Higher Education Evaluation and Development

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Higher Education Evaluation and Accreditation Council of Taiwan

Volume 11 Number 1 ISSN: 2514-5789

Volume 11 Number 1 2017

Higher Education Evaluation and Development

Higher Education Evaluationand Development

Access this journal online:www.emeraldinsight.com/journal/heed

Number 1 1 Editorial boards

2 Institutional research as a bridge: aligning institutional internal data needs and external information requirements from a strategic viewChester D. Haskell

12 A comparative study of student mobility programs in SEAMEO-RIHED, UMAP, and Campus Asia: regulation, challenges, and impacts on higher education regionalizationAngela Yung Chi Hou, Christopher Hill, Karen Hui-Jung Chen, Sandy Tsai and Vivian Chen

25 The development of Malaysian universities: exploring characteristics emerging from interaction between Western academic models and traditional and local culturesMolly Lee, Morshidi Sirat and Chang Da Wan

38 Development of the college-attendance value scale for second-year students in TaiwanMing-chia Lin and Eric S. Lin

EDITORS-IN-CHIEFSAngela Yung-Chi Hou Higher Education Evaluation and Accreditation Council of Taiwan (HEEACT) & Asia-Pacific Quality Network (APQN),TaiwanJagannath PatilNational Assessment and Accreditation Council (NAAC) & Asia Pacific Quality Network (APQN), IndiaSheng-Ju ChanHigher Education Evaluation and Accreditation Council of Taiwan (HEEACT) and National Chung Cheng University, TaiwanHomepage: www.emeraldgrouppublishing.com/services/publishing/heed/index.htmEXECUTIVE EDITORHua-Chi ChouHigher Education Evaluation and Accreditation Council of Taiwan (HEEACT), TaiwanEDITORIAL ASSISTANTCindy ChenHigher Education Evaluation and Accreditation Council of Taiwan (HEEACT), Taiwan

ISSN 2514-5789© Higher Education Evaluation and Accreditation Council of Taiwan (HEEACT), Asia-Pacific Quality Network (APQN)

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Higher Education Evaluation and Development (HEED) is a quality English journal founded by the Higher Education Evaluation and Accreditation Council of Taiwan and has been jointly published with Asia-Pacific Quality Network (APQN) since 2014, and is APQN’s membership journal. HEED is a scholarly refereed journal that aims to encourage research in higher education evaluation and development, raising standard of evaluation research and sharing the discoveries worldwide. The journal welcomes quality papers from subjects of:

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EDITORIAL BOARD

Sheng-Ju ChanProfessor, Graduate Institute of Education, NationalChung Cheng University, Taiwan

Ying ChanProfessor, Graduate Institute of Educational Policyand Leadership, Tamkang University, Taiwan

Dian-Fu ChangProfessor, Graduate Institute of Educational Policyand Leadership, Tamkang University, Taiwan

Dorothy I-Ru ChenAssociate Professor, Department of Internationaland Comparative Education, National Chi NanUniversity, Taiwan

Karen Hui Jung ChenAssistant Professor, Department of Education,National Taipei University of Education, Taiwan

Shaw-Ren LinProfessor, Graduate Institute of Arts andHumanities Education, Taipei National University ofthe Arts, Taiwan

Yi-Fang LiProfessor, Department of Industrial Education,National Taiwan Normal University, Taiwan

Cheng-Cheng YangAssociate Professor, Graduate Institute ofEducational Administration and PolicyDevelopment, National Chiayi University, Taiwan

Cheng-Ta WuProfessor, Department of Education, NationalChengchi University, Taiwan

INTERNATIONAL EDITORIAL BOARD

Judith S. EatonPresident, Council for Higher EducationAccreditation (CHEA), USA

Christopher HillAssociate Professor, Faculty of Education,The British University in Dubai

Simon MarginsonProfessor, Department of Lifelong and ComparativeEducation, Institute of Education, University CollegeLondon (UCL), UK

Joshua Ka-Ho MokChair Professor, Comparative Policy, LingnanUniversity (LU), Hong Kong

Gary PikeProfessor, School of Education, Indiana UniversityPurdue University Indianapolis, USA

Laura E. RumbleyAssistant Professor, Department of EducationalLeadership and Higher Education, Boston College,USA

Jung-Cheol ShinProfessor, Department of Education,Seoul National University, South Korea

Morshidi SiratProfessor, School of Humanities, Universiti SainsMalaysia

Ly TranAssociate Professor, Faculty of Arts and Education,Deakin University, Australia

Padraig WalshPresident, European Association of QualityAssurance (ENQA), Ireland

Rui YangProfessor, Division of Policy, Administration andSocial Sciences Education, The University ofHong Kong, Hong Kong

Akiyoshi YonezawaProfessor, Office of Institutional Research,Tohoku University, Japan

Jianxin ZhangPresident, Asia-Pacific Quality Network (APQN),China

Higher Education Evaluation andDevelopment

Vol. 11 No. 1, 2017p. 1

Emerald Publishing Limited2514-5789

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Editorialboards


Institutional research as a bridgeAligning institutional internal data needsand external information requirements

from a strategic viewChester D. Haskell

International Consultant to Higher Education, Fallbrook, California, USA

AbstractPurpose – This paper explores the roles of institutional research (IR) units in higher education, examiningboth internal and external responsibilities and demands. The purpose of this paper is to encourage a broaderstrategic discussion of the missions and capacities of such academic institutional entities.Design/methodology/approach – The methodology employed begins with a review of relevant literature,followed by critical observations of an experienced reflective practitioner. Beginning with the premise thatacademic institutions are central, the paper discusses the external environment of institutions and therequirements placed on their internal IR operations. A core question is presented: research for whom?Both traditional and alternative organizational models are discussed in this light. The paper then exploresways in which data needs might be aligned in order to provide accountable, useful and transparentinformation to all stakeholders, internal and external.Findings – Findings show that the linking of internal information needs with those of external actors is key toeffective operations; that IR units should seek to be a bridge between their institution and its environment so thateffective information can be provided to all who need it. The paper is not designed as a detailed operational roadmap,but rather to highlight issues for examination within the context of specific institutional and agency situations.Originality/value – Its originality stems from the focus on such linkages and the call for organizationalleaders to recognize the full value of IR both within and across organizational boundaries.Keywords Institutional research, Institutional quality, Accreditation, Information requirements,External accrediting body, Internal organizational structurePaper type Research paper

As is the case in most modern arenas, the capacity for collecting and disseminating dataabout higher education is growing rapidly. New technologies, new software, new analyticmethodologies and new approaches combine to create the potential for exponentially largeramounts and types of data that might be used to inform all interested parties.

Simultaneously, external demands for information about higher education also areexpanding tremendously. Governments require more and better information aboutinstitutional performance and outcomes. Accrediting bodies seek data to improve theircapacity for oversight, verification and quality assurance. Prospective students andtheir families look for information about programs, costs and what their investments willpurchase. Employers seek greater alignment of student capabilities and employer needs.

This confluence of expanding capabilities and increasing demands puts great pressureon those tasked with gathering and analyzing data and reporting results to stakeholders.In most academic institutions, these responsibilities are placed primarily on an internalorganizational unit, typically referred to as “institutional research (IR).”

Higher Education Evaluation andDevelopmentVol. 11 No. 1, 2017pp. 2-11Emerald Publishing Limited2514-5789DOI 10.1108/HEED-08-2017-001

Received 15 March 2017Revised 15 June 2017Accepted 15 June 2017

The current issue and full text archive of this journal is available on Emerald Insight at:www.emeraldinsight.com/2514-5789.htm

© Chester D. Haskell. Published in the Higher Education Evaluation and Development. Published byEmerald Publishing Limited. This article is published under the Creative Commons Attribution(CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of thisarticle (for both commercial and non-commercial purposes), subject to full attribution to the originalpublication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

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This essay will explore the changing roles, responsibilities and opportunities for suchfunctional units, paying particular attention to both internal and external information needsand the degree to which these units are integral to the larger institution. It will argue that IRmust serve both functions by linking institutional requirements to external assessments andpublic information. This will be done from the perspective of a reflective practitioner withextensive institutional and accreditation experience internationally who wishes today’sinformation tools had been available in the past.

Discussions about the nature and function of IR hardly are new. Important contributionsare decades old. For example, Fincher (1985) explored the “art and science of IR” in a chapterof Peterson and Corcoran (1985). Knight et al. (1997) discussed the knowledge and skillsneeded to be effective, while Terenzini (1993, 2013) published not one, but two, seminalarticles 20 years apart on what constitutes IR and the capacities of effective practitioners.However, much of this work focused on defining IR in an operational sense; the nature of itsparameters, how it is best conducted, and the skills required of researchers seeking to definea new profession within academe.

Contemporary IR takes a variety of forms in different academic settings. In some cases,such research is used mainly for internal assessment and to inform decisions, both strategicand operational. In others, it largely reacts to external demands for information fromgovernments, accreditors and additional stakeholders outside the institution such asstudents, the public and other institutions. The presumed objective in both instances isinstitutional quality assurance and enhancement, as well to provide relevant information toall manner of internal institutional actors – senior leaders, student affairs officers,enrollment managers, financial aid officials and more. The fact is that all parts of anacademic institution need data to fulfill their functions.

The centrality of academic institutionsIn the first instance, it must be recognized that institutions are the true locus of highereducation, the place where higher education occurs. Academic institutions are the contextfor specialized programs. Particular academic programs or degrees rarely occur in anorganizational vacuum. This reality is reflected in the vast literature on the nature of highereducation. See, for example, Pelikan’s (1992) sweeping chapter “The idea of the university inscholarly literature.”

Even the smallest of academic institutions are complex places. Multiple degrees,disciplines, departments, as well as a range of support and administrative functions, arecollected under one institutional roof, typically with singular institutional leadership.Further, Rojas and Bernasconi (2011) make the point that these structural intricacies arefurther complicated by the “relative weakness of hierarchical power,” the “dense and diversevalues system,” and, importantly, the fact the institution always has a dynamic interactionwith its various external environments (Rojas and Bernasconi, 2011). Somehow, all theseseparate subunits, levels, programs and functions must be organized together if theinstitution is to be effective and successful.

At the same time, the roles and functions of academic institutions are widening in mostcountries. Massification – the phenomenon of opening of educational opportunities andofferings to much larger segments of a population –means traditional institutions have had toexpand, while new institutions have arisen. Calderon (2012) today, there simply are many morestudents than in the past, as higher education has ceased to be available only to the childrenof national elites. In addition, these larger student populations are also more diverse in terms ofstudent characteristics and demographics, as they are not limited to the attributes of the elites.

Academic institutions are amazingly diverse worldwide. Different missions, structures,scales and approaches to education provide a range of opportunities for students,while also promoting competition and innovation. Institutions themselves thus need

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more and richer data that reflect their disparate and evolving realities and situations.IR is essential for all manner of internal purposes and these purposes have become morecomplicated and disparate.

IR and external environmentsAcademic institutions also do not exist in a vacuum, instead being part of the larger society(Rojas and Bernasconi, 2011). In most countries, academic institutions are expected to beconnected to the community, both the physical community in which they are located and thewider community of society. No longer can universities be isolated ivory towers. Instead,institutions have responsibilities to society, serving constituencies far beyond their gates,including the public and governmental stakeholders that provide support.

A central issue for external stakeholders like government or accreditors is how to assureat least minimum quality in institutions – how to handle institutions that are subpar.As Bok (2013) notes, there are two ways to approach this: accreditation or transparency(He also notes these are not mutually exclusive). This combination of accountability andtransparency puts tremendous pressure on any IR unit (Volkwein, 2008). Finally, in additionto the matter of what is to be measured or made transparent, there is the prior questionraised by Chen and Haynes (2016): “transparency for whom?”

Governments – national and in some countries, state – recognize the vital role highereducation plays in serving national and local developmental and economic needs and thussupport some institutions directly (public institutions) and others indirectly through suchmeans as student financial aid, research support, or tax advantages. Governments alsohave legitimate roles in overseeing and regulating academic institutions. Not only dogovernments have a duty to make sure public funds are put to the best possible use, butthey also have a consumer protection function.

These important functions are sometimes fulfilled by some form of academic assessmentand accreditation body. These entities may be directly part of government through a centralministry of education or similar institution. In other cases, they are quasi-autonomousexternal organizations. And in others these functions are fulfilled by entities largelyseparate from government, operating quite independently. In each case, they are designed tofulfill government’s consumer protection function, while also implementing governmentaccountability requirements, in addition to objectives of quality assurance andimprovement. Finally, in some nations (like the USA) there are multiple structures forfulfilling these functions, such as the Federal Department of Education, and institutionaland programmatic accrediting entities. Whatever the structure, all require informationabout academic institutions.

These external bodies, whether autonomous, independent accreditors or governmentagencies, typically define many of the roles for IR operations within academic institutions.They require various forms of data such as student enrollments, degrees awarded andstudent demographic information. An excellent example is the US Department ofEducation’s Integrated Postsecondary Education Data System requirements placed onacademic institutions in the USA (LoGrasso, 2016). In addition to detailed, nationallymandated information, there often are multiple requirements from a variety of other entities,both required and voluntary, sometimes with different formats or methodologies forcollection and presentation. Accrediting bodies in the US and elsewhere impose furtherextensive data requirements as a condition of their own processes for institutionalaccreditation or reaccreditation.

In addition, there often is another type of external body with information needs that arequite separate from those of either government or accreditor bodies: the institution’sgoverning board. In the American model, at least, boards of trustees and like bodies arelargely composed of external actors who have a fiduciary responsibility for the academic

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institution (Henderson, 2016). Servicing such an entity creates yet another (and often highlypressured) responsibility for institutional researchers.

The point is that much of the role of an IR office is not related to internal institutionalneeds, but rather the servicing of a range of external actors. Many such external demandsmay not be tied to internal goals such as student learning outcomes or institutionalimprovement. Rather they may be solely constructed to meet the external entity’s perceivedneeds. To further complicate things, the data requirements not only may be different incontent, but also may need to be different in form and presentation to be effective.

These external demands have a variety of impacts on an IR office. The number, typeand complexity of data reports may increase. Divergent or inconsistent definitions ofdata items, content and formatting requirements lead to duplicative demands fordata that are structured differently, thus precluding efficiencies. Meeting external datademands means institutions have to dedicate professional staff to this function, often atconsiderable cost. Further, such imposed costs are highest for the smallest institutions.The staffing needed tends to be higher as a proportion of institutional budgets in thesmaller institution.

