DMAIC methodology and tools (Furterer, Hussian, McMurray, Rowe, and Smith, 2007) by applying LSS as an improvement tool in academia (Coowar and Furterer, 2006). This vast body of research exemplifies how LSS was applied in higher education across a wide variety of processes.

With the need to be more frugal, universities are turning to process improvement methodologies such as LSS and quality-based tools to reduce the cost of administrative activities, as well as teaching and learning processes, as discussed in the methodol-ogy section.

MethodologyFurterer, Schneider, Key, and Zhang (2017) showed how

LSS was applied to higher education in a tutoring administra-tive department to improve tutor utilization and efficiency. The University of Dayton hired a Learning Initiatives Coordinator in August 2015 to coordinate tutoring services for the Office of Learning Resources. Improvement goals were already set toward minimizing idle time in walk-in tutoring. The first action of the Learning Initiatives Coordinator was to move any course with infrequent or inconsistent use to appointment only, leav-ing walk-in staff to support critical courses only. The Learning Initiatives Coordinator collaborated with a faculty member in the Engineering Management, Systems, and Technology department to mentor a graduate student in conducting an LSS analysis as a capstone project, sponsored by the Office of Learning Resources. The primary roadblock for the project’s suc-cess was the administration’s hesitation to accept improvement recommendations from graduate research. Therefore, another faculty member from the department with professional experi-ence applying LSS methodology to aspects of HEIs joined the

team. The project is ongoing due to the recommended improve-ments and control factors identified by this case study.

The research team chose to complete a case study to apply the LSS methodology to the campus tutoring center because of the many factors that exist in the tutoring process, which must be understood to improve process quality and maintain control of the process. LSS allows action researchers to collaborate objec-tively with stakeholders to improve processes. This collaborative case study used the LSS Define-Measure-Analyze-Improve-Control (DMAIC) methodology to improve tutoring processes at the University of Dayton. In the Define phase, the team devel-oped the problem statement to gain an understanding of the gaps in the process, created the project charter to reach agreement on the project goals, and performed a stakeholder analysis to identify stakeholders impacted by the process and the project. The team used a Suppliers-Inputs-Process-Outputs-Customers (SIPOC) tool to understand the five to seven high-level activi-ties to be improved. Finally, in the Define phase, the project manager developed a project plan, which guided the successful completion of the project.

The Measure phase relied on subject-matter experts to observe operational processes and create process maps. The team developed a data-collection plan to identify the metrics and data necessary to understand the current processes. Understanding customer needs related to each process was essential in identi-fying the Critical-to-Satisfaction (CTS) characteristics. The research team used descriptive, graphical, and inferential sta-tistics to understand the processes and factors that significantly affect the tutoring process.

The Analyze phase identified factors and root causes contrib-uting to problems in the process by using a why-why analysis. The research team generated recommendations in the Improve phase to adapt processes, based on implementing and measuring them, to assess the improvement to each process. Finally, in the Control phase, control plans were developed and implemented to maintain process improvements.

The following is a description of the LSS DMAIC methodol-ogy applied to the higher-education tutoring-improvement process.

Define PhaseThe team that embarked on the LSS tutoring project included

an Engineering Management master’s student; two faculty mem-bers from the Engineering Management, Systems, and Technology department—one of whom is a Six Sigma Master Black Belt; and the Learning Initiatives Coordinator from the Office of Learning Resources. The project charter is explained below.

Overview: Walk-in tutoring is the most popular opera-tion model for tutoring centers. While this model is

26 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

especially convenient for students, it can often result in low tutor utilization.

Problem statement: Tutoring utilization for walk-in tutoring has historically been quite low. For the Spring 2015 semester utilization was 37.7%, 44.5% for Fall 2015, and 17.4% in Spring 2016. The coordinator schedules tutors at 75% of the historical demand for the walk-in shifts, but this has resulted in low utilization. A new model is needed to improve tutoring utilization and reduce sal-ary costs for idle tutors.

Goals: The purpose is to improve the utilization of walk-in tutors at the university. Key project goals include: understanding the factors that contribute to tutor utiliza-tion, establishing appropriate tutor utilization goals, and improving the tutor scheduling process.

Scope: The processes included in this study are: hiring tutors; scheduling tutors; managing walk-in tutoring appointments; and collecting tutoring visit, work, and customer satisfaction data. This project excludes student athletes and students with disabilities, unless a tutor sched-uled for walk-in sessions tutors them during a scheduled shift. Baseline metrics were developed based on data from the Spring 2015, Fall 2015, and Spring 2016 semesters. Data was collected and improvements were implemented to assess increases in tutor utilization in Fall 2016.

The CTS criteria for the tutoring processes determined by the team are:

• Tutor utilization: total tutoring time divided by total tutor scheduled time.

• Student wait time: time students wait for their walk-in tutoring session to begin.

The stakeholder analysis identifies the project stakeholders, their role in the project, their potential impacts and concerns, and their initial and future receptivity to the project. This analysis is an important tool for identifying and engaging the appropriate stakeholder groups and ensuring that their support is gained by the end of the project. There were three key primary stakeholder groups: tutoring coordinator—representing the tutoring depart-ment administration, students who are tutored, and the tutors who provide student tutoring during the walk-in appointments.

The tutoring coordinator hires tutors, staff, and sched-ules the tutors for both walk-in tutoring and appointments. This person manages the walk-in visits as well. The tutoring coordinator is mainly concerned with tutor utilization that contributes to maintaining the department budget. In the past,

the tutoring coordinator hired a high volume of tutors who were not highly utilized, which contributed to at least a 50% higher volume of tutors.

The students to be tutored included those who arrived with-out an appointment to request tutoring. They were mainly concerned with having a low wait time and gaining knowledge of the subject matter. The tutor stakeholder group were the tutors who provided tutoring and were primarily concerned with help-ing students learn the subject matter and getting paid to do so. The tutoring coordinator was highly supportive of the project, having reached out to the LSS experts for guidance. The students who were tutored were unaware of the special LSS project; there-fore, they were neutral stakeholders from a project-engagement perspective. The tutors were moderately supportive of the LSS project. Both the tutors and the tutoring coordinator needed to be strong supporters of the project by the time the improvements were implemented.

The team applied a project risk analysis to assess any risks that existed, which could derail the successful implementation of improvements to the tutoring processes. The only risk identi-fied was in the ability to perform the appropriate measurement system analysis to assess data accuracy. This was an important element of ensuring that the tutors recorded the data in an unbi-ased and complete manner. The tutoring coordinator reviewed and assessed the accuracy of the data and removed inaccurate or incomplete data as appropriate.

The SIPOC diagram, shown in Figure 1, identifies needed improvements to the major activities of the processes, along with the suppliers and their inputs to the activities, the outputs of the process activities, and the customers of the inputs. It provides a check and balance to the stakeholder analysis to identify all appropriate stakeholders and validate the scope of the processes to be improved.

The team identified the key milestones and activities to ensure that the project activities would be completed.

Define phase activities:

• Create project charter, plan, and stakeholder analysis.

• Perform stakeholder analysis and identify CTS characteristics.

• Select team and launch project.

Measure phase activities:

• Define the current process and voice of process (VOP).

• Validate measurement system.

Analyze phase activities:

• Develop cause and effect relationships.

• Determine and validate root causes.

27 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

Improve phase activities:

• Design future state.

• Establish performance targets and project scorecard.

• Gain approval to implement, train, and pilot.

Control phase activities:

• Implement improvement recommendations and manage change.

• Incorporate process control plans and scorecards.

• Implement continuous improvement cycle: plan, do, check, act (PDCA).

Measure PhaseThe data collection plan identifies and defines the metrics for

measuring the CTS characteristics that are important to the cus-tomers and processes. The metrics for the two CTS characteristics were identified as tutor utilization percentage and average wait time. Tutor utilization was calculated as the total tutoring time divided by the total tutoring scheduled time. The average wait time was the average time from when the students signed in to when the tutor-ing session began. The data collected was from an existing tutoring database for the Spring 2015, Fall 2015, and Spring 2016 semesters.

The team developed process maps for each of the customer-facing activities in the SIPOC tool, with an example of one of them, walk-in tutoring, shown in Figure 2. This unique, process-architecture map tool combines the process flow of the activities with the role that performs each activity, the documents and information systems used within each activity, and additional knowledge that is important to capture to help perform the pro-cess accurately and consistently. The process map can be used as a training and improvement tool. (Furterer, 2017)

For this particular process, when the student arrives to the tutoring center, the Customer Service Associate (CSA) screens the person to determine his or her tutoring need and whether the student possesses the appropriate materials (e.g., textbook, class notes) to commence the tutoring session. If the student is not prepared, he or she is sent to obtain the materials and return later. The CSA also verifies that a tutor is available. If a tutor is available, the tutoring session begins. If a tutor is not avail-able, the student waits until the tutor is available. If the tutoring session extends past 45 minutes and then 60 minutes, an auto-mated reminder is sent to the tutor, and the tutoring manager performs a debrief with the tutor. Learning of the subject matter typically occurs in 45 minutes or less. If the session lasts longer, the student may simply be trying to complete his or her home-work assignment, and no additional subject-matter knowledge is being transferred. When the tutoring session is complete, the tutor swipes the student out, which shows the tutor as available and the customer-satisfaction log is completed by the student.

To collect the VOP data, the Master Black Belt performed the statistical analysis on the tutoring data collected from the TutorTrac data management system. Each visit included tutee demographics and tutor visit data, including gender, ethnicity, nationality, college, major, GPA, athlete type, tutoring type, sub-ject, tutor time in and out, tutor total time, and number of visits this semester for each student.

Additionally, the Learning Initiatives Coordinator included each tutor’s scheduled hours. The baseline for tutor utilization was calculated as:

(total tutoring time) (total scheduled time)

In Spring 2015 and Fall 2015, the tutoring utilization per-centage ranged from 37.7% to 44.5%.