An additional consideration is the numerous and often conflicting demands of multipleaccrediting bodies. Many institutions have both institutional accreditation (accreditation ofthe institution as a whole, or “registration” as it is called in some countries) andprogrammatic or specialized accreditation (accreditation of a particular academic degrees orprograms). These different accreditors have differing purposes and perspectives, thus theirdata requirements are different. This situation adds to the responsibilities of an institution’sinternal research office.

For example, in Mexico there are multiple forms of accrediting organizations.The Ministry of Education (Secretaría de Educación Pública, SEP) imposes highly detailedrequirements on all institutions. Separate programmatic accreditors impose differentrequirements on different degree programs. Graduate programs are assessed and accreditedby a separate agency (Consejo Nacional de Ciencía y Technología, CONACYT) that has itsown set of requirements. Some non-public institutions are accredited by the Federación deInstituciones Mexicanas Particulares de Educación Superiór (FIMPES), a voluntary,non-governmental body that is the only true institutional accreditor in Mexico, and thus faceyet another data set. In other nations, like Australia, institutions that have both vocationaland higher degree programs must meet the requirements of two completely separateregulators, the Australian Skills Quality Authority and the Tertiary Education Quality andStandards Agency. Such complications are not uncommon. While there is considerableoverlap of these various demands, the effect on any institution is the need to collect andreport numerous specialized data sets and analyses. This pattern is common globally.

Ewell (1998) makes a series of recommendations that attempt to address the realities facedin most institutions. For example, reporting burdens are excessive and should be reduced.Duplication is rampant and should eliminated wherever possible. Multiple databases should bereplaced where possible by centralized databases (including those of third parties). At the sametime, however, Ewell (1998) also recognizes the need to tailor data reporting to appropriateaudiences and the importance of reflecting “systemic as well as institutional perspectives.”

The pressures on external accrediting bodies also are increasing in most nations.Government ministries want more and different data, a situation complicated byconstant changes in government directives and in governments themselves. At thesame time, accreditors must determine how to address diversity of institutions within anation or region. How can information requirements be organized to take into account thedifferent scales, missions, ownership or structures of institutions? How can informationrequirements be structured to reflect effectively the tremendous diversity within academicinstitutions – how can institutional complexity be captured by information?

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The challenge to IRThese considerations beg a core question: IR for whom? What is the real purpose of IRcapacity? What are the proper roles of such a function both internally and externally? Is theprincipal purpose to serve the needs of the institutional decision makers? How are thosedecision makers defined? How do the internal and external functions align? Are there otherconsiderations? For example, Colombia has instituted a new information model – theModelo de Indicadores del Desempeño de la Educación Pública (MIDE) – that explicitlystates its purpose is to provide accessible information on higher education institutions forstudents and families (Modelo de Indicadores del Desempeño de la Educación Pública, 2016).

At the same time, the volume and reach of research about higher education issues suchas assessing teaching, measuring student learning or improving classroom efficienciesexploded. Even a casual search on a database site like JSTOR unearths literally tens ofthousands of studies, books and articles on higher education research and its applicationwithin academic settings.

However, much of the emphasis in this literature is about formulating and answeringresearch questions in an institutional setting. It focuses on gathering information to informinstitutional decisions, but says little about institutional structures or purposes. Swing andRoss (2016) cite Gagliardi and Wellman’s (2014) study of US public universities to note thatIR offices are “deluged by demands for data collection and report writing that blot out timeand attention for deeper research, analysis and communication.” Swing and Ross furthernote that the “dominant structure of IR is based on service relationships with a small set ofkey decision makers” (Swing and Ross, 2016, p. 7).

In the same vein, the Association for Institutional Research (AIR) did a survey on thecommon IR output: information dashboards designed to give a snapshot of selected measuresof institutional health or effectiveness (Association for Institutional Research (AIR), 2014).

The question “What are the primary audiences for your dashboard?” responses were:

• campus/institution administrators (91.8 percent);

• faculty/staff (49.3 percent);

• general public (19.2 percent); and

• parents (4.1 percent).

Posed differently, the question “Which best describes who can view the dashboard?” led tothe following results:

• limited to select campus administrators only (31 percent);

• internal to the campus – staff/faculty/administrators only (23.9 percent); and

• open access (15.5 percent) (AIR, 2014).

Clearly, there is no standard definition of information users or stakeholders. In fact, most ofthe dissemination of such dashboard information seems limited to internal institutional users.

A variety of structures for IR units are in evidence in the USA and elsewhere. In manycases, the IR office reports directly to the institutional leader (president). In other cases, thereporting structure is through a provost or vice president for academic affairs. In either case,the office often is not seen as central to institutional operations or priorities. While, there areexamples, such as Australia, where these offices operate as a core and integratedinstitutional function, it is not commonly the case elsewhere. Rather, as in the Americancontext, IR is more likely viewed as a staff function serving only the leadership. Any impacton the broader institution is only by the direction of the leadership.

Typically, the IR office collects as much data as possible, much of it through varioussurvey instruments. The other principal method is garnering data from other offices

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that collect specialized data such as student enrollments from a registrar’s office oradministrative staffing patterns from human resources. Less common are more in-depthdata collection methods such as focus groups, follow up interviews. Large amounts of dataare collected from these and related sources, but its impact may be negligible unlessleadership permits or specifies dissemination.

In this instance, IR is, in effect, a fully integrated component of a top-down, hierarchicalorganizational model. The problem is that this model can be a trap. If information isdesigned primarily to serve the top leadership and only reaches the rest of the organizationthrough the leadership, then it cannot be fully utilized.

This model also means that external accreditors or government agencies have only anarrow keyhole through which to understand the institutions. The external agency requests(or requires) certain kinds of data. Some of these are regularized; for example, standardinformation on enrollments, retention or finances. Others are more in-depth, such as thevolumes of information normally required in institutional review self-studies. In either case,the information gathered and reported is selective; it is structured by what the externalagency defines as necessary. It is never comprehensive, in part because the external agencycannot be comprehensive in its assessment of institutions. There is no agreement on how todefine quality in diverse institutions.

Another aspect of this model is that the external accreditors have a relationship keyhole, aswell. The accreditors typically deal only with the institutional leadership or the designatedinstitutional representative. The agency cannot deal openly with broader sources ofinformation. Further, access to institutional data is usually jealously guarded and limited withthe institution taking the position that data should restricted and not easily proffered.

An alternative model is one where the entire administrative organization – president tojanitors – exists mainly to provide the best possible environment for the faculty andstudents to work and learn together. In this model, information is needed by and providedfor all institutional stakeholders. Such an open data model is also designed to better serveaccreditors. In this model, information of all sorts is continuous and ongoing, not justfocused on specific targets or outcomes. There are several other alternatives underdiscussion among IR professionals including matrix models and federated organizationalstructures (Swing and Ross, 2016).

Data should be designed to be useful for practical real-time engagements, while stillprotecting individual privacy. Properly designed, it should lead to direct and timelyadvising or interventions to support students. In this form, data are not a means tothemselves, but tools to assist others, recognizing the importance of the personal touch byfaculty or staff in support of students. IR units typically are tasked with preparing centralreports providing evidence of performance in key areas such as teaching, learning andresearch. In addition, these units should be the locus of some form of data warehouse that isavailable to staff and faculty. These internal data and the reports produced from them canthen be utilized to meet the various external reporting requirements put upon the institutionby governments, accrediting bodies or others.

The real challenge is how to gather and organize data so information can be made accessibleand useful to support the full range of an institution’s functions and mission. In other words,how can data be organized to best meet the complete scope of internal information required foractions and decision making? And, at the same time, how can the same data be organized toprovide the information required by accreditors and other external stakeholders?

Aligning internal and external data needsIn other words, external data requirements should be aligned with institutional data needs.External agencies should seek few, if any, data not also useful for internal institutionalrequirements. After all, institutions and accreditors have shared interests in information.

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One approach to such problems might be to impose consistent data requirements forevery institution. This, however, leads to one of two problems. Institutional diversityusually is seen as a good thing, reflecting divergent academic traditions, approaches ormissions. Institutional diversity is also seen as valuable for providing choices for students,encouraging competition and facilitating innovation. Yet, limiting diversity in favor ofconsistency or standardization threatens isomorphism, the tendency for institutions tobecome more alike as they try to conform to external incentives or pressures (Powell andDiMaggio, 1991). Alternatively, the recognition of the value of diversity means that datarequirements (and, indeed, almost all accreditation standards) must be set at a threshold orminimal level, thus permitting a diversity of approaches while simultaneously complicatingthe understanding of institutions in the aggregate.

It also must be remembered that the vast bulk of the literature, especially with regard tothe emerging profession of institutional researchers, is based on the US higher educationexperience. While there are effective IR operations in most universities in places likeWestern Europe, Australia and Japan, the field and functions are less developed elsewhere.Nevertheless, interest in IR, both on the part of individual academic institutions and on thepart of external bodies like accreditors and governments is growing rapidly, as highereducation globally is in many ways tending toward an isomorphic convergence largelyaligned with the perceived models of US accreditation and higher education in general.Put differently, everyone recognizes the relationship between good data and data analysisand higher education quality improvement. However, it is not clear that the so-called“American model” is appropriate for all situations.

The demands on external government and accrediting bodies are many. Not only dosuch organizations need data sufficient to fulfill their institutional assessment mandates,but they also need to be able to aggregate institutional data for broader purposes, includingthe formulation of national policies. Such data also are essential for societal purposes, asthey are the basis for aggregate indicators, as well as for purposes of benchmarking.Also, there are numerous data points that are meaningless if not brought together, forexample, how to address the challenges of students who attend multiple institutions or whohave non-continuous academic records. Non-traditional students are often anotherchallenge, as are new, innovative programs. And the growing number of internationalstudents, now estimated at more than five million and growing rapidly, adds yet anotherdegree of complexity (Project Atlas, 2016).

There indeed are powerful new technologies and techniques with potential for important andpositive impacts. Big data, data analysis, predictive analytics, educational data mining andenterprise resource planning are manifestations of these new technologies. In theory, such toolsshould enable institutions or accrediting bodies to collect tremendous amounts of real-time dataand from it make useful information for planning and decisionmaking. Some institutions see suchcapacity as a way to better manage data already collected. Others want to explore these resourcesas ways to expand and improve their institutional effectiveness through direct, timely andactionable data. In any case, the problem is that the advantages of these new tools are often offsetby considerable institutional expenses (in technology, professional staffing, vendors), by the oftensteep learning curve of senior administrators and by potential threats to student privacy.The problem is not the means for data, but, rather, the strategy and capacity for utilizing data.

External accreditors may be able to assist institutions by providing information aboutbest practices or through finding ways to reduce or share costs, especially for smallerinstitutions. At the same time, external accreditors should require transparency from allinstitutions. Transparency and access to data serve both the consumer protection functionand the accountability due to funding sources and governments. Finally, externalaccreditors should work with the institutions they accredit to assure a balancing ofaccreditor and institutional data needs.

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Accreditors and institutions also share a basic problem. The reality is that there are nocommonly accepted definitions or measurements of institutional quality. “Whose quality?”is a common question? Another reason accreditation is largely a minimalist; thresholdexercise is that there are no commonly defined standards of quality (Reisberg, 2011).Accrediting bodies worldwide place great emphasis on “quality processes,” but there is littleagreement on what constitutes a quality outcome.

Furthermore, in many circumstances there can only be proxy measures of quality.One of the dangers confronting IR is measuring those things that can be measuredwhile underemphasizing those things that cannot. This is the methodological problemwith commercial rankings. In such cases, an indicator such as research productivity iscalculated by the number of citations in selected journals. As there is no true measure ofresearch quality, the number of citations becomes a proxy, a number assumed to measuresomething that can be plugged into an algorithm. Crafting a ranking of institutions requiresnumerous such proxy assumptions, thus multiplying the likelihood of inaccuracy at everylevel (Hazelkorn, 2015).

At the same time, a look at characteristics of the leading academic research institutions showsa remarkable consistency. As noted by Bloom and Rosovsky, the best institutions all have:

• an ongoing internal culture of quality useful and appropriate to that institution;

• sufficient data for all decisions (at all levels) within norms of internal and externalaccountability;

• regular internal testing of institutional definitions or standards of quality; and

• rigorous internal processes for meritocratic decisions (Bloom and Rosovsky, 2011).

Such elite institutions do not engage in these sorts of activities because they are required todo so by governments or by external accrediting bodies. Rather, they do so because theyunderstand that defining quality or excellence for themselves and then having theinformation and processes for constant assessment is the key to maintaining their ownstandards and staying competitive with other like-minded institutions. It seems clear thatthe pursuit of quality must incorporate clear and useful data for both decision making andaccountability. However, as Eaton (2015) notes, an institution’s responsibility for its ownquality is a cornerstone of effective quality assurance.

The US-based AIR is the most prominent professional association for individuals in thiscomplex field (There are also a number of AIR spinoffs in other regions, such as those inEurope and South-East Asia). Last year, the association made a series of recommendationsfor more integrated IR. In their “Statement of Aspirational Practice for InstitutionalResearch” it was posited that students, faculty and staff members all need to be viewed asIR stakeholders with data needs, in addition to the more traditional institutional leadership.Such a statement suggests movement toward a model of IR that provides useful informationfor all stakeholders and does so in a timely fashion (AIR, 2016).

ConclusionsIt also can be argued that the AIR approach does not go far enough. Indeed, this paperargues that the aspirations for IR should also be to engage and include externalstakeholders. There should also be greater emphasis on serving the data needs ofaccreditors, other external bodies and, indeed, the public at large.

IR must not be seen as having solely internal institutional functions, even when thosefunctions involve responding to external demands for information. Rather, the internal andexternal roles of IR are not separable. Internal and external stakeholders have a broadshared set of purposes, including quality assurance and improvement. At the same time,

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there are opportunities for two-way learning in the form of information sharing,dissemination of best practices, and shared approaches to problem solving.

The fundamental challenge for those engaged in IR is becoming proactive leaders in dataprovision and utilization. All societies need meaningful and effective ways of measuring andassessing quality in academic institutions. All stakeholders, internal and external, have acommon interest in having access to useful information. The linking of internal interests andinformation requirements with external interests and needs is an opportunity to improvetransparency, accountability and the making of better decisions by all. IR should be seen asa bridge, not a keyhole, and should be fully supported and integrated into the internalinstitution, while also being recognized by external actors for playing a vital role. Only inthese ways can the full power of information be placed in the hands of all who need it.

References

Association for Institutional Research (AIR) (2014), “AIR survey”, December 14, 2012-January 4, 2013,available at: www.airweb.org/eAIR/Surveys/Pages/NationalDataQuality.aspx (accessedFebruary 6, 2017).

Association for Institutional Research (2016), “Statement of aspirational practice for institutionalresearch”, available at: www.airweb.org/ Resources/ImprovingAndTransformingPostsecondaryEducation/Pages/Statements-of-Aspirational-Practice-for-Institutional-Research.aspx (accessedDecember 15, 2016).

Bloom, D.E. and Rosovksy, H. (2011), “Unlocking the benefits of higher education through appropriategovernance”, in Altbach, P. (Ed.), Leadership for World Class Universities: Challenges forDeveloping Countries, Routledge, New York, NY, pp. 70-89.

Bok, D. (2013), Higher Education in America, Princeton University Press, Princeton, NJ, pp. 402-403.

Calderon, A. (2012), “Massification continues to transform higher education”, University World News,No. 237, September 2, 2012, available at: www.universityworldnews.com/article.php?story=20120831155341147 (accessed April 30, 2017).

Chen, P.D. and Haynes, R.M. (2016), “Transparency for whom? Impacts of accountabilitymovements for institutional researchers and beyond”, in Powers, K. and Henderson, A. (Eds),Burden or Benefit: External Data Reporting, New Directions in Institutional Research, Vol. 166,pp. 15-19.

Eaton, J. (2015), An Overview of US Accreditation, Council on Higher Education Accreditation,Washington, DC, p. 3.

Ewell, P. (1998), “Achieving high performance: the policy dimension”, in Tierney, W. (Ed.), TheResponsive University: Restructuring for High Performance, The Johns Hopkins UniversityPress, Baltimore, MD, pp. 156-157.

Fincher, C. (1985), “The art and science of institutional research”, in Peterson, M.W. and Corcoran, M.(Eds), Institutional Research, Vol. 46, John Wiley & Sons, San Francisco, CA, pp. 17-37.

Gagliardi, J.S. and Wellman, J. (2014), “Meeting demand for improvements in public systeminstitutional research: progress report on the NASH project”, National Association of SystemHeads, Washington, DC.

Hazelkorn, E. (2015), Rankings and the Reshaping of Higher Education, the Battle for World-ClassExcellence, 2nd ed., Palgrave Macmillan, New York, NY.

Henderson, A. (2016), “The growth of burden in federal and state reporting”, in Powers, K. andHenderson, A. (Eds), Burden or Benefit: External Data Reporting, New Directions in InstitutionalResearch, Vol. 166, John Wiley & Sons, San Francisco, CA, pp. 22-28.

Knight, W.E., Moore, M.E. and Coperthwaite, C.A. (1997), “Institutional research: knowledge,skills and perceptions of effectiveness”, Research in Higher Education, Vol. 38 No. 4,pp. 419-433.

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LoGrasso, M.F. (2016), “Easing the burden of external reporting”, in Powers, K. and Henderson, A.(Eds), Burden or Benefit: External Data Reporting, New Directions in Institutional Research,Vol. 166, John Wiley & Sons, San Francisco, CA, pp. 52-58.

Modelo de Indicadores del Desempeño de la Educación Pública (2016), available at: www.colombiaaprende.edu.co/html/micrositios/1752/w3-propertyname-3214.html (accessed January 6, 2017).

Pelikan, J. (1992), The Idea of the University: A Reexamination, Yale University Press, New Haven, CT,pp. 190-197.

Peterson, M.W. and Corcoran, M. (Eds) (1985), “Institutional research in transition”, New Directions forInstitutional Research, Vol. 46, John Wiley & Sons, San Francisco, CA, pp. 17-37.

Project Atlas (2016), “Global mobility trends”, available at: https://p.widencdn.net/hjyfpw/Project-Atlas-2016-Global-Mobility-Trends-Infographics (accessed March 4, 2017).

Reisberg, L. (2011), “Where the quality discussion stands: strategies and ambiguities”, in Altbach, P.(Ed.), Leadership for World Class Universities: Challenges for Developing Countries, Routledge,New York, NY, pp. 128-144.

Swing, R.L. and Ross, L.E. (2016), “A new vision for institutional research”, Change: The Magazine ofHigher Learning, Vol. 48 No. 2, pp. 6-13.

Terenzini, P.T. (1993), “On the nature of institutional research and the knowledge and skills it requires”,Research in Higher Education, Vol. 34 No. 1, pp. 1-10.

Terenzini, P.T. (2013), “ ‘On the nature of institutional research’ revisited: plus ca change…?”, Researchin Higher Education, Vol. 54 No. 2, pp. 137-148.

Volkwein, T.R. (2008), “The foundations and evolution of institutional research”, New Directions forHigher Education, Vol. 141, John Wiley & Sons, San Francisco, CA, pp. 5-20.

Further reading

DiMaggio, P.J. and Powell, W.W. (1991), “The iron cage revisited: institutional isomorphism andcollective rationality in organizational fields”, in Powell, W.W. and DiMaggio, P.J. (Eds),The New Institutionalism in Organizational Analysis, University of Chicago Press, Chicago, IL,pp. 63-82.

Rojas, A. and Bernasconi, A. (2016), “Governing universities in times of uncertainty and change”,in Altbach, P. (Ed.), Leadership for World Class Universities: Challenges for Developing Countries,Routledge, New York, NY, pp. 33-51.

Corresponding authorChester D. Haskell can be contacted at: [email protected]

For instructions on how to order reprints of this article, please visit our website:www.emeraldgrouppublishing.com/licensing/reprints.htmOr contact us for further details: [email protected]

11

IR as a bridge

A comparative study of studentmobility programs in SEAMEO-RIHED, UMAP, and Campus AsiaRegulation, challenges, and impacts on higher

education regionalizationAngela Yung Chi Hou

Graduate School of Educational Leadership and Development,Fu Jen Catholic University, New Taipei City, Taiwan

Christopher HillBritish University in Dubai, Dubai, United Arab Emirates

Karen Hui-Jung ChenNational Taipei University of Education, Taipei City, Taiwan, and

Sandy Tsai and Vivian ChenFu Jen Catholic University, New Taipei City, Taiwan

AbstractPurpose – The purpose of this paper is to examine the student mobility programs of the three initiatives – inSoutheast Asian Ministers of Education Organization-Regional Institution of Higher Education andDevelopment, University Mobility in Asia and Pacific (UMAP), and Campus Asia – and provide acomparative analysis of the respective programs in terms of the role of government, institutional involvement,quality assurance, and challenges. In addition, the paper will assess their impacts on higher educationregionalization by regulatory models toward the end of the paper.Design/methodology/approach – The study adopts qualitative document analysis as a major researchmethod to explore the developmental models of three student mobility programs. Document analysis is anapproach used to gather and review the content of existing written documentation related to the study inorder to extract pieces of information in a rigorous and systematic manner.Findings – ASEAN International Mobility for Students (AIMS), Collective Action for Mobility Program ofUniversity Student in Asia (CAMPUS Asia), and UMAP student mobility schemes have a shared purpose inhigher education regionalization, but with different regulatory frameworks and Functional, Organizational, andPolitical approach models. AIMS and CAMPUS Asia as a strong network and government-led initiatives adopta combination of functional, organizational, and political approaches; UMAP provides university-drivenregional mobility programs with a hybridized force. However, all three of them face the same challenges atregional and national levels, such as different national regulation, coordination among participants, andimplementation of credit transfer schemes.Practical implications – The scale of three student mobility programs is still low, which results in limitedimpact on higher education regionalization in Asia. However, a stronger decision-making modeland increased financial support to universities and students are desirable for the creation of a sustainableand effective network.Originality/value – This is an original research and makes a great contribution to Asian nations.Keywords Higher education regionalization, Student mobility programme, AIMS, UMAP, CAMPUS AsiaPaper type Research paper


Received 29 March 2017Revised 9 May 2017Accepted 5 June 2017


© Angela Yung Chi Hou, Christopher Hill, Karen Hui-Jung Chen, Sandy Tsai and Vivian Chen.Published in the Higher Education Evaluation and Development. Published by Emerald PublishingLimited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyonemay reproduce, distribute, translate and create derivative works of this article (for both commercialand non-commercial purposes), subject to full attribution to the original publication and authors.The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

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1. IntroductionGrowth in the internationalization of higher education is driving the expansion of tertiarysystems and institutions throughout the world. It also articulates cross-border collaborationas well as intensifying student mobility (Daniel et al., 2009; Moor and Henderikx, 2013;Hou, 2014). Student mobility within Asia has been driven and encouraged due to economicgrowth, national competitiveness, and regional development in the early twenty-firstcentury. One manifestation of the trend is a significant increase in the number of studentsmoving within and amongst Asian campuses, such as China, Japan, South Korea, andAssociation of Southeast Asian Nations (ASEAN) countries. It was found that more than ahalf to three quarter of international students on Asian campuses come from the otherneighboring countries (British Council, 2008). According to the United Nations Educational,Scientific and Cultural Organization (UNESCO, 2007) yearbook, there were 57,000 Koreanstudents studying in China, compared to 23,000 Chinese students in Korea; 80,000 Chinesestudents in Japan and 23,000 ASEAN students in China.

While, as a percentage of the total student population, the numbers are still a minority,the increase itself requires response, planning, and understanding. Burgeoning middleclasses and demand for higher education are driving population and uptake and thisincrease is seen within borders as well as across them. Demand for education is notnecessarily on par with affordability and funding mechanisms continue to change and placepressures on governments and institutions, thus forcing an alternative solution for thedemand-driven model currently in place.

There is a growing sense among nations that the regional cooperation and joint effortswill facilitate a creation of a “common educational space” (Sirat et al., 2014). The Bolognaprocess in Europe is perhaps the best example of this regional level of educational systemreform as it not only increases student mobility but also strengthens economic integrationwithin the region. The discussion as to whether Asia, or perhaps ASEAN, should adopt asimilar style approach has been ongoing for the past few years but has largely beenhampered by the pronounced disparity between systems and expectations, particularly interms of income demographics, accreditation, and linguistics.

To date, most efforts toward enhancing higher education regionalization in Asia have beenlinked to three international organizations, Southeast Asian Ministers of EducationOrganization-Regional Institution of Higher Education and Development (SEAMEO-RIHED)supported by ASEAN, University Mobility in Asia and Pacific (UMAP), and Collective Actionfor Mobility Program of University Student in Asia (CAMPUS Asia). Their collective aim isthe intensification of the integration of higher education systems across the region throughstudent mobility programs. Founded in 1967, ASEAN covers a land area of 4.46 million km2,and has a population of approximately 600 million people, which is 8.8 percent of the world’spopulation. Its objective is to develop an integrated ASEAN Economic Community, whichfocuses on a single market with free flow of commodities, services, investment, and skilledworkforce. It has ten full members and one observer member, including Brunei Darussalam,Cambodia, Indonesia, Lao PDR, Malaysia, Myanmar, Philippines, Singapore, Thailand, andVietnam (ASEAN, 2015a, b). In 2003, ASEAN decided to launch several mobility programs inorder to strengthen relations and activities among higher education institutions through theestablishment of the ASEAN University Network (AUN) and the SEAMEO-RIHED(ASEAN University Network (AUN), 2014a). SEAMEO-RIHED aims at fostering “theefficiency, effectiveness and harmonisation of higher education in Southeast Asia throughsystem research, empowerment and the development of mechanisms to facilitate sharing andcollaboration in higher education” (SEAMEO-RIHED, 2016, p. 8). One of the most influentialmobility programs by SEAMEO-RIHED is the ASEAN International Mobility for Students(AIMS) program, also called “M-I-T” (Malaysia-Indonesia-Thailand), launched in 2010(SEAMEO-RIHED, 2012).

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Established in 1991, the UMAP is a voluntary collective of government andnon-governmental organizations. It consists of 19 full country members and565 institutional members, including Japan, Macau, Malaysia, Mexico, Mongolia,Philippines, Taiwan, Thailand, Vietnam, South Korea, etc. (UMAP, 2013). It was expectedthat mobility of university students and staff would be increased through the cooperationamong participating institutions. It aimed at achieving a better regional understandingwithin each of the countries and territories in the Asia Pacific through three major types ofexchange programs (UMAP, 2015).

Launched by China, Japan, and South Korea in 2011, CAMPUS Asia is another regionalstudent mobility initiative. The program was designed to promote student mobility betweenSouth Korea, China, and Japan. It was expected to foster the next generation of leaders inAsia by nurturing young talent with a shared vision. In particular, quality assuranceagencies were mainly responsible for the implementation of the program. Currently, theCAMPUS Asia program has evolved into a unique program that promotes studentexchange, creates a new learning model, and develops in-depth discussions of substantialcollaborations among consortia despite their political, economic, and cultural differences(CAMPUS Asia, 2016a, b).

As Asia looks to respond to the shift in regional student mobility, some key issues mustbe addressed based on a closer alignment of systems and policies, such as regulatoryframeworks, qualification recognition, credit transfer system, and quality assurance(Sugimura, 2012; Knight, 2014). SEAMEO-RIHED, UMAP, and CAMPUS Asia have beenactively committed to higher education regionalization through student mobility programs.Hence, this paper will examine the student mobility programs of the three initiatives listedabove and provide a comparative analysis of the respective programs in terms of the role ofgovernment, institutional involvement, quality assurance, and challenges. In addition, thepaper will assess their impacts on higher education regionalization and harmonization byregulatory models at the end of the paper. To that end, there are five research questionsaddressed as follows:

RQ1. What type of student mobility programs were provided by SEAMEO-RIHED,UMAP, and CAMPUS Asia?

RQ2. What were the regulatory models of the three student mobility initiatives adopted?

RQ3. How did governments and institutions implement the three student mobilityinitiatives? What were their respective roles?

RQ4. How was the quality of the three student mobility initiatives assured?

RQ5. What impact and challenges have the three student mobility initiatives meant forhigher education regionalization?

2. Regionalization and its rise in Asian higher educationOver the past decade, regionalization can be seen to have become a trend worldwide.Traditionally, regionalization has been “viewed within the dual frames of proximity andpatterns of exchange and dimensions that in turn have been conceptualized and actualizedalong prevailing norms of time and space” (Neubauer, 2012, p. 4). It is a formal process ofintegrating regional policies and shared benefits in alignment with global practices(Dale and Robertson, 2002; Beerkens, 2004). Varying types of orientations of regionalizationhave been discussed recently, which will likely lead to different consequences and outcomes.In general, regionalization is often considered as either a subset of globalization or just asubstitute to globalization (Dale and Robertson, 2002; Beerkens, 2004). The former, to someextent, emphasizes the integration of regional policies and practices into a global context in

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alignment with free trade and economic liberalism. On the contrary, the latter tends to resistglobal forces and protect a distinct cultural identity within region.

Scholars have proposed another concept that regionalization is generated from“internationalization” linking to higher education policy. Driven by global competition,improving national internationalization levels of higher education is seen by governmentsas one of the strategies for human resources development and global talent attraction.A notable evolution in higher education internationalization was the rise of regional identityand cultural awareness throughout regional collaborations, engagement, and alliances inhigher education systems.