Suppliers Inputs Process Outputs Customers

Students to be tutored, students to be hired for tutoring, and tutoring staff

Student qualifications, student applications, need for tutoring, historical tutoring utilization, and work data

Hire tutors Hired tutors Tutoring staff, tutors

Tutoring staff and tutors Need for tutoring, historical tutoring utilization, and work data

Schedule tutors Tutoring work schedule Tutoring staff, tutors

Students, tutors, and tutoring staff

Students with need for tutoring by class

Manage walk-in tutoring

Tutored students Tutoring staff, tutors

Students, tutors, and tutoring staff

Tutored student data and tutor work data

Collect tutoring data Tutor work data, customer satisfaction survey, and tutor visit data

Tutoring staff

Figure 1: SIPOC Diagram

28 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

Tutor utilization decreased to 17.4% in Spring 2016 due to replacing graduating tutors. The new tutors tended to be less productive than the more experienced and older tutors.

Analyze PhaseThe team investigated the impact of class on the mean time

of visit as well as number of visits, which are shown in Figure 3. Freshmen have a higher mean time of the tutoring visit and a higher number of visits for walk-in tutoring. Sophomores also have a higher number of walk-in tutoring visits. These trends were expected since most of the courses supported are for fresh-men and sophomore students.

Some other interesting findings in the Fall 2016 tutoring data included:

• The average tutoring time for the sessions tended to decrease with an increase in the students’ GPA, and there were more visits from those with a GPA between 3.0 and 3.49:• GPA of < 2.0: mean time of visit = 63.9 minutes, 52 visits• GPA of 2.0 to 2.49: mean time of visit = 55.3 minutes,

143 visits• GPA of 2.5 to 2.99: mean time of visit = 59.8 minutes,

298 visits

• GPA of 3.0 to 3.49: mean time of visit = 59.1 minutes, 585 visits

• GPA of > 3.5: mean time of visit = 55.0 minutes, 376 visits

• The average tutoring time was fairly consistent by college/school, and number of visits was as follows:• Arts & Sciences: mean time of visit = 58.6 minutes, 563 visits• Business: mean time of visit = 57.3 minutes, 365 visits• Education: mean time of visit = 57.2 minutes, 190 visits• Engineering: mean time of visit = 58.2 minutes, 335 visits

1

1

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3

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Role

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ivity

Doc

umen

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/M

ethod

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Textbooks/class notes

Verify student is prepared

Student ID feedback formIntake form

Feedback formIntake form

Tutor cycle process

Session goals Customer satisfaction

Google formTutor roster(Excel)

Tutor roster(Excel)

Tutor roster(Excel)

Time in courseWait time

TutorTracTutorTrac

Start wait time

Start 2

2

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materials

45-minutereminder

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Show tutor as

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Assigntutor Tutoring

Swipestudent intoTutorTrac

Swipestudent outof TutorTrac

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Appt. > 60min.?

CSA CSA

CSA CSACSA CSA

TutorTutor Mgr. Tutor Mgr./TutorTutee

Yes Yes

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No No

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Figure 2: Process Map for Walk-In Tutoring

Figure 3: Mean Time of Visits and Number of Visits by Class for Fall 2016

50

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29 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

• The number of visits by specific tutors varied from nine to 57. The average tutoring time also varied by tutor from 51.6 to 81.8 minutes. This demonstrates that there is quite a bit of variability in the tutor practices and their ability to tutor across different subject matters.

• The number of visits and mean time of the visit were higher for women (895 visits, 58.2 minutes) compared to male stu-dents (559 visits, 57.6 minutes).

• The number of visits varied by week of the semester, most likely aligning to exam and assignment schedules.

• Math had the highest number of visits for Fall 2016 with 904 visits, followed by chemistry with 316, constituting 84% of the visits for walk-in appointments.

• The number of visits was statistically significant, at an alpha of 0.10, for:• Class• College• Nationality• Ethnicity• GPA• Week of semester• Interaction of gender and class• Interaction of gender and GPA• Interaction of gender and week of semester

The team performed a why-why analysis, shown in Figure 4, on the question, “Why is tutor utilization low?” and identified

Not understandingfactors thatcontribute to

need for tutoring

Not collectingdetailed tutoringand work data

Not consideringbest practices

Changes inuniversity class

schedule

No limit on tutoring

appointmentlength

Current spaceavailability

Selected tutoringapproach

Reduced tutoringhours

No incentive toreduce budget

Low-volumecourses offered

at walk-in

Athleticdepartment thought

they neededdedicated tutors

Separate tutorpool for athletic

department

Overstaf�ng

Why is tutorutilization low?

Athleticdepartment pays

for tutoringservices

Why?

Why?

Why?

Why?

Why?Why?

Why?

Why?

Why?

Why?

Why?

Why?

Why?

Figure 4: Why-why Diagram

30 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

the following root causes: changes in university class schedule, not considering best practices, and no incentive for reducing budget. During the Measure phase, it became apparent to collect detailed utilization, work, and wait-time data.

Improve PhaseThe team brainstormed improvement ideas and performed

a Quality Function Deployment (QFD) House of Quality, shown in Figure 5. The QFD House of Quality ensured that the improvement recommendations were prioritized and aligned with the CTS criteria.

The team generated the following improvement ideas that positively impact the CTS of tutor utilization, with the root causes in parentheses:

• Revise scheduling approach: Incorporate hybrid model using tutors for walk-ins and appointments (Root cause: no incentive to reduce budget).

• Investigate strategies for assigning tutors to clients (Root cause: no incentive to reduce budget).

• Monitor daily or weekly utilization of individual tutors (Root cause: not collecting detailed tutoring and work data).

• Identify course portfolio preferences for tutor hiring (Root cause: not understanding factors that contribute to need for tutoring).

• Identify tutoring location that will allow for expanded hours (Root cause: changes in university class schedule).

One way to increase tutor utilization is to allow scheduled appointments during walk-in tutoring hours. With this hybrid model, tutors would meet with tutees at walk-in tutoring when they are not meeting with students who had previously sched-uled an appointment. Allowing appointments during walk-in times may also assist in appropriately forecasting demand and adjusting staffing needs.

The team plans to investigate strategies for assigning tutors to students during walk-in hours. The current assignment policy prioritizes scheduling tutors with the smallest course profile over tutors with the largest course profile. This means tutors with larger course profiles are likely underutilized compared to tutors who support only a few courses. In a related project, different strategies for the assignment process to identify opportunities for further improvement are being investigated.

To improve scheduling efficiency, it may be helpful to cre-ate desired course portfolios to assist in the hiring process. For example, it may be desirable for students who are able to tutor the calculus sequences to also provide tutoring for chemistry and physics courses.

Currently, walk-in tutoring takes place in a location that does not become available until 6:30 p.m. Based on historical data, students prefer earlier tutoring times. Therefore, it may be beneficial to identify other spaces on campus that would allow walk-in tutoring to begin earlier in the day.

Control PhaseIn the Control phase, the team developed a control plan to

maintain new process improvements. The following process steps that need to be controlled and their control mechanism are provided.

• Hire tutors: Hire based upon critical tutor visit factors, measured by tutor utilization.

• Schedule tutors: Implement statistical process control charts to measure tutor utilization on a daily basis.

• Manage walk-in tutors: Implement statistical process con-trol charts to measure wait time on a daily basis.

• Collect tutor data: Ensure tutoring visit and work data is col-lected weekly as measured by tutor utilization and wait times.

The actions to be taken if the process is out of control is to investigate assignable causes and correct the process as required. The control plan owner is the tutoring coordinator.

The following improvements, based on a scheduling approach, were implemented in the Fall 2016 semester:

• Reduced the number of classes for walk-in tutoring to focus on high-volume courses.

Figure 5: Quality Function Deployment House of Quality

10 9 9 9 9 97 3 3 3 1

Absolute weight 111 111 90 111 97

Relative weight 1 1 5 1 4

Impo

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31 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

• Incorporated a hybrid scheduling approach, using the tutors for walk-ins and appointments during the same time.

The Fall 2016 utilization was 62%, a significant improvement from the prior semesters, as shown in Figure 6. This resulted in an 18% to 45% improvement compared to previous semesters.

Conclusions and Future WorkThe LSS project was successful in improving tutor utiliza-

tion for the Office of Learning Resources Tutoring Center. The department plans to incorporate continuous process improve-ment in the future. This case study can be used as a guide for other HEIs that would like to improve processes, enhance qual-ity and efficiency, and reduce costs of providing services in higher education.

The team will investigate and implement the following improvements in the future.

• Investigate strategies for assigning tutors to clients. Currently, the assignment of tutors is done first for those who have skills for tutoring fewer subjects, negatively impacting the utilization of tutors who can work across more subjects. Different approaches would be designed and tested. A pos-sible strategy would be to assign tutors so that the average and variance of the individual tutor utilization are considered when assigning tutors, instead of just which subject areas they can tutor. The next improvement idea would help facilitate the understanding of the average and variance of individual tutors’ utilization.

• Monitor weekly utilization of individual tutors via statistical process control. Individual, moving-range control charts would be used to ensure that tutors maintain an “in control” utilization for the days they are working related to their tutoring utilization,

both for their average and variation. The quality character-istic would be to measure individual tutor utilization as the number of hours spent tutoring divided by the scheduled tutor hours. The current metric aggregates actual tutoring hours and scheduled hours across all of the tutors for an entire semester. There would be value in understanding the utilization for each tutor on a weekly basis.

• Identify course portfolios preferences for tutor hiring. When hiring tutors, consider the portfolio of courses that they can tutor and hire based on the historical and proposed course needs. This would require aligning with the course schedules and needs of the professors and students. A new process for defining tutoring requirements each semester would need to be developed using historical data available.