Higher education is seen as critical to promote regional integration and harmonization.Regionalization of higher education is presented differently according to “the dimensions,actors, and values involved in the process” (Sirat et al., 2014, p. 1). Knight (2012) definedregionalization of higher education as “a process of facilitating, promoting, building andstrengthening closer collaboration and alignment among higher education actors within adesigned area of framework called a region” (p. 10). Throughout an alignment of highereducation systems, collaboration in higher education projects, and activities amongpartners, “it is expected that the ultimate goal of regional integration can be achieved.A rapid growth in regional student mobility can explain a positive sign in the newphenomenon” (Deardorff et al., 2012, p. 480). Under this concept, regionalization, as aregional form of internationalization, aims at integrating global trends and internationalpractices into regional context (Hawkins et al., 2012; Knight, 2013b; SATO, 2014).

Higher education in Asia has been growing rapidly since the 1990s. In recent decades,higher education in Asia has transformed into the massification phase, which not onlygenerates access to higher education but also increases public concern over the globalcompetitiveness of national higher education system. In order to respond to internationalcompetition, efforts toward enhancing higher education regionalization have graduallyincreased in Asia since 2000 ( Jayasuriya, 2009; Knight, 2014; Kuroda, 2014). In general,Neubauer (2012) categorized the development of higher education regionalization in Asiainto two phases: from 1950s to 1980 and from 1980 to present. During the first phase,neighboring countries were grouped due to economics, intra-regional interactions, trade andsecurity, and education. The Association of Southeast Asian Institutions of Higher Learningestablished in 1965 aimed to foster the development of the higher education institutions,develop a sense of regional identity and interdependence, and connect with each other’sregional and international organizations concerned with research and teaching (Chan, 2015).ASEAN, founded in 1967, is another example. ASEAN had two major goals. The first onewas to “accelerate the economic growth, social progress and cultural development.”In addition, it also hoped to build a prosperous and peaceful community of Southeast Asiannations through joint endeavors” (ASEAN, 2016, p. 1).

The period after 1980 to present is a time when Asia was significantly and visiblyimproving. “Rising Asia” has made a big growth in economic progress and scientificdevelopment. The impact of neoliberalism and market deregulation has resulted in themanifestations of a broader-based interregional organization and a multilateral relationshipamong participating members (Marginson et al., 2011). Although the diversified scopes ofregions are overlapping, multi-layered, multi-actors, and multi-faceted, “regionalcollaborations in higher education remains inseparable from the broader geopoliticalcontext” (Nelson, 2013, p. 246). APEC, APQN, UMAP, and ASEAN+3 emerged due to thenewly defined concept. In general, there are three existing regional forms in Asian highereducation including Southeast Asia, East Asia, and a combined Greatest East Asian region.

Marginson et al. (2011) emphasized that a successful regionalization in higher educationonly depends on a sufficient level of economic and social development, geographicalproximity, cultural commonality, and sustained political will of all partners.

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Sugimura (2012) emphasized that “regionalization in Asia has been moved by nationalgovernments and people in general” (p. 47). Instead, Yavaprabhas (2014) argued that“harmonization,” a neutral term, would better replace “regionalization” in higher educationto avoid undesirable consequences, such as uniformity, standardization, homogeneity, etc.

3. Conceptual framework, governance model, and partnership of highereducation regionalization in Asian networksDue to the tendencies of regionalization discussed above, there would be varyingconceptual frameworks for the regulation of higher education regionalization. Earlier inthe 1990s, Altbach proposed a “center-periphery” concept which explains the relationshipbetween knowledge domination by western countries and other developing highereducation systems affected by neo-colonialism (Altbach, 1998, 2004; Kuroda, 2014).During the period, western hegemony in economy and culture predominately influencedthe development of many developing and under-developing Asian countries. Thedisparity in the maturity of higher education systems between western and non-westernnations seemed obvious. Following a booming economy in Asia by the end of thetwentieth century, a rise of Asian awareness and identity has rapidly led to highereducation regionalization in the region. Although “the Flying Geese” model, consideredJapan as an Asian leader, was proposed to the new trajectory of Asian higher educationregionalization, some scholars argued that the model likely overestimated Japaneseinfluences in Asian Pacific and Southeast Asia (Altbach and Umakoshi, 2004;Kuroda, 2014). Instead of a melting pot, currently, “Mosaic type” with an emphasis oncultural diversities and harmonization can be better explained by the new scenario in Asia(Kuroda, 2014). In other words, the current conceptual framework of higher educationregionalization by Asian networks appears to be supportive of multicultural dimensions, localidentities, and diversification through the process of regional collaboration (Hawkins 2012).

Knight (2013a) proposed Functional, Organizational, and Political approaches calledFOPA model that Asian networks would likely adopt with regard to purpose andengagement. Each approach is not completely independent from each other, to some extent,but interrelated. There are two major purposes in the Functional approach initiatives,including an alignment of higher education systems and policies, development ofcross-border collaborative programs, establishment of qualification frameworks, and credittransfer systems in order to facilitate regional harmonization and talent mobility.The Organizational mode focuses a multilevel layer of interactions and a diversity of actors.In this approach, government and non-government bodies, higher education institutions,quality assurance agencies, or other professional bodies are in collaboration with each otherto achieve the ultimate goal of higher education regionalization. The Political model is meantto implement the agenda and higher education initiatives with the strong engagement ofgovernmental policy makers. Signing declaration, convention, agreements, or treaties areregarded as the significant strategies for regional integration and harmonization in thisapproach (Knight, 2012, 2013a, 2014).

When it comes to governance and participation, hard and soft approaches are oftenimplicated by several regional networks or organizations (Hawkins et al., 2012; Chan, 2015).A hard approach means a top-down and structural model which is mainly driven bygovernment and coercive forces. The key participants are ministerial officers. In turn,individuals, universities, or groups could also initiate regional collaborations or projectswith a soft or bottom-up approach. Combining joint efforts from governments andinstitutions, hybridized approach now is drawing more attention. In this approach,governments will likely entrust a group of universities or related higher educationorganizations which are given a certain level of autonomy to take part in the network(Hawkins et al., 2012; Chan, 2015).

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Traditionally, the bilateral approach is considered as one of the most popular partnershipformula of the intellectual collaborations among universities in Asian countries.Two universities from different countries develop a joint degree, double degrees, orshort-term programs collaboratively, aiming at enabling students to develop their globalcitizenship (Terada, 2003; Hou, 2016). In order to enhance regional consciousness andpreserve diversity, the multilateral or multi-layer partnership model that started to flourishin Asian international networks or consortiums is considered as a more effective andefficient approach for higher education regionalization.

In conclusion, international organizations are often regarded as a propeller which givesimpetus to regional integration and harmonization in high education. Currently, “Mosaictype” outlines the new concept of higher education regionalization in Asia. In terms ofpurposes, functions, partnership, and participation, the approaches adopted by Asiannetworks and organizations could be diverse (see Table I).

4. Development and intended consequences of three student mobility programs4.1 AIMS exchange programsStarting in 2010, AIMS was the exchange program developed by SEAMEO-RIHED.The participants were representatives of ASEAN governments. Each participating countrywas entitled to a balance between the number of sending and receiving students.In addition, governments were responsible for funding programs provided, the selection ofparticipating universities, and the fields of the programs. All government representativesheld regular review meetings in order to ensure the quality of the AIMS exchange program(SEAMEO-RIHED, 2014).

To date, seven countries with more than 60 universities have taken part in the initiative.There were more than ten field offerings with a total of 500 courses. The participatingcountries included Brunei Darussalam, Indonesia, Malaysia, Thailand, Vietnam, and Japan.Each year, there was a gradual increase in participating student numbers since theexchange program was launched. Over past five years, the total number of the participatingstudents has risen to 1,200. AIMS targeted elite students, so the selection criteria includedstudying at least one year at home university, GPA score, English proficiency, and learningmotivation. Generally speaking, participating students would take eight to ten creditswithin one to three semesters. All credits awarded at the host university will be transferredinto the home university.

4.2 UMAP semester and super short programsAt the early developmental stage, UMAP was just acting as a platform of informationsharing and exchange in higher education issues. It aimed at the creation of a credit transfersystem in order to facilitate student mobility easily within region. UMAP did not start

Currentconceptualframework

Purposes/functions Governance model Partnership Actors

Mosaic type Functional Soft (bottom up) Bilateral/multilayer UniversitiesOrganizational Hybridized (mutual) Bilateral/multilayer Government and

nongovernment organizations,professional bodies

Political Hard (top down) Multilayer Government and universitiesSource: Authors

Table I.Conceptualframework,

governance model,and partnership ofhigher educationregionalization inAsian networks

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student mobility programs until 2007. Institutional members could nominate a maximum oftwo students per year to take part in the exchange program. However, it is estimated thatonly 50 out of 500 institutions actively took part in the semester exchange programsover years (UMAP, 2013, 2015). In 2011, UMAP launched a new type of program called“Super Short-Term Program” (SSTP). It would last between one and eight weeks long insummer or winter breaks. A wide range of disciplines were offered by participatinginstitutions, such as cultural studies, language courses, arts, business, andentrepreneurship. Most importantly, UMAP awarded each selected participant ascholarship of USD800 (UMAP, 2013).

Generally speaking, the majority of the country members are not actively engaged inUMAP activities, except Taiwan, Thailand, Malaysia, Japan, and Philippines. Only Taiwanand Japanese Governments provided a special scholarship program for selected students. In2016, Philippines Government organized a thematic exchange program titled “UMAPDiscovery Camp” in collaboration with four local institutions. In country members, likeSouth Korea, Hong Kong, and Macau, universities were the country representatives as wellas served as National Secretariat. Universities’ participation was voluntary. The financialsupport from governments is limited.

Student selection criteria were set by each university instead of UMAP committee.UMAP encouraged motivated students to apply for the mobility programs. From 2011 to2015, the number of students who participated in UMAP semester and SSTP was around380. Whether credits gained at the host institution could be transferred and accumulatedstill relied on home university decision though UMAP had developed Credit TransferScheme (UCTS) in 2000.

4.3 CAMPUS Asia exchange and joint/dual-degree programsInitiated by Japanese, South Korea, and Chinese leaders in 2009, CAMPUS Asia aimed atpromoting exchanges with universities among three countries throughout cooperationamong quality assurance agencies. After a joint screening process, ten trilateralcollaborative programs among Japan, China, and Korea were launched in 2011, whichwere implemented on a five-year period. A selection committee by three countries, theKorea-China-Japan Committee for Promoting Exchange and Cooperation amongUniversities, was organized to develop guidelines for selection of trilateral consortia interms of procedures, fields, and quality assurance (CAMPUS Asia, 2016a). The majorcharacteristics of the initiative were the participation of top universities, the inclusion ofjoint/dual-degree programs, as well as the emphasis of quality assurance mechanism.

Based on partnership and collaborative experiences, universities from each of threecountries would form a trilateral consortium in order to develop student exchanges or jointprograms. Although each university would set its own criteria for student recruitment,applicants must be equipped with excellent English proficiency as well as a high academicperformance. Each consortium was to support approximately 30 students per institution(10 outbound students and 20 inbound students). Up to 2014, the number of participatingstudents was approximately 450 with a high proportion of graduate students. The majorityof participants are exchange students, compared to a limited number of degree-seekingstudents (Higher Education Evaluation Center, 2014). Most selected students werefinancially supported by host governments, including scholarship and living expenses.

Quality assurance agencies in three countries played a major role in the initiative.The Japan-China-Korea Quality Assurance Council established jointly by NationalInstitution for Academic Degrees and Quality Evaluation of Japan, Higher EducationEvaluation Center of the Ministry of Education of China, and Korean Council for UniversityEducation of Korea carried out a quality monitoring for the ten pilot programs between 2013and 2015 based on a shared quality assurance framework. In the process of quality

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monitoring, three quality assurance agencies would “address quality assurance ofinternational education, identify and promote successful practices that encourage educationquality throughout the higher education community, and draw up joint guidelines for thequality assurance of transnational education for use by quality assurance agencies in Japan,China and Korea” (CAMPUS Asia monitoring, 2016, p. 1).

5. Analysis and comparisons of three student mobility programsThere are significant differences among the three programs in terms of government role,institutional involvement, and student recruitment. Credit transfer systems and qualityassurance also differ across the three initiatives.

5.1 Regulatory approach, government role, institutional involvement, and studentrecruitmentUMAP was the first and biggest organization committed to developing study mobilityprograms, but the level of government engagement was the weakest among them. Bottom-up/soft approach was adopted at national and international levels. In contrast, AIMS andCAMPUS Asia initiated by a strong international network and governments tended to complywith a top-down/hard regulatory model, including selection of institutions and programs.Institutions could join UMAP activities voluntarily and offer exchange programs at theirdiscretion. Instead, institutions in AIMS and CAMPUS Asia were invited and screened bygovernments first. Institutions in the three initiatives are responsible for program delivery andstudent recruitment, providing an element of autonomy in design and management.

When it comes to student recruitment, AIMS enrolled more students than the other two;graduate students in CAMPUS Asia outnumbered undergraduates. Besides, CAMPUS Asiaintended to attract top students only in comparison with AIMS and UMAP. Up to 2016,AIMS enrolled more than 1,200 students in a relatively higher scale (see Table II).

5.2 Credit transfer system, learning outcomes, and quality assuranceThe credit system is supposed to reflect the number of classes attended as well as otheracademic requirements fulfilled by students. In other words, what students actually learn duringa period should be converted into a number of credits. In order to facilitate student mobility,three initiatives all took a creation of a credit transfer system into consideration. With the initialobjective and modeling European Credit Transfer System, UCTS in 2000 became the first creditsystem designed to be used in the Asia Pacific region. On September 21, 2016, in the 25thanniversary and conference, UMAP published the new version of “UMAP Credit Transfer

AIMS UMAP CAMPUS Asia

Starting year 2010 2007 2011Role of government Actively engaged Loosely engaged Strongly engagedInstitutional involvement Nominated/responsible

for program and coursedelivery/set criteria forstudents recruitment

Voluntary/responsible forprogram and coursedelivery/no specific rulesfor student selection

Invited/responsible forprogram and coursedelivery/set criteria forstudents recruitment

Students participation(2011-2015)

Around 1,200/motivatedstudents/undergraduate

379/motivated students/undergraduate

450/elite students/graduate

Quality assurance Accredited program/external reviews are notavailable

No review Internal and externalreview by three QAagencies’ internal review

Credit transfer system UCTS/ACTFA UCTS NoneSource: Authors

Table II.Developmental modelsamong AIMS, UMAP,

and CAMPUS Asia

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Scheme: User’s Guide.” In the new guidebook, it summarized that one UCT was equivalent to38-48 hours of student workloads, including 13-16 academic hours of instruction (UMAP, 2016).UMAP expected that all participating institutions would apply the principles for the creditsearned by exchange students at the host university.