• Identify tutoring location that will allow for expanded hours. Currently, the tutoring location is also used as a classroom, and tutoring cannot start until 6:30 p.m. The tutoring department would like to look for a new location that is not restricted by the class schedule and where tutoring can begin earlier in the day.

The department also plans to share the success of this project with other departments to help promote the value of LSS meth-ods and tools in higher education. The department manager is extremely satisfied with the results of this study and has already requested a new LSS project to improve the hiring and training process for more than 200 student-employees.

References:Adina-Petruţa, P., & Roxana, S. (2014). Integrating Six Sigma with quality management systems for the development and continuous improvement of higher education institutions. Procedia - Social and Behavioral Sciences, August 14, 2014, 143, 643-648.

Al Kuwaiti, A., & Subbarayalu, A. (2015). Appraisal of students experience survey (SES) as a measure to manage the quality of higher education in the Kingdom of Saudi Arabia: An institutional study using Six Sigma model. Educational Studies, 41(4), 430-443.

Akinrefon, T., Furterer, S., Battikhi, A., Coowar, R., Ferreras, A., Gibson, K., Lakkoju, R., & Meza, K. (2005). The use of a balanced scorecard in a Six-Sigma academia improvement project. Proceedings of the 12th Annual International Conference on Industry, Engineering and Management Systems, Cocoa Beach, FL.

Antony, J. (2015). Editorial note for the special issue on Lean Six Sigma for higher education. International Journal of Quality & Reliability Management, 32(9), 924.

Figure 6: Tutor Utilization Percentage

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Bandyopadhyay, J. (2014). A framework for design, development, and delivery of high quality on-line higher education program in the U.S using Six Sigma approach. Journal of Business and Behavior Sciences, 26(3), 43.

Balzer,W., Brodke, M., & Kizhakethalackal, E. T. (2015). Lean higher education: Successes, challenges, and realizing potential. International Journal of Quality & Reliability Management, 32(9), 924-933.

Coowar, R., & Furterer, S. (2006). Lean Six Sigma as an improvement tool in academia. Proceedings for American Society for Engineering Education Conference, Huntsville, AL.

Douglas, J., Antony, J., & Douglas, A. (2015). Waste identification and elimination in HEIs: The role of Lean thinking, International Journal of Quality & Reliability Management. 32(9), 970-981.

Furterer, S. (2017). Using a process map to create a process archi-tecture. Presentation at the ASQ World Conference on Quality and Improvement, Charlotte, NC.

Furterer, S. L., Coowar, R., Akinrefon, T., Banjan, P., Battikhi, A., Champney, R., & Cholvanich, T. (2005). Framework development using Six Sigma and quality tools to achieve operational excellence in higher educa-tion. Proceedings of the American Society for Engineering Management National Conference, Virginia Beach, VA.

Furterer, S. L., & Crumpton-Young, L. (2005). Application of Six Sigma service experiential learning opportunities within engineering education. Proceedings of the 2005 American Society for Engineering Education Annual Conference, Virginia Beach, VA.

Furterer, S. L., Djaho, A., Hartley, J., Kaufmann, J., Millan, A., Ollikainen, K., & Uskert, A. (2006a). Six Sigma approach to improve the faculty accreditation process at the University of Central Florida. Proceedings of the 12th Annual International Conference on Industry, Engineering and Management Systems, Cocoa Beach, FL.

Furterer, S., Hussian, B., McMurray, S., Rowe, P., & Smith, M. (2007). Improving the recruiting of university students through application of Six Sigma DMAIC methodology and tools. Proceedings of the 2007 International Conference on Industry, Engineering, and Management Systems, Cocoa Beach, FL.

Furterer, S., Schneider, K., Key, M., & Zhang, Y. (2017). A Lean Six-Sigma approach for improving utilization of walk-in tutors. Proceedings of the Fourth International Conference on Lean Six Sigma for Higher Education, West Lafayette, IN.

Furterer, S. L., Sharawi, A., Casanas, C., Londe, G., Linde, L., & Ahram, T. (2006b). Six Sigma project – Improving web development and design processes. Presentation at the 12th Annual International Conference on Industry, Engineering and Management Systems, Cocoa Beach, FL.

Jenness, J., Ederer, N., Ferris, J., Vialet, J., Vicens, M., Gaumier, A., & Furterer, S. L. (2006). Six Sigma approach to improve national panhellenic conference recruitment at the University of Central Florida. Presentation at the International Conference on Industry, Engineering and Management Systems, Cocoa Beach, FL.

Martinez, F., Beaver, R., Goapal, V., D’Angelo, R., Torrejon, M., Shah, A., & Furterer, S. L. (2006). Six Sigma methods for the improve-ment of an asset management process at the University of Central Florida. Presentation at the International Conference on Industry, Engineering and Management Systems, Cocoa Beach, FL.

Nahmens, I., Furterer. S., Bernardinez, M., Buradha, K., Cochie, K., Saenz, J., & Unlu, K. (2005). Integrated Six Sigma and lean approach to improve graduate student management program in industrial engineer-ing advanced academics. Proceedings of the 11th Annual International Conference of Industry, Engineering, and Management Systems, Cocoa Beach, FL.

Rodrigues, F., Schoen, H., Mehta, A., Schwartz, E., Lloyd, T., Tu, Y., & Furterer, S. L. (2006). Designing a Six-Sigma-based process management model to achieve operational excellence at the University of Central Florida. Presentation at the International Conference on Industry, Engineering and Management Systems Conference, Cocoa Beach, FL.

Sharawi, A., Shah, A., Rajendran, M., & Furterer, S. (2007). Applying Six Sigma tools to improve WebCT course development and design pro-cesses. Proceedings of the 2007 International Conference of Industry, Engineering and Management Systems, Cocoa Beach, FL.

Sharma, R., Furterer, S., Blanc. J. P., Chovanich, T., Hatcher, H., Kittirattanapaiboon, Morton, S., & Nagarajan, R. (2005). Florida engi-neering education delivery system opportunity for improvement phase II. Presentation at the International Conference of Industry, Engineering and Management Systems, Cocoa Beach, FL.

Svensson C., Antony, J., Ba-Essa, M., Bakhsh, M., & Albliwi, S. (2015). A Lean Six Sigma program in higher education. International Journal of Quality & Reliability Management, 32(9), 951-969.

Tetteh, G. (2015). Improving learning outcome using Six Sigma meth-odology. Journal of International Education in Business, 8(1), 18-36.

Thomas, A., Antony, J., Francis, M., & Fisher, R. (2015). A com-parative study of lean implementation in higher and further education institutions in the UK. International Journal of Quality & Reliability Management, 32(9), 982-996.

Waterbury, T. (2015). Learning from the pioneers: A multiple-case analysis of implementing Lean in higher education. International Journal of Quality & Reliability Management, 32(9), 934-950.

33 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

Sandra Furterer, Ph.D., is an associate pro-fessor at the University of Dayton in the Department of Engineering Management, Systems and Technology. She recently returned to academia from industry where she served as a vice president of process transformation for Park National Bank in Columbus, Ohio. Furterer has more than 25 years of experience in business process and quality improvement. An ASQ Fellow, she is also an ASQ certified Six Sigma Black Belt, Quality Engineer, and Six Sigma Master Black Belt. Furterer is the author or co-author of four reference text-books on Lean Six Sigma, Design for Six Sigma and Lean Systems. For more informa-tion, send an email to her at sfurterer1@udayton.edu.

Kellie Schneider, Ph.D., is an assistant profes-sor in the Department of Engineering Management, Systems, and Technology at the University of Dayton (UD). Prior to joining the faculty at UD, she was an instructor in the Freshman Engineering Program at the University of Arkansas. Schneider has a vari-ety of research and scholarship interests including quality and reliability, engineering education, and community-based operations research. She is a member of IISE, INFORMS, and ASEE. Contact Schneider via email at kschneider2@udayton.edu.

Michael B. Key, M.A., is the Learning Initiatives Coordinator in the Office of Learning Resource at the University of Dayton. In addition to coordinating tutoring support for the university, he also manages and teaches a developmental learning course, coupled with academic coaching support, for students on academic probation. Key’s schol-arly interests include organizational research and leadership, inquiry-based learning, and literature as a mode of social criticism. He is a contributing member of the College Reading and Learning Association. Contact Key at mkey01@udayton.edu.

Yusheng Zhang is a graduate student in the department of Engineering Management, System, and Technology at University of Dayton. His email address is zhangy66@udayton.edu.

Sandra Furterer

Kellie Schneider

Michael B. Key

Yusheng Zhang

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Quality Approachesin EducationUnderstanding the

cross-departmental

role of IT in

the design and

implementation of

quality initiatives in

higher education

Exploring the Role of Information Technology Leadership in Higher Education: Implications for Total Quality ManagementLouis Hickman and Mesut Akdere

AbstractThe current shortage of highly skilled employees across the country continues to be a concern for higher education institutions facing flat and decreasing funding. Information technology expands the reach of education via distance education, simulation technol-ogy, massively open online courses, and more. Information technology departments are responsible for identifying transformational change opportunities, implementing tech-nologies that expand the reach of universities, and operating efficiently with flat funding. Identifying effective information technology leadership practices to enable change and reduce costs is vital for modern higher education institutions. Utilizing a literature review, existing findings and gaps are identified in information technology leadership research before relating those findings to Total Quality Management. Transformational leadership may help counteract the forces in higher education that resist change. Information tech-nology leaders are uniquely positioned because they have both information technology and higher education knowledge, enabling them to serve as invaluable partners as higher education institutions attempt to provide value in a rapidly changing world.

KeywordsInformation Technology, Leadership, Higher Education, Total Quality Management

IntroductionLeadership is widely recognized as the most important element in Total Quality

Management (TQM) success. Information technology (IT) is similarly important because it helps to generate the information for making data-driven, quality decisions and for managing and updating business processes. Leadership in the IT context can be essential for TQM success. IT leaders are uniquely positioned because their work is poorly understood by much of the university, but that work can be vital to establishing and maintaining a competitive advantage (Bhatt, Grover, & Grover, 2005). Business knowledge is one of the most widely studied antecedents to IT value generation (cf. Reich & Benbasat, 2000). In the higher education (HE) context, business knowledge means that IT leaders must understand how to drive both faculty and administrative success. With adequate business knowledge, IT leaders have the potential to serve as partners who understand the levers of the wider university and can collaborate on projects that increase the efficiency of the university.

Of Deming’s 14 points for TQM (Kanji, 1990), IT leadership is, by nature, directly involved in instituting leadership, driving out fear, and breaking down barriers. Collaboration and communication are necessary for any IT solution to benefit the insti-tution. IT continues to increase in importance in HE as universities expand their use of massively open online courses, simulation technology, big data, and distance education. Additionally, many efficiency gains in HE processes are due to IT systems eliminating existing bureaucratic, labor-driven job processes by replacing them with innovative lean systems. Considering the importance of leadership for both TQM and IT, the funding

FOCUS AREA: HIGHER EDUCATION

35 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

challenges facing HE institutions, and general societal upheaval, the leadership behaviors that demonstrate a commitment to quality and an ability to enable technological change are vital for the future success of HE.

Leadership in Higher EducationThe future of HE is considered a part of global competitive-

ness as emerging economic powers increase their investment in HE. As such, it has been suggested that the future of HE in the United States is reliant on leadership that enables productive and change-capable organizational cultures (Fullan & Scott, 2009). The HE leadership research has missed opportunities by failing to investigate how leadership can create change, provide orga-nizational direction, and support organizational effectiveness (Kezar, Carducci, & Contreras-McGavin, 2006). One con-tributor to this shortcoming is that public HE faces governance barriers to change due to public oversight that may resist change (Leih & Teece, 2016). Adaptive, change-oriented organizational cultures cannot be created in a traditional, hierarchical fashion focused on management. Rather, a collective, collaborative, and team-oriented style of leadership has become increasingly necessary as HE faces growing challenges (Kezar, Carducci, & Contreras-McGavin, 2006).

The emphasis on collaboration is important because one or two persons cannot solve the problems HE faces today. Previously, funding was expected to increase continuously along with tax revenues. Today, tax revenues are flat in many states while, simultaneously, public HE serves more students than ever. HE leaders must bring stakeholders together from both inside and outside of their institutions. Simply pulling together a group of people with different agendas, perceptions, and skills can be key for transformational change in HE (Padró, 2010). Establishing collaborative efforts is likely to require social capital (Bolden, Petrov, & Gosling, 2008), which is developed by creat-ing connections with the leadership throughout the institution. Voluntary coordination and collaboration with stakeholders has been proposed as the solution to the IT-business gap because it develops trusting relationships and improves organizational agil-ity (Hickman & Akdere, 2017a). Our attention now turns to how IT is positioned to tackle the challenges facing HE leadership.

Information Technology LeadershipTransformational leadership (TL) is comprised of the four

I’s: idealized influence, inspirational motivation, individualized consideration, and intellectual stimulation (Bass & Avolio, 1990). TL is one of the most widely explored leadership types (Day, Fleenor, Atwater, Sturm, & McKee, 2014; Akdere, 2015b; Top, Akdere, & Tarcan, 2015), and it is the most commonly studied

leadership style in the IT context (Hickman & Akdere, 2017b). TL is especially important in gaining employee commitment in the non-profit context (Rowold, Borgmann, & Bormann, 2014). Leadership, rather than management, is particularly important for IT because expertise is distributed and requires collabora-tion to combine into valuable solutions, much like improving the HE organization. For this very reason, Hill (1992) argued that leadership is a vital dimension to consider when assessing technical professionals. Leadership is important for technology adoption in the HE context (Keengwe, Kidd, & Kyei-Blankson, 2009), a key component of any IT-enabled change. TL would help gain employee commitment to change because employees would be considered in the process, influenced individually to become motivated to perform in the new way of working, and stimulated by the challenge.

While it has been argued that chief information officers widely practice TL because it enables organizational trans-formation (McLean & Smits, 2014), the HE context faces additional barriers. While TL practices have been found to be high among IT executives in HE, IT employees do not consider the climate conducive to innovation (Katz & Salaway, 2004). The additional barriers faced in HE limit the transformational change that IT can create. Considering that HE context limits the ability of TL to create an innovative environment for IT, we must seek out another concept that mediates the relation-ship. IT-enabled change and improvements require extensive coordination and collaboration at all levels of the organization, which both necessitates and engenders senior executive support from non-IT management (Campbell, Kay, & Avison, 2005). IT units in the HE context can expect that their environments will only be transformative if the high-ranking members of both the academic and administrative sides of the institution support the innovative efforts. Additionally, IT must have collaborative and synergistic (Nevo & Wade, 2010) relationships with partners throughout the institution. Consequently, we suggest the follow-ing propositions for future empirical studies to further explore this phenomenon (as illustrated in Figure 1):

Figure 1: Proposed Relationships Between Transformational Leadership and Innovation in Higher Education Information Technology

Collaborative relationships

InnovationTL leadershipTop management

support

36 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

Proposition 1: The impact of TL on innovation in the HE context is mediated by the extent of collab-orative relationships IT has with the rest of the institution.

Proposition 2: The impact of TL on innovation in the HE context is mediated by the amount of top man-agement support IT receives, both from the academic and administrative segments of the institution.

Implications for TQMMuch of the focus of this article has been on collaboration

in one form or another. The HE problems of the 21st century are too big for one person to solve alone. For nearly 30 years, TL has been identified as important for TQM success. In fact, it is an integral component of the Education Criteria of the Malcolm Baldrige National Quality Award (Akdere, 2015a) in terms of leading the quality management process for the purpose of achieving business excellence. The TQM process is a collective effort requiring effective action leading to both behavioral and cultural change on behalf of organizational members.

Zairi (1991) argued that TQM is a bottom-up activity enabled by modern leadership’s emphasis on participatory deci-sion making and employee involvement. He further argued that charismatic leadership, the idealized influence and inspirational motivation dimensions of TL, is important for gaining commit-ment to TQM. Similarly, when analyzing a series of cases, Zairi (1994) identified several factors important for success in TQM implementation, including setting and communicating a vision, recognizing people as assets, developing a process-based culture, developing partnerships, and engaging in internal leader devel-opment. Setting and communicating a vision is a component of both charismatic leadership dimensions. Individualized con-sideration can only occur once people are recognized as valuable assets. Intellectual stimulation focuses on helping followers to constantly re-examine the methods and processes used at work (Bass & Avolio, 1990), ask-ing them to focus on the means used to achieve ends. Inspirational motivation does not apply only to follow-ers—TL leaders also develop partnerships to attain their visions of the future. And, finally, if TL can show the way to a more participative and process-oriented work-place, that will develop a pipeline of future leaders who follow those same behaviors.

IT leadership is directly involved in three of Deming’s 14 points for management. Instituting leadership can be accomplished from the IT perspective by the collabora-tive behaviors already identified as important. The goal

of IT is to help people, machines, and processes in institutions to do better work. This is accomplished by automating processes, providing additional information for decision making, and cre-ating better tools for connecting the people in and outside of HE institutions. A participative and collaborative set of IT leaders will, by forming a diverse set of relationships, help individuals understand how IT can help drive quality in their departments. TQM provides a systematic way for effective decision-making processes (Akdere, 2011) that are critical in IT operations.

Driving out fear and breaking down barriers are highly interrelated because they both rely on interdepartmental com-munication. Effective IT leadership must create synergistic relationships with non-IT units because IT’s functions directly impact all areas except for IT. The only way that IT is affected by its work is through the skills and expertise required to develop and maintain solutions. The solutions change the relationship the HE institution’s stakeholders have with IT. Specifically, IT changes the way employees work, suppliers coordinate with IT, and how students apply for and study at an HE institution. Learning-management systems are nearly universal, demand for online courses and degrees continues to increase, and most students manage their administrative relationships (e.g., tuition payments, class scheduling, and transcript requests) with the university through online systems. Breaking down barriers is necessary to drive out fear, and the IT units in universities are uniquely positioned to accomplish these changes. Figure 2 depicts the relationships to Deming’s points for management.

Conclusions and Future ResearchIT leadership, especially that which fits the mold of TL, is

uniquely positioned to help HE improve quality. The distinct position of the IT function provides the cross-departmental vision that is difficult to find elsewhere. HE institutions should

Figure 2: IT Leadership Processes and Impact on Deming’s Points for Management

IT leadership

Information for decision making

Institute leadership

Automate processes Driving our fear

Synergistic relationships

Breaking down barriers

IT contributing processes

Affected points for management

37 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

ensure that IT leadership is involved in designing and imple-menting quality initiatives. Researchers should examine the impact of effective leadership not just of whoever is managing the initiatives, but they must also investigate how leadership from key IT employees can help those initiatives succeed.

Future research should examine the impact that TL leadership within IT has on HE TQM efforts. Specifically, cross-sectional data should be collected to examine whether TL’s relationship to innovation is mediated by the extent of collaborative relation-ships between IT and the rest of the university and the amount of top-management support IT receives. Many of the necessary leadership behaviors identified as important for TQM may be fulfilled by transformational IT leaders, so IT leadership may be able to help with quality efforts, even if innovation is inhibited by HE culture.

References:Akdere, M. (2011). An analysis of decision making process in organiza-tions: Implications for quality management and systematic practice. Total Quality Management and Business Excellence, 22(12), 1,317-1,330.

Akdere, M. (2015a). Malcolm Baldrige National Quality Award. In S. M. Dahlgaard-Park (Ed.). The Sage Encyclopedia of Quality and the Service Economy, 383-385. Thousand Oaks, CA: Sage Publications.