In addition to UCTS, the AUN created AUN Credit transfer system (ACTS)for 30 participating institutions in 2009 and implemented it as a pilot project in 2011(ASEAN-AUN-ACTS, 2013; ASEAN, 2015a, b). Through the adoption of ACTS gradingscale in which student learning outcomes would be ranked into five subgroups from A(excellent) to E/F (fail), host universities would provide students a “Certificate ofCompletion” signed by the AUN-ACTS Secretariat as well (ASEAN University Network(AUN), 2014a, b; Sujatanond, 2016).

Because ACTS are only applicable for AUN institutions, therefore, SEAMEO-RIHED isplanning to develop a new credit transfer scheme called Academic Credit TransferFramework (ACTFA) for all higher education institutions in Southeast Asia, particularly forAIMS, in order to harmonize existing credit transfer arrangements in Asia (SEAMEO-RIHED,2014). But UCTS has been adopted by three AIMSmember countries, Thailand, Malaysia, andPhilippines, who actively participated in UMAP’s exchange program. Moreover, PhilippinesGovernment officially requested all universities and colleges to follow UCTS guideline forexchange programs.

In order to assure learning outcomes of students studying at all participatinginstitutions, credit transferability was regarded as one of the characteristics of CAMPUSAsia. Yet, there was no specific system developed by the initiative. Instead, CAMPUS Asiaundertook a quality monitoring process by three quality assurance agencies to determinewhether the quality of the mobility program in trilateral consortiums was ensured.In contrast, quality assurance systems were not embedded into AIMS and UMAP initiatives.ASEAN Quality Assurance Network, as a collective body of all ASEAN quality assuranceagencies, did not conduct any quality review activities over AIMS yet. Besides, there was nosign that UMAP would collaborate with other quality assurance networks, such as APQN inthe near future (Table II).

6. Discussions6.1 FOPA model implication and regulatory governanceExamining these three initiatives using Knight’s FOPA model, AIMS and CAMPUS Asiaconsists of three functional, organizational, and political tendencies. In contrast, UMAP fallsin the functional mode only. Both AIMS and CAMPUS Asia utilized practical strategies andpolicy which facilitate closer alignment and student mobility within region. Governments,institutions, and quality assurance agencies collaborated with in the developmental process,credit transfer framework, and quality assurance model of student mobility programs.Based on political will, AIMS and CAMPUS Asia signed multi-layer agreements, promotedregional policy dialogs, and developed funding schemes to formalize initiatives “in order tomake regionalization of higher education a priority” (Knight, 2013a, p. 120). With a well-known and established credit transfer system, UMAP had a more functional strategy topromote higher education regionalization. Yet, given the reality that UMAP was lacking astrong governmental support and organizational architecture, UMAP would exert itslimited influence over institutions and students (see Table III).

Furthermore, an understanding of the regulatory models of the three initiativesdemonstrates that a top-down and government-driven student mobility scheme tends to bemore effective than a bottom-up model or a hybrid type. AIMS and CAMPUS Asia initiativesdemonstrate that the political support and financial scholarship from the government couldstrengthen institutional involvement and encourage student participation. In other words,AIMS and CAMPUS Asia initiatives are meant to have an emerging influence on higher

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education regionalization due to their hard approach in comparison to UMAP’s hybridizedforce. In general, three initiatives still exerts little influence on regional integration due to alimited scale of the program. However, it can be predicted that a top-down, hard, andintentional approach would likely lead to program sustainability in the long run. This is ofparticular relevance for future integration debates where the level of disparity is pronouncedand the individual national functions distinct and varied.

6.2 Quality, challenges, and impacts on regionalizationCredit transfer systems and quality assurance mechanisms are the key elements in fosteringstudent mobility programs (Knight, 2013a; Yonezawa et al., 2014). Although UCTS, ACTFA,and quality monitoring were created by three initiatives, respectively, the coordinationbetween governments, institutions, and quality assurance agencies would need to beimproved further. Furthermore, diversity in national regulations, academic calendars, andgrading policies in Asian higher education would continue to challenge the implementationof three initiatives. Nevertheless, quality remains the major concern of three initiatives, withonly CAMPUS Asia undergoing an external quality review of the programs provided byparticipating institutions. The inclusion of quality assurance mechanism in the other twoinitiatives is still under development (CAMPUS Asia, 2016b).

As Horie (2014) indicated, “operating quality programmes requires teaching andcoordinating staff who fully understand the pedagogical principles and are capable offacilitating such learning inside and outside the classroom” (p. 19). In the short-termdevelopment, AIMS, CAMPUS Asia, and UMAP should think of advising participatinginstitutions and their staff to apply the new academic credit system and change their currentgrading system. For a long-term perspective, engagement of national QA agencies orregional QA networks will be getting more and more significant.

Yet, it is important to note that the total number of students moving within Asia Pacificand Southeast Asia throughout three initiatives remains relatively low. So, there was limitedevidence to assess the impacts they brought into higher education regionalization. SinceAsian networks have a shared goal to intensify the integration of higher education systemsacross the region, they anticipate that student mobility schemes would serve as a catalystthat “recognizes diversity of higher education systems and cultures within the region whilepromoting common practices and guidelines” (Fahmi, 2013).

7. ConclusionAIMS, CAMPUS Asia, and UMAP student mobility schemes have a shared purpose inhigher education regionalization, but with different regulatory frameworks and FOPAmodels. AIMS and CAMPUS Asia as a strong network and government-led initiatives adopta combination of functional, organizational, and political approaches; UMAP providesuniversity-driven regional mobility programs with a hybridized force. However, all three of

AIMS UMAP CAMPUS Asia

FOPA Functional/organizational/political

Functional Functional/organizational/political

Governance model Top-down/hard force Bottom-up/hybrid type Top-down/hard forceManagement International network led University led Government ledChallenge Quality/organization/

coordination/languageBudget/quality/governmentsupport/language

Learning outcomes/language

Impacts Low Low LowSource: Authors

Table III.Regulation, challenges,

and impacts amongAIMS, UMAP, and

CAMPUS Asia

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them face the same challenges at regional and national levels, such as different nationalregulation, coordination among participants, and implementation of credit transfer schemes.Experience from three initiatives demonstrates that credit transfer has become a key issuein promoting student mobility and exchange, in which a credit calculation system should beassociated, and connected, with learning outcomes. Concurrently, the question as to how toharmonize the different credits and grading systems that can recognize learning outcomesand experiences across countries and higher education institutions becomes a major concernat three initiatives (Sirat et al., 2014).

Up to present, the scale of three student mobility programs is still low, which results inlimited impact on higher education regionalization in Asia. However, a stronger decision-making model and increased financial support to universities and students are desirable forthe creation of a sustainable and effective network. Knight (2013a) elaborated that:

There is no one way or right way to go about higher education regionalization. Each region,however defined, will develop its own path which acknowledges and respects the commonalitiesand differences among higher education institutions and systems (p. 123).

Although regionalization of higher education is still under-developed in the region, Asiannations have begun the process of collaboration to achieve their ultimate goal of regionalintegration and harmonization through alignment of higher education systems and studentmobility programs. It can be foreseen that the joint efforts among varying higher educationstakeholders to achieve regionalization will be getting more and more significant.

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content&view=article&id=155:seameo-rihed&catid=98&Itemid=519 (accessed October 25, 2015).SEAMEO-RIHED (2016), “2015-2016 annual report”, SEAMEO-RIHED, Bangkok.Sirat, M., Azman, N. and Bakar, A.A. (2014), “Towards harmonization of higher education in Southeast

Asia: Malaysia’s perspective”, Inside Higher Education, April 13, available at: www.insidehighered.com/blogs/globalhighered/towards-harmonization-higher-education-southeast-asia

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Kitamura, Y., Meerman, A. and Kuroda, K. (Eds), Emerging International Dimensions in EastAsian Higher Education, Springer, Singapore, pp. 81-102.

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Corresponding authorAngela Yung Chi Hou can be contacted at: [email protected]


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The development ofMalaysian universities

Exploring characteristics emerging frominteraction between Western academic models

and traditional and local culturesMolly Lee

The HEAD Foundation, SingaporeMorshidi Sirat

Commonwealth Tertiary Education Facility, Bayan Lepas, Malaysia, andChang Da Wan

National Higher Education Research Institute,Universiti Sains Malaysia, Penang, Malaysia

AbstractPurpose – The purpose of this paper is to investigate, in general, what are the contemporary externalinfluences that have been dominant in Malaysian universities and what are the major local traditionalpractices that are also found in these universities.Design/methodology/approach – From the literature review, the paper proposes a conceptual frameworkto explore hybridity in governance and management, programs and curriculum, teaching and learning, andresearch and service.Findings – Using the conceptual framework, the paper discusses the Malaysian higher education in terms ofWestern influence and indigenization of Western models, the background context of Islamic universities andseven possible hybridities compiled from anecdotal evidences.Originality/value – The conceptual framework and possible hybridities identified in the paper serve to providethe guide to a more systemic empirical investigation to examine the characteristics of Malaysian universitiesemerging from the interaction between external influence and local cultures. The Malaysian case also potentiallycontribute in exploring the question, “Are Asian universities different from Western universities?”.Keywords Hybridity, Malaysian universities, Traditional and local culturesPaper type Research paper

IntroductionThe development of higher education in the Asian region in the past decade has been quiteimpressive when compared to other regions such as Sub-Saharan Africa and the Arab States.The rapid expansion of higher education in Asia can be attributed to increasing social demandfor higher education brought about by partly population growth, the democratization ofsecondary education and the growing affluence of many countries. The statistical data showsthat the tertiary gross enrollment ratios from 1999 to 2009 have increased from 14 to 28 percentin East Asia and the Pacific, from 19 to 22 percent in Central Asia, and from 9 to 13 percent inSouth and West Asia (UNESCO Institute of Statistics, 2011). Besides widening access to highereducation, many governments are implementing policies to improve educational opportunities

Higher Education Evaluation andDevelopment

Vol. 11 No. 1, 2017pp. 25-37

Emerald Publishing Limited2514-5789

DOI 10.1108/HEED-08-2017-004

Received 3 May 2017Revised 26 June 2017

Accepted 29 June 2017


© Molly Lee, Morshidi Sirat and Chang Da Wan. Published in the Higher Education Evaluation andDevelopment. Published by Emerald Publishing Limited. This article is published under the CreativeCommons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and createderivative works of this article (for both commercial and non-commercial purposes), subject to fullattribution to the original publication and authors. The full terms of this licence may be seen athttp://creativecommons.org/licences/by/4.0/legalcode

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Developmentof Malaysianuniversities


among the disadvantaged groups in particular the women, rural populations, the poor and theminority groups.

The rapid expansion of higher education and the rising unit cost have causedtremendous fiscal strain on many governments which led them to restructure their highereducation systems. The restructuring of higher education in various countries involvedthe privatization of higher education, the corporatization of public universities,the implementation of student fees and the formation of strategic partnership betweenpublic and private sector in the provision of higher education. As higher education systemsexpand, they become more bureaucratic and regulated so as to ensure the provision ofquality higher education. National quality assurance and accreditation agencies wereestablished to ensure greater public accountability and transparency from higher educationinstitutions especially with regard to quality and their performances in the variousuniversity ranking tables.

Quite a number of Asian countries are investing heavily on their flagship universities inorder to elevate them to world-class status. For examples, China implemented its project211 and 985; South Korea introduced its “Brain Korea 21”, “World-Class University” and“Study Korea” projects; Taiwan initiated the “Excellence Initiatives”; and Japan changed itsfunding model to strengthen its top 30 universities. In all these projects, substantialresources are channeled to selected universities so that they can become world-classresearch universities. These countries also invested heavily on research and development(R&D). It was reported that the economies of East/Southeast Asia and South Asia includingChina, India, Japan, Malaysia, Singapore, South Korea and Taiwan represented 25 percent ofthe global R&D total in 2001 but accounted for 34 percent in 2011. China (15 percent) andJapan (10 percent) were the largest R&D performers in this group (National ScienceFoundation, USA, 2014).

There is no doubt that Asian universities have made tremendous strides in terms of studentenrollments as well as the volume and quality of research outputs, but the outcomes of theirfuture developments are yet to be seen. To some, Asian universities are joining the world’sleading universities and may soon overtake their Western counterparts (Marginson, 2011;Morgan, 2011), but there are others who predict that Asian universities may hit a “glassceiling” because they maintain that Asian universities are basically imitative rather thancreative. Thus, the inputs of financial and other resources can make progress only so far(Altbach, 2010; Mohrman, 2005). It is interesting to note that both sets of arguments citedculture as the reason for its predicted outcomes. Therefore, it is pertinent to raise the question“Are Asian universities different from those in Western countries?”.

Research problemA comparative study consisting of nine cases has been launched to explore this researchquestion. The nine cases comprise three mainstream universities, three Islamic universitiesand three Chinese community-based universities to provide a robust sample in capturing thediversity of ethnic/religious influence in Malaysian higher education. Mainstreamuniversities refer to the majority of universities in Malaysia which have strong Britishand American influence, and the three selected include a public research university, privatenon-profit university and private for-profit institution owned by a company listed on theKuala Lumpur Stock Exchange. Two of the three Islamic universities are public universitiesand the other is private, while all three Chinese community-based are private institutions.

The aim is to examine in what ways are Asian universities differ from those in theWesterncountries and why do such differences emerge. The proposed hypotheses are as follows:

H1. Asian universities are different from Western universities because of hybridizationwhere Western academic models interact with local traditional cultures in differentsocial settings.

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H2. Asian universities are not only influenced by global trends in higher education butthey are also influenced by Asian values which are embedded in the Islamic,Confucian or Buddhist traditions.

The purpose of this paper is to investigate hybridity in Malaysian universities. Hybridity willrefer to the contemporary external influences that have been dominant in Malaysianuniversities interacting with major local traditional practices that are also found in theseuniversities. The paper will further examine how the traditional values and practices haveinteracted with more recent external influences in Malaysian universities. More specifically, thepaper highlights some of the hybridities that may exist in some of the Malaysian universities.

Literature reviewMuch has been written about the Western origins of Asian universities. Altbach (1989) statesthat “In Asia, as in other parts of the Third World, the impact of Western academic models andinstitutions has been significant from the beginning and it remains important even in thecontemporary period” (p. 9). The Western academic models include patterns of institutionalgovernance, the ethos of academic profession, the rhythm of academic life, ideas about science,procedures of examination and assessment, in some cases the language of instruction, and otheraspects of higher education. Studies have shown that various models have been imported bymany Asian countries during the colonial period including China, Japan and Thailand eventhough these countries have not been under colonial rule. The French model was imported byformer French colonies such as Cambodia, Laos and Vietnam with the Dutch influence inIndonesia as well as the American influence in the Philippines. The British model was inheritedby India, Pakistan, Bangladesh, Sri Lanka, Malaysia, Singapore and Hong Kong, while theGerman model had its impact in Japan, South Korea and Taiwan (Neubauer et al., 2013). It waspointed out that the continuing impact of the West is still very significant throughout Asia asexhibited in the pervasive and subtle influence of the English language, the idea of theuniversity as a meritocratic organization, the importance of scientific research, the notion ofacademic freedom and institutional autonomy (Altbach, 1989).

While Asian universities are patterned on Western models, it is also clear that many Asiancountries have adapted the model to meet local needs and realities. There has been considerableinterplay between foreign influence and Asian realities. As Hawkins (2013) argues, “the so-calledmodern universities is actually, in some settings (e.g. China and India), and perhaps in manysettings, a hybrid of indigenous elements, overlaid with Western forms and elements, resultingin a reindigenized hybrid” (p. 52). He maintains that the strong intellectual traditions ofConfucianism and Buddhism were firmly entrenched prior to Western contact and continue todominate many aspects of social, cultural and educational life in the Asian region. On the sameline of argument, theMuslim tradition is paramount inMalaysia and Indonesia while the RomanCatholic tradition is in the Philippines, and so on (Shin, 2013).

Using the indigenization perspective, Marginson (2011) constructed “the ConfucianModel” of higher education in East Asia and Singapore. The Confucian systems of highereducation consisted of four interrelated features as follows:

(1) a strong nation state which steers and control the development of higher education;

(2) high tertiary participation with a large private sector and household funding;

(3) high stake public examinations; and

(4) strong state support for research.

According to him, the Model is not a simple adaptation of the Western university in EastAsia but rather it is an organic hybrid of old and new, and East and West. It has beenpointed out that some of the characteristics of the model are related to Asian values, such as

27


the role played by a strong state presence and centralized governments in pursuingcollective well-being (Chan, 2013). The concept of Asian values is defined as to includefamily solidarity, filial piety, collective good, social harmony, consensus as well as hardwork ethics (Tu, 1989).

However, in the era of globalization, much of the recent development of higher educationis influenced by global trends such as the massification, marketization, bureaucratizationand internationalization of higher education (Lee, 2013). In analyzing the global influenceson higher education, some scholars maintain that globalizing practices such as internationalbenchmarking, greater use of English, strive toward world-class university, andtransnational higher education might create homogenizing forces to converge Asianuniversities in line with Western universities, in particular, at the institutional level.As Chan (2013) argues, “it is undeniable that more internationalized institutions in EastAsian universities are converging to Western style, particularly those in pursuit ofworld-class status” (p. 43). His study shows that due to greater internationalization of highereducation, Asian universities are again adopting Western practices and standards whichoften may go against the kind of Asian values that are embedded in these societies.

In examining the impacts of globalization on education, it is important to note that globalforces do not operate only in the economic sphere nor do they originate only from the West.In recent decades, one has witnessed the spread of Islamic resurgence in many Muslimcountries, including Malaysia. The intellectual characteristics of this global trend are thefervent belief that society should be organized on the basis of Islamic religion, advocacy forgreater political freedom, and a general aversion to Western civilization (Chandra, 1987).These characteristics are quite evident as reflected by the political uprisings in the“Arab Spring” countries and the number of terrorist attacks against Western powers suchas the September 11 (2001) and the Bali bombing (2002) incidents. The spread of Islamicrevivalism can be attributed to various factors. According to Turner (1991), thefundamentalist revival in Islam is an example of the relativizing effect of globalization. Hemaintains that Western modernization in either its capitalistic or Marxist forms failed todeliver either material benefits or a coherent system of meanings to the Islamic world.Indeed, rapid industrialization and urbanization appeared to offer only stark inequalitybetween the populace and the politically dominant elite. Islamic revivalism in variousMuslim countries marks a rejection of Western modernization and secularism which areembedded in these Islamic countries arising from colonization and globalization.

The Islamic revivalism has impacted on the higher education sector as well. Not onlymany Islamic universities were established in various Muslim countries, these universitiesalso network and exchange ideas on how to develop the concept of Islamic higher education.For example, in 2010, the Muslim Universities’ Vice Chancellors’ Forum was held in KualaLumpur, Malaysia and the theme was “Charting New Directions for Muslim Universities:Must We Subscribe to Western Ideological and Philosophical Constructs?”. During thatconference, much of the discourse revolved around issues on Islamic education, Islamichigher education and Islamic higher education philosophy (Fauziah and Hafiz, 2012). It wasreported that one of the objectives of the conference was to establish cooperation among theMuslim universities to develop higher education differently from the conventional Westernstyle. Therefore, the following research question is timely and very appropriate:

RQ1. Are Asian universities different from Western universities?

The following section proposed a conceptual framework for the research study.

Conceptual frameworkThe concept of hybridization is commonly used not only in the natural sciences but also in thesocial sciences in fields such as cultural studies, media studies and studies of globalization.

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Hybridization is defined as “the ways in which forms become separated from existingpractices and recombine with new forms in new practices” (Rowe and Schelling, 1991, p. 231).This principle can be extended to structural forms of social organization, including theuniversities. In cultural studies, cultural hybridization refers to an amalgam of cross-culturalinfluences which are blended, patchworked and layered upon one another (Yazdiha, 2010).The notion of cultural hybridity in postcolonial theory is the culture arising out of interactionsbetween “colonizers” and “the colonized”. In a communication theory, hybridity is a used as adevice for describing the local reception of global media texts as a site of cultural mixture(Kraidy, 2002). This notion is further extended to the studies of cultural globalization wherehybridity is taken as a clear product of global and local interactions.

Kraidy (2005) maintains that “since hybridity involves the fusion of two hithertorelatively distinct forms, styles or identities, cross-cultural contact, which often occursacross national borders as well as across cultural boundaries, is a requisite for hybridity”(p. 5). In the analysis of globalization, the cross-cultural contact occurs through themovement of people, ideas and practices across national borders. Hybridity hasemerged as a privileged site for conceptualizing global and local articulations.The interactions between foreign and domestic influences can produce a variety ofoutcomes. For example, the media-culture industries in regional centers such as Brazil,Mexico and Hong Kong have increasingly indigenized Western genres. A studyof the media-culture industries in Hong Kong (Lee, 1991) shows four patterns ofindigenization: the parrot pattern refers to a wholesale mimicry of foreign culture by localindustries – both in form and content; the ameba pattern describes a modified form but anon-changing content such as the adaptation of a foreign movie for local consumption; thecoral pattern describes cultural products whose content is changed but whose form isuntouched; and the butterfly pattern is a radically hybridization that makes the domesticand foreign indistinguishable.

In the literature on higher education in Asia reviewed above, the hybrid university isoften being mentioned. The research question would then be:

RQ2. What does a hybrid university look like?

If hybridization is the interaction between Western academic models and traditionalcultures resulting in institutional hybrids, then what are these institutional hybrids indifferent national settings. A further question would be:

RQ3. Which are the likely sites of hybrid formation in a higher education institution?

It is postulated that hybrid formation would occur in the following domains:

• hybridity in governance and management;

• hybridity in programs and curriculum;

• hybridity in teaching and learning; and

• hybridity in research and service.

Therefore, the research project will examine what a hybrid university would look like in asociety that is embedded in the Confucian, Islamic or Buddhist traditions. It will also explorethe sites of hybrid formation at the institutional level to identify the various kinds ofinstitutional hybridities that may have emerged.

The Malaysian caseMalaysia is an interesting case because it has not only a strong colonial influence under theBritish rule, but it is also a Muslim country that is undergoing Islamic resurgence. The rest

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of this paper is an analysis of the British legacy and American influences on the Malaysianuniversities in general and more specifically an analysis of the Islamic universities whichcan be viewed as a hybrid university.

Western influenceMalaya has been under the British colonial rule before achieving its independence in 1957.The higher education system that developed in the multi-ethnic society of Malaysia(after 1963) had its origin from Great Britain. Its first university, University of Malaya, whichwas established in 1959, was an implantation of a British higher education model (Selvaratnam,1986). The export of the British model by the colonial master was reported as “If we were goingto export universities to our overseas dependencies they would of course be Britishuniversities, just as the cars we export there are British cars” (Ashby, 1966, p. 224).

As found in British universities then, the academic activities were organized and revolvedaround a number of core disciplines that form the body of knowledge that was used in teachingand research. The medium of instruction was English and most of the faculty members wereexpatriates. The reading and reference materials used were basically European and mainlyBritish in content and character. The authorities of the university included the court, the council,the senate, the faculties, the boards of studies, the boards of selection, the board of studentwelfare, the guild of graduates and other such bodies. The vice chancellor was appointed by theuniversity council as the principal of academics and executive officer of the university.The council was the governing body of the university and the principal authority in determiningbroad policies for the whole university. The senate was in charge of academic matters and it wasmade up solely of academics. The registrar took care of both academic and administrativeaffairs while the bursar dealt with financial matters (Lee, 1997).

As the years went by, expatriate academics from America and local academics who weretrained overseas were hired and soon the American influence was beginning to be felt inUniversity of Malaya as well as in the newer universities[1] that were established in the1970s and 1980s. Many of the Malaysian universities adopted both the semester and creditsystems. Continual assessment throughout the course and Grade Point Average wereimplemented in most of the universities. Some of the universities have schools instead offaculties, and many of the programs are multidisciplinary in approach. The Americannomenclature of professor and associate professor became widely used. It can be said thatmany of the Malaysian universities are a hybrid of British and American model (Lee, 1997).

Indigenization of Western modelsIn the early years of independence, University of Malaya has a strong academic traditionwith autonomy. The main power was located within the university itself, as in the Britishmodel. The university was allowed to draw up its course content, award its own degrees,hire its own faculty and admit its own students. This academic autonomy was maintaineduntil the “Universities and University Colleges Act” was passed in 1971. This Act has farimplications on the governance and management of Malaysian universities until today.

The Western models of university with their knowledge structure and organizations,their curricula and standards, and their social functions could not meet the needs of amulti-ethnic society and a rapidly developing economy, with a high population growth rateand marked economic inequalities along ethnic lines, as was the case in Malaysia(Selvaratnam, 1986). As many of the academics then were from foreign countries, they weremore concerned and preoccupied with their respective academic disciplines, standards andnorms from the international academic community instead of addressing socio-politicalissues that were prevalent in the local communities. Similarly, most of the local academicswho had Western training were socialized toward a Western educational perspective,intellectual culture and professional expectations of their respective host countries.

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Within the Malaysian universities, a good deal of the teaching and research was not relevantto the societal problems that confronted their immediate environment. In fact, it was theautonomy that the academic community enjoyed which allowed them to identify themselveswith the international knowledge system rather than the local issues and problems. In sum,the Western models seemed to be divorced and isolated from the political, socio-economicdevelopment of the country. Thus, steps were taken by the Malaysian government toremedy the situation.

As mentioned earlier, there were marked economic inequalities along ethnic lines.The inequitable distribution of income, which was closely linked to the inequality ofeducational opportunities, became a prominent political issue among the different ethnicgroups in Malaysia. The Malay ruling class realized that the economic imbalances alongethnic lines between the Bumiputras and non-Bumiputras, if remained uncorrected, wouldlead to intense political and social conflicts. Thus, the Malay-led government took concretesteps to restructure the Malaysian society by providing educational opportunities to theBumiputras. Education, and in particular higher education, is viewed as an instrument forsocial mobility as well as social cohesion. In 1971, the “Universities and University CollegesAct” (Malaysia, 1971) was passed and this Act provided a common legislative andregulatory framework for all universities in Malaysia.

The indigenization of the Western models is reflected in a number of key features in thislegislative framework. First, the autonomy of the universities are curtailed and the highereducation system becomes a strong state-coordinated system. The Act ensured that no newfaculty or course may be introduced at any of the universities without prior consultation withthe Minister of Education. Second, the medium of instruction was converted from English toBahasa Malaysia which is the national language. The usage of the national languageaccompanied by the emphasis on a curriculum that is relevant to the local socio-economic andcultural needs gave the impetus to the development of an indigenous knowledge culture.Third, an ethnic quota system for student admission to the public universities, which wasbased on the racial composition of the population, was implemented. In order to effectivelycoordinate the implementation of this policy, the Ministry of Education established a CentralProcessing Unit for Universities which deals with all the selection of students for admission tothe public universities. As observed by Selvaratnam (1988):

The implementation of this tightly controlled process of selection and admission into the country’suniversities eroded one of the deep-rooted and jealously guarded academic traditions of universityautonomy, that is, the practice of allowing each university to determine its own admission policyand criteria (p. 184).

The government’s justification for this policy was to widen access to higher education incongruent with the needs, aspirations, and expectations of the people, and more importantlyto the Bumiputra community on whose support the ruling regime relies heavily.

With the implementation of the ethnic quota policy, many students from the minoritygroups (Chinese and Indians) experienced difficulties in gaining admission into the publicuniversities even though they were qualified to be admitted. To overcome this bottleneck, aninfluential and economically affluent group from the Chinese community wanted toestablish the Merdeka University in the 1970s but it was turned down by the Malay-ledgovernment (Selvaratnam, 1986). This university was supposed to cater for the excessdemand for higher education among the Chinese whose traditional Confucian values placehigh aspirations for education and the medium of instruction was supposed to be Chinese.However, the political conditions at that time did not favor the establishment of such auniversity. Thus, it was not until two decades later before the Chinese community wasallowed to set up their own higher education institutions to meet the demands mainly,but not exclusively, of those Chinese-medium students of Chinese Independent secondary

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schools who for various reasons could not further their education in the public universities.Some of the higher education institutions that are supported by the Chinese communityinclude the Southern University College which was established in 1990, New Era College in1997 and Universiti Tunku Abdul Rahman in 2002.

These community-funded “Chinese Universities” in Malaysia have their roots in the traditionof Chinese education which aims at perpetuating the culture of the Chinese community lest itlost its cultural roots (Mok, 2015). Its niche function is to study and research on local Chineseculture and history with special attention on inter-ethnic relations and issues that concern socialharmony and national unity. It is posited that this is one type of higher education institutions inMalaysia where various kinds of institutional hybridities are likely to emerge.