Akdere, M. (2015b). Transformational leadership. In S. M. Dahlgaard-Park (Ed.). The Sage Encyclopedia of Quality and the Service Economy, 819-822. Thousand Oaks, CA: Sage Publications.

Bass, B. M., & Avolio, B. J. (1990). Developing transformational leadership: 1992 and beyond. Journal of European Industrial Training, 14(5), 21-27.

Bhatt, G. D., Grover, V., & Grover, V. (2005). Types of information technology capabilities and their role in competitive advantage: An empirical study. Journal of Management Information Systems, 22(2), 253-277.

Bolden, R., Petrov, G., & Gosling, J. (2008). Tensions in higher edu-cation leadership: Toward a multi-level model of leadership practice. Higher Education Quarterly, 62(4), 358-376.

Campbell, B., Kay, R., & Avison, D. (2005). Strategic alignment: A practitioner’s perspective. Journal of Enterprise Information Management, 18(6), 653-664.

Day, D. V., Fleenor, J. W., Atwater, L. E., Sturm, R. E., & McKee, R. A. (2014). Advances in leader and leadership development: A review of 25 years of research and theory. The Leadership Quarterly, 25(1), 63-82.

Fullan, M., & Scott, G. (2009). Turnaround leadership for higher educa-tion. Hoboken, New Jersey: John Wiley & Sons.

Hickman, L., & Akdere, M. (2017a). Integrated review of stakeholder theory: Implications for technology adoption and training. Proceedings of the Academy of Human Resource Development International Research Conference in the Americas, San Antonio, TX.

Hickman, L., & Akdere, M. (2017b). Development of effective IT leadership behaviors: A review. Proceedings of the Midwest Association for Information Systems Annual Conference, Springfield, IL.

Hill, R. B. (1992). Dual career paths: Recognizing the technical con-tributor. Journal of Compensation and Benefits, 4(1), 10-16.

Kanji, G. K. (1990). Total quality management: The second industrial revolution. Total Quality Management, 1(1), 3-12.

Katz, R. N., & Salaway, G. (2004). Information technology leadership in higher education: The condition of the community. EDUCAUSE Center for Applied Research (white paper). Retrieved from https://www.educause.edu/ir/library/pdf/ERS0401/ekf0401.pdf.

Keengwe, J., Kidd, T., & Kyei-Blankson, L. (2009). Faculty and technol-ogy: Implications for faculty training and technology leadership. Journal of Science Education and Technology, 18(1), 23-28.

Kezar, A. J., Carducci, R., & Contreras-McGavin, M. (2006). Rethinking the” L” word in higher education: The revolution of research on leader-ship. ASHE Higher Education Report. Hoboken, New Jersey: John Wiley & Sons.

Leih, S., & Teece, D. (2016). Campus leadership and the entrepreneurial university: A dynamic capabilities perspective. Academy of Management Perspectives, 30(2), 182-210.

McLean, E. R., & Smits, S. J. (2014). Management, leadership, and the roles of the CIO. International Leadership Journal, 6(1), 3-22.

Nevo, S., & Wade, M. R. (2010). The formation and value of IT-enabled resources: Antecedents and consequences of synergistic relationships. MIS Quarterly, 34(1), 163-183.

Padró, F. F. (2010). A leadership model for higher education quality. In Nair & Webster (Eds.), Leadership and Management of Quality in Higher Education, 37-54, Amsterdam: Elsevier.

Reich, B. H., & Benbasat, I. (2000). Factors that influence the social dimension of alignment between business executives and information technology objectives. MIS Quarterly, 24(1), 81-113.

Rowold, J., Borgmann, L., & Bormann, K. (2014). Which leadership constructs are important for predicting job satisfaction, affective com-mitment, and perceived job performance in profit versus nonprofit organizations? Nonprofit Management & Leadership, 25(2), 147-164.

Top, M., Akdere, M., & Tarcan, M. (2015). Transformational lead-ership, job satisfaction, organizational commitment, organizational trust in Turkish public hospitals: Public servants versus private sector employees. International Journal of Human Resource Management, 26(9), 1,259-1,282.

Zairi, M. (1991). Total Quality Management for Engineers, Cambridge, England: Woodhead.

Zairi, M. (1994). Leadership in TQM implementations: Some case examples. The TQM Magazine, 6(6), 9-16.

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Louis Hickman, M.S., is Ph.D. student in tech-nology at Purdue University’s Polytechnic Institute. His research in human resource development focuses on the intersection of technology and people, including publications on information systems, leadership develop-ment, intercultural competence development, and quality management. Contact him at lchickma@purdue.edu.

Mesut Akdere, Ph.D., is an associate profes-sor of human resource development in the Department of Technology Leadership & Innovation at Purdue University, West Lafayette. He serves as the director of Purdue Polytechnic Leadership Academy helping STEM students develop their leadership competencies. Akdere is also the inaugural faculty research fellow at the Center for Intercultural Learning, Mentorship, Assessment, and Research at Purdue University. His research focuses on developing intercultural leadership competen-cies through simulated learning technologies, workforce development in STEM fields, quality management, and performance improvement through training and organization develop-ment. Akdere has been appointed to serve on the Board of Examiners for the Malcolm Baldrige National Quality Award program. For more information, contact him via email at makdere@purdue.edu.

Louis Hickman

Mesut Akdere

Beginning in 2013, the Quality Approaches in Education editors will announce an annual best paper award to the author(s) of a paper published in Quality Approaches in Education. �e award will be announced in January of each year for the best paper from the issues of the previous year and will be based on the largest single contribution made to the development or application of quality approaches in education. �ere is no nomination form for this award.Visit our website at asq.org/edu/quality-information/journals/ today!

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39 Quality Approaches in Education Vol. 8, No. 2

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Quality Approachesin Education FOCUS AREA:

HIGHER EDUCATION

Developing

innovative

partnerships for

low-enrollment

majors to address

reducing budgets

Collaborative Initiatives in Higher Education: A Case Study of Economics ProgramsCasey Abington

AbstractThe proportion of higher education funding in the United States provided by state govern-ments has been shrinking since the Great Recession when states were forced to make large cuts. In Missouri, tuition freezes were imposed along with a decrease in appropriations. Consequently, universities had to find creative ways to increase revenues while lowering costs. One such strategy was forming the Missouri Alliance for Collaborative Education (MACE), where universities collaborate through shared faculty resources. Participating universities offer different upper-level electives in which students at each university are able to enroll. The primary goal of the alliance is to reduce resources required to offer specific, low-enrollment majors. This article provides an overview of the MACE initiative in economics. First, the need for the collaboration is discussed. Next, the design and imple-mentation of the program is explained. Finally, the benefits and challenges are explored along with results and conclusions.

Keywords Higher Education, State Appropriations, Collaboration

IntroductionThe Great Recession had a dramatic impact on the budgets of state governments. Tax

revenue plummeted while the need for public welfare spiked. Although federal relief from the American Recovery and Reinvestment Act (ARRA) of 2009 helped offset some effects, states still struggled to balance budgets. As a result, state governments were forced to reduce spending to compensate for the lost revenues (Gordon, 2012). In most states, higher education funding was one area that suffered large cuts. For example, Arizona and Illinois have both cut higher education spending by more than half, with decreases of 55.6% and 54.0%, respectively, since 2008 (Mitchell, Leachman, and Masterson, 2016).

Prior to the recession, state funding for higher education was steadily growing. Figure 1 shows total state support for higher education across the United States from 2007 to 2017. It shows a clear upward trend followed by a considerable decline during the recession. Thirty-eight states spent more on higher education for the 2015-2016 school year than in the previous year (Mitchell et al., 2016).

According to a report published by the State Higher Education Executive Officers Association (SHEEO), state and local spending per student from 2010 to 2012 was the lowest in the past 25 years (SHEEO, 2015). More recently, state support for higher educa-tion has started to rebound, yet all states except four (Montana, North Dakota, Wisconsin, and Wyoming) are still spending less than before the recession (Mitchell et al., 2016).

Before the Great Recession, states provided more than 60% of funding for public higher education, while 35% came from tuition revenue, and the remaining 5% from local sources. By the end of the recession, however, the proportion of funding from states dropped to 50%, and the amount from tuition revenue climbed to 45% (SHEEO, 2015). With declining funding, institutions were forced to reduce spending, raise tuition, or find new sources of revenue. The severity of funding cuts differed across states and universities, as did the responses. Some eliminated programs or courses, hiked tuition, created fees, laid

40 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

off faculty and staff, required employee furloughs, or increased class sizes (Jones and Wellman, 2010).

Missouri, like other states, experienced a large decrease in state funding during the recession. Unlike the national average, however, Missouri state appropriations have remained essentially flat since and are still well below pre-recession levels as shown in Figure 2.

In addition to the severe funding cuts resulting from the reces-sion, four-year public universities in Missouri faced an additional budget hurdle. With a goal of keeping college education afford-able, the state government imposed tuition freezes for fiscal years 2010 and 2011, and has since allowed tuition hikes only as large as the increase in consumer price index (Hunn, 2009; MDHE, 2017). This was not common across states as many institutions compensated for the loss of funding by simply raising tuition and fees. Without the ability to increase revenues through tuition, public universities in Missouri were forced to find more creative solutions. During the 2010 Higher Education Summit, Missouri

Governor Jay Nixon stated that there must be fundamental changes in higher education. He asked universities to focus on four areas: attainment, academic program review, cooperation and collabo-ration, and funding (Nixon, 2010). Soon after his speech, the Missouri Alliance for Collaborative Education (MACE) pro-gram was proposed.

The next section describes the MACE initiative. Details of the MACE program in economics programs are then pro-vided. The benefits and challenges of the MACE program are discussed and results thus far are summarized. Finally, conclu-sions and future work are presented.

MACE InitiativeThe MACE program was devel-

oped in 2010 as a direct response to the recession-induced decline in funding for higher education in Missouri. Reduced state funding, combined with tuition freezes, required Missouri universities to find ways to utilize their resources more efficiently. The MACE program aligned with the governor’s third focus area— cooperation and collaboration. The ini-tiative was designed for programs with low enrollment or limited resources. The

goal was to protect these programs from elimination as uni-versities faced tight budgets. The basic premise of the MACE program is collaboration among several universities by sharing faculty resources for specific majors. Each participating univer-sity offers different upper-level major courses rather than each university offering all electives. Students complete their major by taking most courses through their (“home”) university along with some upper-level electives taught online through the part-ner (“provider”) schools.

While the MACE initiative was developed for several disciplines, the focus of this article is on the economics pro-gram collaboration between three universities, which include Northwest Missouri State University (NWMSU), Southeast Missouri State University (SEMO), and University of Central Missouri (UCM). The purpose of this collaboration, which was implemented in the fall of 2011, is twofold. First, it preserves the economics programs at the three universities by reducing required resources. Second, it enhances the economics course

$86,000$84,000$82,000$80,000$78,000$76,000$74,000$72,000$70,000$68,000$66,000

Stat

e su

ppor

t in

mill

ions

Year

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Figure 1: State Support for Higher Education in the United States (Illinois State University of Education, 2017)

$900,000,000

$850,000,000

$800,000,000

$750,000,000

$700,000,000

$650,000,000

$600,000,000

Stat

e ap

prop

riatio

ns

Year

2008 2009 2010 2011 2012 2013 2014 2015

Figure 2: State Operating Appropriations for Public Higher Education in Missouri (MDHE, 2017)

41 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

offerings for each university by facilitating access to additional faculty with different areas of expertise.

The MACE Initiative in Economics

Participating UniversitiesAll three participating schools are four-year public universi-

ties located in different areas of Missouri. Total enrollment at NWMSU, SEMO, and UCM is 7,000, 11,000, and 14,000 stu-dents, respectively. The undergraduate student characteristics at each school are similar. The majority of students are comprised of Missouri residents, and the percentages of minority and inter-national students are comparable. University-wide average ACT scores range from 21.8 to 23 for the three universities (NWMSU, 2017; SEMO, 2017; UCM, 2017).

CoursesIntroductory and intermediate courses in macroeconomics

and microeconomics continue to be taught on each campus and are not part of the collaboration. These courses tend to have suffi-cient enrollment as they are required for other majors. Therefore, only upper-level economics electives are part of the MACE program. The six courses included in the collaboration are Labor Economics; Money, Credit, and Banking; International Economics; Comparative Economics; Sports Economics; and Econometrics. Each university is responsible for teaching two specific MACE courses—one per semester.

TuitionStudents enroll in MACE courses through their home uni-

versity. Tuition dollars stay with the home university, regardless of which school is responsible for teaching the course. For exam-ple, UCM teaches the MACE Econometrics course. If a student from NWMSU wants to take Econometrics, they enroll in the course through NWMSU just as they do any other course taken at the university.

Enrollment ProcessStudents are not required to transfer any courses between

universities. As previously mentioned, students enroll in MACE courses through their home universities. However, enrolling in the course is just the beginning of what can be a complicated process.

Prior to the start of the semester, the appropriate contact (director or chair) at each home university sends the rosters of students enrolled in MACE courses to the provider universities. Each provider institution must then ensure that the students from the partner universities are properly enrolled into the MACE courses and have access to the necessary online course

sites. The process is complex because the students are not paying tuition to and are, therefore, not officially students at the provider university. This creates some challenges regarding enrollment, registration, communication, and course-site access. Along with the instructors and program contacts, the universities’ respec-tive registrars and information technology departments must be involved in the solutions to these issues.

Access to Online Course SitesAll MACE courses are delivered online; therefore, students

must have access to the provider university’s course site. Enrolling a student in a course site is a separate process from enrolling the student in the course and differs across universities.

Each participating university uses a different learning (course) management system to facilitate its online courses. As such, students must learn and adjust to using the provider insti-tution’s system. It is the responsibility of the provider university to deliver the necessary login information and instructions to the MACE students.

Course Content, Design, and GradesEach provider institution is responsible for creating and

delivering the MACE courses it teaches. There are currently no MACE guidelines for courses and, therefore, no uniformity. While course syllabi are provided to participating universities for each MACE course, instructors have full control over required textbooks and materials, content, structure, assessment, and grades. Once course grades are assigned, the provider institu-tion’s instructor emails the grades to the appropriate contact at the students’ home universities.

Number of StudentsWhen the MACE program for economics was created, the

three universities made an informal agreement that enrollment for each university in each MACE course would be capped at 10 students. Under that agreement, the maximum number of MACE students in a course would be 20. These potential 20  students would be in addition to the regular, home enroll-ment in the course. The provider university decides how strictly to enforce the cap.

Three MACE courses are offered each semester—one per university. Figure 3 shows the total number of students from each home university enrolled in courses taught by provider uni-versities. The figure shows some instances where the enrollment caps of 10 students were not strictly enforced. It is also clear that enrollment imbalances exist across universities. In every semester except one, the number of SEMO and UCM students taught by NWMSU was greater than the number of NWMSU students

42 Quality Approaches in Education Vol. 8, No. 2asq.org/edu

taught by those schools. These imbalances mostly reflect the size differences of the universities as well as the number of economics majors at each. NWMSU is significantly smaller in both aspects.

When discussing enrollments in MACE courses, it is important to remember that tuition dollars stay with the home university, not the provider university. NWMSU is at a disadvantage when comparing the number of additional stu-dents taught versus the number of tuition dollars received. UCM is at an advantage as they are larger and have more than double the number of economics majors. Figure 4 illustrates the number of economics majors at each university through-out the past ten years.

Benefits of the MACE Program

Preserve economics programsThe most significant benefit of the MACE initiative is that

it has allowed all three participating universities to keep, and

even grow, their economics programs (Figure 4). This might have been impos-sible without the collaboration. Prior to the formation of the MACE program, the economics majors at all three universities were identified as “low-enrollment,” and eliminating low-enrollment programs was one option to reduce costs as each university faced large funding cuts dur-ing the recession.

Increased variety of course offerings

The collaboration enables each uni-versity to offer an increased variety of courses. University course offerings are limited by the number and expertise of faculty. The MACE program gives each participating university access to addi-tional faculty with different areas of specialization, allowing the universities to offer a larger number and wider vari-ety of economics electives. For example, the collaboration has enabled all three universities to offer a Sports Economics course, which was not possible before.

Cost savingsThe MACE program reduces the

number of upper-level economics elec-tives that each school must offer. With four electives taught by other universities, fewer faculty resources are needed for each economics program. For example, NWMSU requires one less full-time economics faculty member than before the collabora-tion because fewer courses must be taught for the degree.

Connections and networkingBoth students and faculty can benefit from interactions

with students and faculty at other universities. Students inter-act and learn from each other during the courses through online class discussions and other assignments. Students from other universities bring different perspectives and ideas because they have taken courses from different professors and, therefore, have different knowledge. The students also have varying jobs, internships, and contacts, all of which are often discussed in courses. This exposure presents additional net-working opportunities that could open paths to internships and careers.

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Additionally, students benefit by having access to additional faculty resources at two other universities. This not only gives students additional resources for new knowledge but also for ref-erences, recommendations, internships, and job opportunities.

Finally, faculty can also gain from having contacts at other universities. These connections can translate into research col-laborations, jobs, and other professional opportunities.

Demonstrates willingness to changeAs mentioned previously, Missouri’s government encour-

aged cooperation and collaboration. Participation in the MACE program shows that the universities are willing to change, adapt, and take part in reducing costs and operating efficiently through collaborations.

Challenges of the MACE Program

Larger class sizesThe MACE program leads to larger enrollment in the collab-

orative courses. This is not problematic if the course originally had low enrollment. However, if there was healthy enrollment before the collaboration, adding the MACE students can make class sizes quite large. Each university has its own enrollment caps for courses, and the additional MACE students are generally not included in these caps. Therefore, MACE courses can have enrollment levels beyond a university’s typical maximum. There have been instances where the collaboration has pushed enroll-ment to 55 students or more. Figure 5 shows total enrollment levels in MACE courses taught by NWMSU and the breakdown of how many of these students are from NWMSU versus how many are enrolled at the other universities.

The number of students in a course impacts how that course is designed and taught. Large classes simply cannot be taught

or structured in the same way as small classes. For example, it becomes necessary to rely more on multiple choice rather than short-answer or essay questions for assessments. For example, essay and short-answer questions, written assignments, term papers, and projects are less likely to be assigned to large classes because of the time required for grading. The larger the class, the more difficult it is to provide meaningful, personal feedback to each student. While more students can have a positive impact on class discussions through additional ideas and perspectives, there are still negative effects on discussions. The sheer number of posts becomes an issue. It is difficult for students to read every single post, and it becomes time-consuming for the instructor to respond to each one. In smaller classes, it easier to carry on a meaningful discussion because the students and the instructor can read and respond to all posts.

Confusion for studentsThere are many potential sources of confusion for students in

MACE courses. First, they often do not know about or under-stand the collaboration. They may be confused as to why they are taking a course taught by a professor at another university. In general, improvement is needed in explaining and promoting the program to students.

The process of enrolling in and taking a MACE course can be confusing. Prior to the start of the course, students receive mul-tiple emails from various people about registration, the course site, and the course itself. Much of this communication occurs well before the beginning of the semester—either during sum-mer or winter break. Some students do not check email regularly during breaks and therefore might miss this important informa-tion. That aside, even if all emails are read, the communication and information often are from people who the students do not know and from a university other than their own.