Islamic universitiesUnlike other countries such as Indonesia, Islamic higher education in Malaysia is a recentphenomenon. While the Indonesian’s Institutions of Islamic Higher Education wereestablished as early as in the 1940s as natural extensions of the widely spread madrasahs(traditional Islamic schools) and pesantrens (traditional Islamic boarding schools) (Fu’ad andJamhari, 2003), the first Islamic university in Malaysia was established in 1983 and this isthe International Islamic University Malaysia (IIUM). A few other Islamic higher educationinstitutions were established even later such as the Selangor International IslamicUniversity College in 1995 and Universiti Sains Islam Malaysia (USIM) in 1998.

The establishment of these Islamic higher education institutions can be attributed to theIslamic resurgence that was spreading across the world in the 1970s and 1980s. The IIUMwas in fact an initiative of the Organization of Islamic Cooperation (OIC). It was aninternational effort to establish a higher education institution based on Islamic principles.In the Islamization of knowledge, Islamic values are inculcated into all the disciplines.Representatives from eight OIC countries[2] sit in the Board of Governors of this university.The medium of instruction are English and Arabic and the university admits a greatnumber of international students from Muslim countries. The more recent USIM is a publicuniversity established by the Ministry of Education to cater mostly to students whoattended sekolah agama (Islamic religious schools). The focus of this university is onIslamic studies and the development of good character. The Selangor International IslamicUniversity College is a private institution which was established by the Selangor StateIslamic Religious Council with the aim of producing Islamic professionals who can leadsociety as well as develop the Islamic knowledge.

The unique features of Islamic education are to bring back religion into the curricula and toinfuse the Islamic revelation with scientific knowledge. The focus is on Islamic studies. As SyedNaquib Al-Attas (1991) stated that the concept, content and process of Islamic education isbased on revealed truth, particularly on the reality and concept of God. Islamic pedagogiesfocus on the integration of Naqli (revealed knowledge) and Aqli (human knowledge) with theaim of transforming society. In Islamic higher education, the emphasis is on the holisticdevelopment of the individual. In Islam, the ultimate aim of education is more than securing anearning activity but to realize the complete submission to Allah, and equipping oneself withbalanced development of his or her spirit, intellect, feelings and body (Gulam, 2000). To put itsuccinctly, Islamic higher education is to mould the souls as well as inform the intellect.Thus, the curricula tend to emphasize ethics, morals, values and soft skills and the graduateswould be religious-focused instead of skilled-focus. The Islamic higher education philosophy isto acquire knowledge for the common good and promote widespread of knowledge sharing(dakwah) which is quite contrary to the concept of commercialization of R&D through patentsand licenses. In other words, the outputs of any R&D effort should benefit the “bottom billion”and not just for commercialization. Thus the Islamic universities would be another site forhybrid formation in the higher education sector in Malaysia.

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Possible hybriditiesThe following is a list of possible hybridities that may be found in various higher educationinstitutions in the Malaysian context. This list is compiled from anecdotal evidences whichneed to be proven through systemic empirical investigation. Moreover, each of the possiblehybridities lies in a continuum with the dichotomies at the extreme ends but the manifestationof each hybridity can occur anywhere along the continuum in a particular setting. The list isneither exhaustive nor is it arranged in any particular order of importance:

(1) Religious influence: while the principle of secularism is commonly practised inWestern countries, it is not the case in many Asian countries which see themselvesas Muslim countries, Buddhist countries, Hindu countries or others.The separation of the state from religious institutions is very clear cut inWestern countries, whereas many countries in the Asian region have a national orstate religion. In many instances, the strong religious influences have penetratedmany social institutions including the universities. Taking the Islamic universitiesin Malaysia and the Buddhist universities in Thailand as examples, religiousstudies are very much part and parcel of the university curricula. However, thereare variations of the degree of religious influence along the continuum.For instance, there are pure secular private universities in Malaysia which donot have a mosque in its campus; there are also secular public universities whichfeature a mosque in the campus; and then the Islamic universities where themosque plays a central role in the university campus. As a Muslim country,Malaysia has been legislated that all its universities must teach Malaysian Studies(including Islamic and Asian civilizations), Islamic Studies (for Muslim students)and Moral Education (for non-Muslim students). The rationale for this ruling is toestablish a Malaysian education identity (Lee, 2004).

(2) Architectural identity: while most of the Malaysian university campuses havemodern architectural buildings, it is not the case in the Islamic universities and“Chinese” universities. For example, the Chancellery building of USIM sported acentral dome which is a typical feature of Islamic architecture that dates back tothe Ottoman empire in the fifteenth century. On the other hand, UTAR hascombined traditional Chinese design with modern architecture. The Ling LiongSik Hall in UTAR campus in Kampar has a large sweeping roof which has asweeping curvature that rises at the corners of the roof. Both these universitiesmark their unique identities in the architectural form of the central building foundin their campuses.

(3) Research methodology: the scientific inquiry is well understood to be a methodologycommonly used to seek for truth in the natural world. It is a way of investigatingthings with proposed explanations for the observations. The scientist is free toidentify and define his research problem and ask his research questions and then hewould use the scientific method to investigate the problem. However, it is not thesame in the study of Islamic theology. The starting point is to accept the revealedtruth as presented in the theological texts. Islamic studies consist of using variouspedagogical approaches to study fiqh (Islamic jurisprudence), tasawaf (Islamicmysticism), tafsir (Quaranic exegesis) and akhlak (ethics) (Fu’ad and Jamhari, 2003)but not to question the basic premises of the religion.

(4) Interpersonal relationships: the interpersonal relationships among colleagues andthose between faculty members and students can be quite different in varioussettings. In many of the Western university settings, collegial relationships arecommonly found among the academics but in the Malaysian campuses the

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interpersonal relationships can be quite hierarchical. For example, the dean of afaculty can actually direct a junior academic to collect data for the dean’s researchproject without any due acknowledgment. In the case of faculty and studentrelationship, it is usually quite informal in a Western setting where they addresseach other by their first names, but that is not the case in the Malaysian setting fornot only the relationship can be quite formal, there is also the tendency for therelationship to develop into a long and loyal relationship such as thoserelationships between a guru or master and the disciples that were commonlyfound in traditional educational settings.

(5) Individualism vs collectivism: this dichotomy is usually found in how theacademics carry out their work and how their work is being assessed. In theWestern context the scholarship of the individual is of paramount importance asreflected by the research and publications of that particular academic. More oftenthan not, the performance of the academics are reviewed and assessed by theirpeers in their respective discipline. However, in the Malaysian context, the Asianvalue of collectivism is reflected in some of the common practices among theacademicians. The number of co-authorships is much higher among Malaysianacademics than their Western counterparts. Very often, the number of co-authorsin a particular publication can be more than two. Furthermore, the assessment andevaluation of academic performances is sometimes carried out by bureaucratsrather than academics.

(6) Merit-based structures vs relational (network-friendship) structures: anotherdichotomy is found in the ways of how people are recruited and promoted.The Western approach is to use merit-based criteria in such areas such ashiring, promotion, retention, student recruitment and so on. This applies to peoplesuch as students, faculty members as well as university leaderships. However, inthe Asian context, much has been written about the importance of personalrelations (what Chinese call guanxi or relationship) in getting access toopportunities and resources. In the Malaysian campus life, ethnic origins,personal relations and sometimes political affiliation play a very important part onwho gets appointed or promoted. While merit-based structures allow for increasedacademic freedom, freedom of inquiry, competition, mobility and collaboration,relational and network-based traditions can enhance job opportunities, promotionprospects, research access, leadership position, and many aspects of university life(Hawkins, 2013).

(7) Freedom of Expression vs politically constrained expression: a central feature of theWestern academic model is the notion of academic freedom in both teaching andresearch. While freedom in research is fundamental to the advancement of truth,freedom in teaching is fundamental to the protection of the rights of the teacher inteaching and of the students to freedom in learning. However, in the Asian contextincluding the Malaysian context, the academic freedom of academics is very oftencurbed by political interference in university affairs (Hawkins, 2013).

Conclusion and way forwardWhat have presented in the above sections is the conceptual framework for the researchproject on “Hybridity in Malaysian Universities” including a list of possible hybridities thatmay be found in various types of Malaysian universities. Anecdotal evidence across thethree types of universities outlined in the conceptual framework underlined the possiblehybridities that were the result of interaction with contemporary external influence and

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local traditional and culture in Malaysia. Further work on the research project would involvecollecting empirical data to test the posited hypotheses. It is proposed that these data wouldbe collected from a sample of nine universities consisting of three mainstream universities,three Islamic universities and three Chinese universities. Data will be collected using avariety of methods including:

• official documents analysis (including websites);

• in-depth interviews of informants from high level management, mid-levelmanagement, academics and students in selected universities;

• in-depth interviews of MoE officials; and

• expert workshops with stakeholders and resource persons.

The data collection will focus on hybrid formation in various aspects of university life suchas governance and management, programs and curriculum, teaching and learning as well asresearch and service.

The data collected will be analyzed based on a common research framework developedand shared by the cross-country comparative study research team. The research findingsfrom various case-studies will be further analyzed so as to theorize how and whyhybridization occurs in Asian universities.

AcknowledgmentThis paper is based on a larger research project entitled “East-West-Islamic Tradition andthe Development of Hybrid Universities in Malaysia” led by Morshidi Sirat and Chang DaWan, with co-researchers Molly Lee, Hazri Jamil, Munir Shuib, Guat Guan Toh and NurRafidah Asyikin Idris. The funding of the project is from Universiti Sains Malaysia underResearch University Grant: 1001/CIPPTN/816264.

Notes

1. These universities included Universiti Sains Malaysia (USM), Universiti Kebangsaan Malaysia(UKM), Universiti Pertanian Malaysia (UPM), Universiti Teknologi Malaysia (UTM), InternationalIslamic Universities Malaysia (IIUM), Universiti Utara Malaysia (UUM), and others.

2. These eight governments are Malaysia, Bangladesh, Egypt, Libya, Maldives, Pakistan, SaudiArabia and Turkey.

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Corresponding authorMolly Lee can be contacted at: [email protected]


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Development of thecollege-attendance value scale forsecond-year students in Taiwan

Ming-chia LinResearch Center for Curriculum and Instruction,

National Academy for Educational Research, New Taipei City, Taiwan, andEric S. Lin

Department of Economics, National Tsing Hua University, Hsinchu, Taiwan

AbstractPurpose – The purpose of this paper is twofold: to develop the college-attendance value scale (CAVS) in theTaiwan context to understand undergraduates’ reasons for or benefits from college education, and to examinehow the value relates to additional motivational goals, academic performance, and expected terminal degree.Design/methodology/approach – Data analyses involved sophomores (n¼ 729) who completed alearning-experience survey that included CAVS of the personal value and collective value subscales, expectedterminal degree, Achievement Goal Questionnaire, and cumulative grade point average (CGPA). Constructvalidity evidence was substantiated by the results of exploratory factor analysis (n¼ 364) for two-factoridentification, and by the results of confirmatory factor analysis (n¼ 365) for a good model-fit.Findings – The interrelations between variables in regression analysis supported the predictive validity;achievement goals were predictors of CGPA, while personal value was a sole predictor of expected terminaldegree. Findings suggest that CAVS is a predictive measure for Taiwanese undergraduates’ academicperformance and choices.Practical implications – In terms of policy implications, college students’ values of college attendance shouldnot only be regularly investigated by institutional research, but should be widely applied by university students,educators and administrators to facilitate the optimal learning development for each undergraduate.Originality/value – The study develops a short but effective scale of college-attendance value for theTaiwanese students who usually attend college after graduating from high school. The CAVS is useful inmanifesting the students’ major reasons for pursuing college education.Keywords Achievement, Personal value, College-attendance value scale (CAVS), Collective value,Expected terminal degreePaper type Research paper

1. IntroductionCollege students’ learning experience has been increasingly considered a key part ofinstitutional research (IR) which is mainly focused on evaluating institutional effectiveness interms of learning success (Hossler et al., 2001; Kelly et al., 2016; Kuh et al., 2006; Volkwein, 2011;Wu, 2016). In an attempt to better reflect institutional effectiveness, IR may address multiplevariables such as learning values, engagement, outcomes, student’s characteristics, campusenvironment, teacher-student interaction, and more (Hossler et al., 2001; Kelly et al., 2016;Kuh et al., 2006; Volkwein, 2011; Wu, 2016). While these variables appear to be broad-gauged,student learning experience is arguably the core of college education, and thus always plays a


Received 15 March 2017Revised 9 May 2017Accepted 24 May 2017


© Ming-chia Lin and Eric S. Lin. Published in the Higher Education Evaluation and Development.Published by Emerald Publishing Limited. This article is published under the Creative CommonsAttribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivativeworks of this article (for both commercial and non-commercial purposes), subject to full attribution tothe original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

This research was supported by Ministry of Science and Technology in Taiwan under Grant MOST105-2410-H-656-009.

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critical role in charting the path to learning success (Kuh et al., 2006; Whitt et al., 2008).The learning experience is usually measured by a variety of variables, such as academic valuesor expectations, readiness for college education, learning attitudes, engagement, achievements,and completion of college study. Thus, these factors make it possible to unveil the learningprocess and outcomes occurring in varying structured or unstructured curricula, real-life tasks,and social events that college students attend (Hossler et al., 2001; Kuh, 2005; Kuh et al., 2006;Lin et al., 2014). With these learning-experience indicators, IR is more likely to reveal thecommon learning experience for the majority of college students, and to signal directions ofinstitutional improvement. Among these indicators, the value and goal variables (e.g. valuesof college education and goals of academic achievement) are found to be predictive of success incollege study (Chen and Lu, 2015; Kember et al., 2008).

In fact, value of education has been found to be relatively effective in terms ofelaborating on why one emanates motivation to attend schooling, to attain achievement,and to express expectations of engaging in further education (Betz, 1993; Battle andWigfield, 2003; Eccles et al., 1983; Eccles, 1987, 2009; Jones et al., 2010; Kember et al., 2008).There are two values, collective value (e.g. peer influence, career concern) and personalvalue (e.g. knowledge development, self-exploration), that are critical for success inschooling (Battle and Wigfield, 2003; Eccles, 2009; Liem et al., 2012). These two valuesserve as active antecedents for academic achievements and related choices regardingfurther education (Battle and Wigfield, 2003; Eccles, 2009).