Figure 5: Enrollment in the MACE Money, Credit, and Banking and Labor Economics Courses Taught by NWMSU

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Lack of consistency and controlAs mentioned previously, there are no guidelines for design-

ing and teaching MACE courses. Therefore, they have different syllabi, requirements, and structures. Students must learn how to navigate and use a new learning management system when taking a course offered by another university.

There has not been any formal review of MACE courses by the participating universities. Each institution is responsible for ensuring that the courses offered are of high quality. Therefore, each university must trust that other universities and professors are giving the students a good experience and equipping them with the appropriate knowledge and skills.

LogisticsThe MACE program requires additional effort from

instructors, department chairs or directors, registrars, and technical support staff. A significant amount of time is spent responding to questions, concerns, and issues that arise as a result of the collaboration.

A major logistical issue is that the participating universities operate on different academic calendars. They have differing semester start dates, finals dates, days off, and holiday breaks. The MACE courses always follow the provider university’s schedule. Therefore, it is often necessary to accommodate students who are on different schedules and provide some flexibility, especially during the first week of class as students are still in transition. It is particularly challenging for students when a MACE course starts earlier than their other classes.

Grade submission is also affected by the differing academic calendars. Recall that the provider institution assigns student grades, but the home institution is responsible for submitting official grades. It is possible that the home institution’s semes-ter ends before the provider institution. When this occurs, the home university must enter an incomplete or in-process grade and then submit a grade change once the grades are received from the provider institution. While this does require addi-tional administrative work, the students should not be negatively affected because only the final grade is reported.

As discussed previously, registering and granting access to the online course sites for students from other universities is a complicated process. The chair or director, registrar, technical support, and instructor must work together to determine the best method. Some questions to address include the following:

• Should the students be fully enrolled in the provider university?

• What information does enrollment require?

• Are students assigned IDs and email addresses for the pro-vider institution?

• What is the timeline for the registration process and who is responsible for each step?

• Who communicates with the students; and when and what do they communicate?

Each university has developed answers to these questions.

Caps on enrollmentThe MACE program agreement suggested a cap of 10 stu-

dents per university per course. At times, 10 is not sufficient to meet enrollment demand. For example, NWMSU must offer its own section of International Economics on campus because there are not enough seats available in the MACE course taught by the provider institution. This clearly makes the collaboration less beneficial in terms of saving faculty resources as the course must be taught on campus anyway.

Tuition dollars and compensationStudents enrolled in MACE courses pay tuition to their

home universities. It was shown previously that NWMSU, the smallest school, has the fewest students enrolled in MACE courses. Therefore, NWMSU is teaching more students, yet receiving fewer tuition dollars than the other universities. It should also be noted that instructors teaching MACE courses are not given additional compensation for the larger class sizes. Overall, the collaboration appears to be more advantageous for larger universities.

DeliveryMACE courses are offered online only. This type of course is a

benefit for some students as it provides flexibility. However, some students prefer or perform better in a face-to-face environment. Students have no choice but to take some of their upper-level eco-nomics electives online. Economics is difficult for many students, and is often more challenging when taught online.

ResultsIt is difficult to say with certainty yet whether or not the

MACE program has been successful. How should success be calculated? Is it measured by reduced costs, increased revenues, higher enrollment in economics courses, more economics majors, improved graduation rates, or something else?

In terms of reducing costs, the MACE initiative has been suc-cessful. Each university can offer its economics major with fewer required resources. For example, the collaboration saves NWMSU the equivalent of a full-time economics faculty salary each year.

In regard to enrollment, the results from the three universi-ties have been mixed. Figure 4 shows the number of declared

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economics majors at each university throughout the past 10  years. From 2004 to 2010, the number at each university remained relatively constant. Then all three universities saw an increase in majors between 2010 to the fall of 2011, when the MACE program began. After 2011, trends differed for the participating schools. NWMSU has seen a small, yet steady increase in economics majors each year from 2010 to 2015. After a big increase from 2009 to 2011, SEMO had a steady decline in majors each year from 2012 to 2014, but rebounded with a significant increase in the 2015 academic year. UCM has expe-rienced the largest change in majors, more than doubling from 2010 to 2012. Much of this increase is attributable to the cre-ation of the Business Economics major in 2012. Overall, two out of the three participating schools have reported increases in the number of economics majors since the start of the MACE program. It is also important to note that total undergraduate enrollment at the three universities has not changed significantly in the past five years. Based solely on this data, it is difficult to draw any firm conclusions regarding the impact of MACE and economics enrollments. Yet, Figures 4 and 5 still provide impor-tant information regarding trends.

One way to measure the effectiveness of courses in general is through student evaluations. Currently, the provider insti-tution and instructor do not receive evaluations from MACE students. The universities are missing an opportunity to collect additional feedback that could be used to improve the courses and the collaboration.

Furthermore, the three participating universities have not met to review the program since the collaboration began. It would be beneficial to discuss the experiences of each university and work together to improve the program.

Conclusions, Recommendations, and Future Research

The MACE program was designed to save lower- enrollment majors that could face potential elimination by reducing expenses when state funding was decreased during the recession. The MACE program decreases the cost of these majors by shar-ing faculty resources across universities.

The MACE initiative for economics includes three universi-ties for which the economics degree programs were considered to be low-enrollment. Each participating university offers two dif-ferent upper-level economics elective courses for which students from all three universities are able to enroll.

Participating institutions and students benefit from the MACE program in a variety of ways. First, the collaboration lowers the number of economics courses that each institution must offer, thereby reducing required resources. Universities are

also able to offer a greater variety of economics electives with access to additional faculty. Another benefit is the opportuni-ties for additional networking—student to student, student to faculty, and faculty to faculty. Finally, participating in the col-laboration shows state government that universities are willing to adapt and operate more efficiently.

The MACE program also comes with challenges. The most common issues that arise are logistical and can create confusion for the students. Students enroll through their home universi-ties and pay tuition to their own school, but the course is taught online by another university. The MACE courses are not stan-dardized—each instructor creates his or her own syllabi and course structure. Furthermore, each university operates on its own calendar and uses a different learning (course) manage-ment system. Another issue is that the participating universities differ in size, causing an imbalance in the number of additional students taught. The smaller universities are teaching more additional students, but are not receiving the added tuition. Finally, MACE courses are only offered online. Online delivery and learning can be difficult for upper-level economics courses, which often involve complex theory and mathematics.

All three universities have been able to continue offer-ing economics majors since the MACE was formed. In that sense, the collaboration has certainly been successful. Also, the challenges of the program have become easier to handle over time with experience. This article provides an overview of the MACE program in economics and describes some of the bene-fits and challenges. However, this summary is not sufficient for determining whether the program is truly beneficial for each university or sustainable going forward. A more detailed anal-ysis of each university’s experience is needed to answer these questions. The analysis should include a thorough cost-benefit comparison for each economics program, an examination of enrollments and resources, along with feedback from students, instructors, and chairs or directors.

References:

Gordon, T. (2012). State and Local Budgets and The Great Recession. Retrieved from https://www.brookings.edu/articles/state-and-local-budgets-and-the-great-recession/.

Hunn, D. (2008, November 17). Nixon Brokers Another College Tuition Freeze. St. Louis Post Dispatch. Retrieved from http://www.stltoday.com/news/local/education/nixon-brokers-another-college-tuition-freeze/article_a25ff745-45a8-5613-8523-087b309ae8fe.html.

Illinois State University College of Education. (2017). Grapevine sum-mary tables fiscal year (FY) 2016-17, Table 1: State fiscal support for higher education, by state [Data file]. Retrieved from http://education.illinois-state.edu/grapevine/tables/.

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Jones, D., & Wellman, J. (2010). Breaking bad habits: Navigating the financial crisis. Change: the Magazine of Higher Learning, May/June 2010. Retrieved from: http://www.changemag.org/Archives/Back%20Issues/May-June%202010/breaking-bad-full.html.

Missouri Alliance for Collaborative Education (MACE). (2010). Memorandum of agreement to form the Missouri instructional coalition for eco-nomics. Retrieved from http://www.semo.edu/pdf/MACE-Economics.pdf.

Missouri Department of Higher Education (MDHE). (2017). Statistical summary. Retrieved from http://dhe.mo.gov/data/statsum/.

Mitchell, M., Leachman, M., & Masterson, K. (2016). Funding up, tuition down: State cuts to education threaten quality and affordabil-ity at public colleges. Retrieved from http://www.cbpp.org/research/state-budget-and-tax/funding-down-tuition-up.

Nixon, J. (2010). Governor Nixon’s remarks at higher education sum-mit. Retrieved from http://governor.mo.gov/news/speeches/gov-nixons-remarks-higher-education-summit.

Northwest Missouri State University (NWMSU). (2017). Northwest facts. Retrieved from http://www.nwmissouri.edu/facts/index.htm.

Redmond, W. (2012). Collaboration in Missouri higher education: The MACE Initiative. Teacher-Scholar: The Journal of the State Comprehensive University, 4(1), 21-32.

Southeast Missouri State University (SEMO). (2017). Institutional research fast facts. Retrieved from http://www.semo.edu/ir/facts.html.

Southeast Missouri State University (SEMO). (2015). Missouri alliance for collaborative education. Retrieved from http://www.semo.edu/mace/.

State Higher Education Executive Officers Association (SHEEO). (2015). State higher education finance: FY 2014 report. Retrieved from http://www.sheeo.org/sites/default/files/project-files/SHEF%20FY%202014-20150410.pdf.

University of Central Missouri (UCM). (2017). Fast facts. Retrieved from https://www.ucmo.edu/about/facts/.

Casey Abington, Ph.D., is associate profes-sor of economics at Northwest Missouri State University in Maryville, Missouri. Her fields of specialization are macroeconomics and labor economics, and her primary research interests are the economics of education and economic growth. Contact Abington via email at casey@nwmissouri.edu.Casey Abington

47 Quality Approaches in Education Vol. 8, No. 2

Quality Approachesin Education

The American Society for Quality’s Education Division publishes the online, double-blind, peer-reviewed journal Quality Approaches in Education. The editorial team actively encourages authors to submit papers for upcoming issues.

The purpose of this journal is to engage the education community in a discussion of significant topics related to improving quality and identifying best practices in education and workforce development; and expanding the litera-ture specific to quality in education topics. With the increased emphasis on quality improvement in education, Quality Approaches in Education engenders a conversation focusing on this topic, supported by manuscripts from the interna-tional education community of faculty, researchers, and administrators from different disciplines and professions. Quality Approaches in Education welcomes submissions of manuscripts from higher education, K-12, and workforce development. The journal also welcomes manuscripts from the student services arena, institutional research, professional development, continuing education, business affairs, and other aspects of education related to quality improvement. We encourage evidence-based analysis using quality approach-driven improvement of education.

The following types of articles fit the purview of Quality Approaches in Education:• Case studies on how to improve quality in a college, school system, or workforce development program using

evidence-based analysis, continuous improvement approaches, especially related to improving student retention and degree completion.

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• Case studies that highlight the emerging improvement science for education and the continuous improvement cycle.• Significant conceptual articles discussing theories, models, and/or best practices related to quality in higher educa-

tion, K-12, and workforce development.NOTE: We may dedicate an issue to a special topic to highlight areas of high interest in the field of education.Articles generally should contain between 3,500 and 5,000 words and can include up to six charts, tables, diagrams, illustrations, or photos of high resolution. For details, please check the “Author Guidelines” at: http://asq.org/edu/quality-information/journals/

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Quality Approaches in Education is a double-blind, peer-reviewed journal that is published online by the Education Division of the American Society for Quality (ASQ). The purpose of this journal is to engage the education community in a discussion of significant topics related to improving quality and identifying best practices in education as well as expanding the literature specific to quality in education topics. We will only consider articles that have not been pub-lished previously and currently are not under consideration for publication elsewhere.

General InformationArticles in Quality Approaches in Education generally should contain between 3,500 and 5,000 words and can include

up to six charts, tables, diagrams, photos, or other illustrations. See the “Submission Format” section for more detail.

The following types of articles fit the purview of Quality Approaches in Education:• Case studies on how to improve quality in a college, school system, or workforce development program using

evidence-based analysis and continuous improvement approaches, especially related to improving student retention and degree completion.

• Research articles reporting on survey findings such as a national survey on students’ attitudes toward confidence, success, social networking, student engagement, access and affordability, etc.

• Case studies or research articles addressing issues such as the role of faculty, administrators, and trainers in quality systems.

• Case studies or research studies focusing on the role of quality in accreditation.• Case studies demonstrating best practices and systems thinking in education using the Baldrige Education Criteria

for Performance Excellence, Lean Six Sigma or other national quality models, standards from the Council for the Advancement of Standards in Higher Education (CAS), or national frameworks and protocols, including preparing K-16 teachers for teaching in the 21st century learning environment.

• Case studies or research studies on scholarship of teaching and approaches to improve teaching, enhancing and supporting student learning, learning outcomes assessment best practices, and best practices for using technology in the classroom.

• Case studies or research studies on how student service units and intervention programs impact the quality of stu-dent experience and student learning.

• Case studies or research studies specific to collaboration with industry on STEM education through internships, co-ops, and capstone experiences for providing experiential and deep learning experiences and preparing students for STEM careers.

• Research studies on how education practices impact the quality of student life and student success for different student populations, including underrepresented groups, first generation in college students, and students from low-income families.

• Case studies that highlight the emerging improvement science for education and the continuous improvement cycle.• Significant conceptual articles discussing theories, models, and/or best practices related to quality in higher education,

K-12, and workforce development.

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Manuscript Review ProcessWe log all article submissions into a database and delete all references to you. These “blinded” versions then go to the

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Quality Approachesin Education

Submission Format1. We accept only electronic submissions in Microsoft Word format. The first page should be a title page with the

title, names of the authors, and their affiliations. The second page should be the start of the proposed article with the title and abstract (150 words maximum) at the top of the page. There should be no reference to the author(s) or affiliation in the text that follows. Instead of the name of a university for a case study, the text should state “the University”. The margins should be one inch all around on 8½ x 11 pages with Word’s one-column format, left-justified. The title and section titles should be 14-point bold Calibri font. The text font should use 11-point Calibri font and a line spacing of 1.5 is preferred.Section headings should be 12-point bold Calibri and left justified. Typical section names are: Abstract, Introduction, Background, Literature Review, Methodology, Results, Discussion, Suggestions for Best Practices, Summary or Conclusions, Recommendations, Future Work/Research, Acknowledgments, and References. The actual headings will depend on the focus of the manuscript. There may be two additional levels of sub-headings. The first set of subheadings would be left-justified with the first letter of each word capitalized and in bold, 12-point Calibri. The second level of sub-headings would be the same but in italics.

2. If you are familiar with the APA formatting, we prefer the APA format, but will accept a well-formatted manu-script following these already mentioned guidelines.

3. The manuscript should be between 3,500 and 5,000 words including the abstract, tables, and references. It should include no more than six tables or figures. If you feel strongly that more tables or figures are needed to support the manuscript, we ask that you submit the additional tables or figures and provide an explanation for including them.

4. Tables should be included at the end of the article and must be in Microsoft Word. Each table must be referenced in the article and labeled and centered on a separate line, such as <Insert Table 1 About Here> with the caption for Table 1 on the next line, such as Table 1: Graduation Rate by Major. Do not embed .jpg, .tif, .gif, or tables in other similar formats in your article.

5. Drawings, graphs, and other illustrations should be sent in an email as separate .jpg files with 300dpi; each item should be included in a separate file. All drawings and other illustrations must be referenced in the article, and must be labeled and centered on a separate line, such as <Insert Figure 1 About Here> with the caption for Figure 1 on the next line: “Figure 1: Pareto Analysis of Student Participation in Department Activities.”

6. We can use photos if they enhance the article’s content. If you choose to submit a photo with your article, it must be a high-resolution .jpg or (at least 300 dpi and at least 4” by 6” in size). Photos should be sent in separate files and referenced in the article. Photos should be accompanied by a complete caption, including a left-to-right listing of people appearing in the photo, when applicable. Do not include any text with the photo file. All persons in the photo must have given permission to have their photo published in Quality Approaches in Education.

7. Also submit a separate high-resolution electronic photo (at least 300 dpi) for each author. Author photos should be at least 1” by 2”. Author photos should have a plain background, and the author should be facing toward the camera. Please include a separate Word document with a 75- to 100-word biography for each of the authors, men-tioning the place of employment, as well as contact information.

Author Guidelines

52 Quality Approaches in Education Vol. 8, No. 2

Quality Approachesin Education

Citations and ReferencesQuality Approaches in Education follows the 6th edition of the Publication Manual of the American Psychological

Association. Citations and references should use the (author’s last name, year of publication) notation in a citation in the text and use the APA style.

The reference section should be headed with the section heading of “References” and all references are to be listed alphabetically by the first author’s last name. Each reference should list all authors. List the online URL with a hyperlink. Retrieved date is not needed. Here are some examples:Book examples:

Veenstra, C., Padró, F., & Furst-Bowe, J. (eds). (2012). Advancing the STEM agenda: Quality improvement supports STEM. Milwaukee, WI: ASQ Quality Press.

Sorensen, C. W., Furst-Bowe, J. A., & Moen, D. M. (2005). Quality and performance excellence in higher education. Bolton, MA: Anken Publishing Company, Inc.Journal article examples:

Dew, J. (2009). Quality issues in higher education, Journal for Quality and Participation 32(1), 4-9. Retrieved from http://asq.org/pub/jqp/past/2009/april/index.html

Plotkowski, P. (2013). Guest commentary: Real-World engineering education: The role of continuous improvement, Quality Approaches in Higher Education, 4 (1), 2-4. Retrieved from http://rube.asq.org/edu/2013/05/best-practices/quality-approaches-in-higher-education-vol-4-no-1.pdfReference example:

National Science Board. (2012). Science and engineering indicators 2012. Arlington, VA: National Science Foundation. Retrieved from http://www.nsf.gov/statistics/seind10/.

If the authors cite their own work, they should simply state (Author, year) and the same in the reference list (no title) in the initial manuscript (since the reviews are double-blind).

One of the most common errors we have observed with submitted articles is improper referencing due to improper attribution in the text and reference section. Please make sure that all the material in the submitted article is properly referenced and cited as appropriate.

SubmissionSend an electronic copy of the Word document of the manuscript including the title page, abstract, text of the manu-

script, acknowledgments, and references, with a separate file of any surveys used, separate .jpg files of the figures and photos of authors, and a Word document of the author biographies to Dr. Elizabeth Cudney at QAEJournal@gmail.com.

Note on Copyright TransferPrior to publication, you must sign a form affirming your work is original and is not an infringement of an existing

copyright. Additionally, we ask you to transfer copyright to ASQ. The copyright transfer allows you to reproduce your article in specific ways, provided you request permission from ASQ and credit the copyright to ASQ. The transfer also allows ASQ to reproduce the work in other publications, on its website, etc.

If you use materials from other works in your articles (other than standard references), you must obtain written per-mission from the copyright owner (usually the publisher) to reprint each item of borrowed material. This includes any illustrations, tables, or substantial extracts (direct quotations) outside the realm of fair use. Submit these permission letters with the article. Articles cannot be published until copies of all permission letters are received.

For example, an article includes a PDSA illustration from a book. The permission statement would include: Figure 1 is from Nancy R. Tague’s The Quality Toolbox, 2nd ed., ASQ Quality Press, 2005, page 391. This permission statement would appear in the caption just below the PDSA figure.

Author Guidelines