Despite this great functionality, these two values have yet to be adequately applied toundergraduates’ evaluation of their college attendance. It is not uncommon for undergraduatesto experience fluctuations in their college-attendance value throughout their college studies(Kember et al., 2008). Applying these two values of college attendance may yield interestinginsights into how value fluctuations relate to undergraduates’ striving for higher achievement,and their arrival at the choice of graduate studies or a job. In this sense, it is of great necessityfor college administrators to learn about the values undergraduates hold (e.g. the college-attendance values of why they attend college), and then to tailor college-learning experiences tothe needs of undergraduates, which may constitute evidence for the relative institutionaleffectiveness in terms of the students’ success (Kelly et al., 2016). This study aims to examineundergraduates’ reasons for attending college by developing the college-attendance value scale(CAVS). In particular, the study addresses two research questions:

RQ1. Can the CAVS measures undergraduates’ personal and collective values ofattending college?

RQ2. Are the undergraduates’ college-attendance values related to their achievementgoals, academic performance, and expected terminal degree?

1.1 IR for higher quality higher educationIn higher education, there has been a growing volume of IR that is often designed toexamine the evidence for institutional effectiveness and related factors (Kelly et al., 2016;Volkwein, 2011; Wu, 2016). IR can be briefly defined as a series of actions that will hopefullylead to evidence-based decisions on enhancing the learning experience and institutionaleffectiveness (Kelly et al., 2016; Volkwein, 2011; Wu, 2016). For instance, IR may includesystemic data collection and analysis of learning input, experience, outcomes, datainterpretation, and policy making, which may help university administrators makeinformed decisions as well as launch major initiatives for institutional improvement(Kelly et al., 2016; Volkwein, 2011; Wu, 2016). To make the institutional improvement morerelevant to student learning experiences, IR should comprise a wider range of data, such asstudents’ grade point average, and survey results on learning attitudes, values, andsatisfaction. By exploiting the potential of these measures, IR should examine learning

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Developmentof the CAVS

values as well as achievements to reveal the relative institutional effectiveness of promotingthe optimal learning of each college student, since learning values (sometimesoperationalized as motives or motivational beliefs) have been recognized as a keyantecedent for the desired learning process and outcomes of students at all levels in botheastern (Kember et al., 2008; Liem et al., 2012) and western (Battle and Wigfield, 2003;Eccles, 1987, 2009; Eccles et al., 1983) societies.

However, Kelly et al. (2016) point out that Asian cultures and practices often leave the surveyresults (e.g. surveys on students’ attitudes, values, or perceived competence) unresponsive tostudents’ needs or less transparent to the public, which may hinder the potential collaborationbetween industry, university, and other education stakeholders. To address this less transparentdisadvantage, university administrators should better disseminate the information gained fromIR, such as students’ demographics, values of college education, and learning process andproducts (Kelly et al., 2016). Among these variables, college-attendance value, denoting thereasons for and benefits of receiving a college education, as a key predictor of learning andachievement, may be a good start for the IR implications.

1.2 The conceptual framework of college-attendance value1.2.1 Value of higher education. Value of higher education is worth considering because itserves as a key antecedent for completing undergraduate or graduate degrees that often allowsfor the pursuit of a professional career (Betz, 1993) or the accumulation of human capital(Schultz, 1982). A number of studies have addressed this issue using the framework of theexpectancy-value theory, and found that value beliefs are predictive of intention or choice totake higher education courses (Battle and Wigfield, 2003; Eccles et al., 1983; Eccles, 1987;Jones et al., 2010). Particularly focusing on graduate education, Battle and Wigfield (2003)targeted college women in the USA, and developed the valuing of education scale (VOE) whichsubsumes four values of graduate education, including intrinsic value of interest, attainmentvalue of self-achievement, utility value of job and practical concerns, and cost of time and effort.VOE was found to be predictive of intention to engage in graduate education, with twoprominent predictors, intrinsic-attainment value out of personal criteria, and utility value out ofsocial or practical criteria (Battle and Wigfield, 2003).

While intrinsic-attainment value and utility value of graduate-program attendance have beenfound to be predictive of intention to engage in graduate education (Battle and Wigfield, 2003),social value remains less addressed (e.g. the value mainly shaped by family and peer influence).Social influence often plays a key role in affecting one’s education-related choices from theperspective of the expectancy-value theory (Battle and Wigfield, 2003; Eccles et al., 1983; Eccles,1987). This study attempts to fill in this gap by addressing the social influence denoting how keysocializers (e.g. parents, teachers, and peers) affect the individual’s perceived importance of atask (Bernardo, 2008; Eccles, 2009). Particularly in eastern societies, social influence has beenrecognized as a key factor in determining one’s schooling pursuit and academic performance,which often constitutes social motive or value for learning (Bernardo, 2008; Chen and Lu, 2015;Liem et al., 2012). Thus, this study addresses both the intrinsic-attainment value and social valuewhen conceptualizing undergraduates’ college-attendance value in Taiwan.

1.2.2 Collective value and personal value in relation to achievement goals. The expectancy-value theory has long been recognized as quite effective in terms of predicting individuals’achievement and future choices in education research (Battle and Wigfield, 2003;Eccles et al., 1983; Eccles, 1987). Recently, Eccles (2009) proposed integrating her expectancy-value theory with the identity-development theory (Oyserman et al., 2002). Eccles (2009)specifies two identities. Personal identity reflects an identity making individuals unique, whilecollective identity reflects a social role of the intended pursuit (e.g. gender role).In particular, collective identity may drive one to learn or develop over time in pursuit of

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meeting social expectations or norms of one’s development. These two identities are highlyinteractive but not identical with each other, making them distinguishable (Eccles, 2009).

These two identities are dynamically fluid in terms of content, salience, and relevance acrosscontexts, through subjective interpretations, and over time (Eccles, 2009). Contents refer to one’sachievement-related tasks or choices, while salience and relevance refer to the perceivedimportance of tasks and choices in the development of intended identities. Moreover, contents,salience, and relevance of the collective and personal identities are subject to three elements.The first is the social and psychological experiences that individuals accumulate in opting forvarying tasks. Notably, these choice experiences exert reciprocal influences among each otherover time (Eccles, 2009). For example, one’s choices today will become one’s past experiences ofchoices tomorrow. These past experiences often affect future choices. The second element is theindividual’s agency in interpreting those experiences to enact or threaten specific personal orcollective identities. Individuals usually interpret the importance of these experiencesaccording to the extent to which they foster development of their intended identities. Third,the co-construction of the identities involves not only individuals, but also the key socializers(e.g. family and peers) with whom individuals interact across contexts (Eccles, 2009). Interactingwith key socializers, individuals tend to gradually internalize particular social norms, such associal-role systems, conventional activities, and ideal characteristics into their value systems.In summary, collective and personal identities are dynamically constructed over time, throughsubjective interpretation, and across contexts. This dynamic nature of identity-basedmotivation was adopted by the study.

These values are largely observable by achievement-related beliefs, such as achievementgoals, expectancy and value of achievement-related choices (Eccles et al., 1983; Eccles, 1987).In academic settings, Eccles (2009) elaborated that achievement goals and expectancy forachievement are more related to achievements, while task values are more related tointention or choices regarding one’s job or further education. The study targeted task valuefor graduate choices.

Instead of using Eccles’ (2009) terms of collective and personal identities, the presentstudy specified the terms as collective value and personal value for a direct denotation ofcollege-attendance value. This value reflects undergraduates’ continuing interpretation ofhow relevant prior choice of college attendance is to their short-term or long-term goals.Usually, this interpretation is highly susceptible to ongoing college studies that constantlyoffer social or psychological experiences to shape the value (Kember et al., 2008). AdoptingEccles’ (2009) logic, this value hypothetically affects undergraduates’ future choice, such asintention to continue with graduate education or to get a job.

Similar to Eccles’ expectancy-value theory, the achievement motive theory also stressesthe importance of one’s collective and personal values to one’s academic achievement, andproposes two major motives, the social-oriented motive (e.g. parents’ or teachers’expectations) and the individual-oriented motive (e.g. personal expectations) (Diseth andKobbeltvedt, 2010; Liem et al., 2012). In fact, studies on the achievement motive theoryspecified that motive functions as an indirect antecedent of academic achievement, usuallythrough a powerful mediator, achievement goals (i.e. performance-approach/-avoidancegoals) (Bernardo, 2008; Diseth and Kobbeltvedt, 2010; Liem et al., 2012). Furthermore,social-oriented motive has been found to be more related to performance-approach andperformance-avoidance goals, while individual-oriented motive has been found to be morerelated to mastery-approach and performance-approach goals (Liem et al., 2012). Followingthis logic, the study hypothesized that the college-attendance value is positively related toachievement goals, and that performance-approach goals are predictive of academicachievement. University administration should first learn students’ college-attendance valuewhich is highly related to the subsequent learning process and outcomes, and then monitor

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and evaluate the learning process and outcome, which greatly signals directions for thecurriculum and instruction innovation university wide.

To recapitulate, this study sought to investigate undergraduates’ reasons for or values ofattending college, mainly using the two subscales, the collective value (e.g. of peer’s orparent’s influence and job-seeking term), and personal value (e.g. of knowledge explorationand development of in-depth thinking). Moreover, these two values were hypothesized as anantecedent for academic achievement and expected terminal graduate degree, under theframework of Eccles’ (2009) recent expectancy-value theory.

1.3 Purpose of the studyThe aim of the study was twofold: to develop the CAVS in the Taiwan context for anunderstanding of undergraduates’ reasons for or benefits of college education; to examinethe degree to which college students’ college-attendance values relate to their additionalmotivational goals, academic performance, and expected terminal degree. This developmentinvolved a procedure including analyses of construct validity within CAVS (convergent anddiscriminant validity), and predictive validity of CAVS (regressing CAVS on academicachievement and expected terminal degree).

2. Method2.1 Context of the studyThe participants in the study were 731 sophomores from a national university that wasranked in the top three in Taiwan for educating intellectuals and publishing research in theSTEM fields of science, technology, engineering, and mathematics. In order to understandundergraduates’ learning experiences and find directions for institutional improvement,a school-wide survey was conducted.

The survey targeted sophomores for three reasons. First, sophomores are at a transitionalstage of advancing from freshmen to juniors, which means their learning engagement andachievement may undergo changes, such as having better or worse learning experiences intheir second year of study (Loughlin et al., 2013; Maunder et al., 2012; Tobolowsky, 2008).These changes are arguably important to the ongoing development of most undergraduates.The change in a better direction often enables undergraduates to have more desired learningoutcomes throughout their college studies (including holding more personal values or intrinsicmotivation to learn), and to make more appropriate choices in their second year of study orafter graduation (Loughlin et al., 2013; Tobolowsky, 2008). Thus, there is a growing need toinvestigate the sophomores’ learning experiences (e.g. learning values and beliefs,engagement, and achievement) (Maunder et al., 2012; Tobolowsky, 2008). Second,sophomores are more familiar with their college life; they may make more reflectiveappraisals of the college environment and the effectiveness of the institution, according totheir college studies, as compared to freshmen. Such familiarity would make this investigationmore likely to reflect the extent to which the university is effective in providing good learningexperiences and a suitable environment for fostering undergraduates’ learning and promotingundergraduates’ positive values for college attendance (Loughlin et al., 2013). Third, there is aTaiwan Higher Education database (Chen, 2007) which mainly focuses on the college-learningexperiences of freshmen and juniors in Taiwan. Yet, the learning experience of sophomoresremains less addressed in the higher education field (Maunder et al., 2012; Tobolowsky, 2008),as well as in the institutional practices in Taiwan (Chen, 2007).

With a focus on sophomores, this study addressed college-attendance value that mainlyconstitutes reasons for college attendance, and the interrelations between collegeattendance, achievement goals (Elliot and McGregor, 2001), academic performance, andexpected terminal degree (i.e. master’s or doctoral degree).

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2.2 Sample of the studyIn this survey, all sophomores (n¼ 1,541; 66.06 percent male (n¼ 1,018), 33.94 percent female(n¼ 523)) were invited to participate. The returned 731 questionnaires were processed to screenout the incomplete questionnaires. Thus, two questionnaires were excluded from the analyses,giving a final sample of 729 (response rate: 47.31 percent of 1,541). The participants’ average agewas 20.44 years (SD¼ 0.72). A total of 39.72 percent of the participants were female (n¼ 287),and 60.6 percent were male (n¼ 442). The participants came from seven colleges of theuniversity as follows: 12.9 percent from the science college, 22.4 percent from engineering,19.8 percent from electrical engineering and computer science, 12.4 percent from humanities andsocial sciences, 7.5 percent from life science, 10.4 percent from nuclear science, and 14.5 percentfrom technology management. Although a common estimate of sampling data is to includesampling weight by the variables of interest (e.g. gender and field), sampling weight ofteninvolves great complexity, such as weight variables being arbitrary in nature (Winship andRadbill, 1994). Thus, we did not include sampling weight in the subsequent analysis; however,this limits the possible generalizations of the study findings to the wider context.

In the year of the study, the undergraduate population was 6,189 students of whom65.6 percent were male students, and 34.4 percent female. The population undergraduates camefrom seven colleges: 14.9 percent from the science college, 24.3 percent from engineering,18.0 percent from electrical engineering and computer science, 11.9 percent from humanities andsocial sciences, 5.9 percent from life science, 10.8 percent from nuclear science, and 13.8 percentfrom technology management. Thus, the results of the demographic data (i.e. gender andcollege) suggest that the ratios of the sampled participants closely corresponded to those of theentire undergraduate population, making the study results relatively representative.

2.3 MeasuresBelow are the details of the measures of the CAVS, Achievement Goal Questionnaire (AGQ),cumulative grade point average (CGPA), and expected terminal degree.

2.3.1 CAVS. Designing CAVS involved four phases: adopting theories, collecting itemsfrom the database, consulting experts, and piloting on students.

2.3.2 Construction of CAVS. CAVS subsumed two constructs, personal value andcollective value. Personal value denotes individualized interests, needs, reasons, or benefitsof learning that help individuals perceive the importance of learning to personaldevelopment or goal pursuit in a long term. Collective value denotes social interests, needs,reasons, or benefits of individuals’ learning that help them perceive the importance oflearning for conformity to social norms or expectations. The construction of CAVS adoptedthe framework of the expectancy-value theory, with a focus on collective value and personalvalue (Eccles, 2009). Using this framework, potential items were drafted. Since these itemswere written in the participants’ native language (Chinese), no translation was needed. Then,the CAVS draft was given to three experts who were researchers in educationalmeasurement, educational psychology, and psychology. These experts commented on therelevance of the items to undergraduates’ value of college attendance, and possible problemswith item wording and interpretation. Lastly, the CAVS draft was administered to a focusgroup of three students from the targeted population. The focus group commented on theextent to which the items adequately reflected their college-attendance value, and whetherthey interpreted the items in a manner corresponding to that of the item development. Withthese comments, possible problems in wording and interpretation were resolved, whichprovided preliminary content validity evidence for the eight items of CAVS.

2.3.3 Two subscales of CAVS. The two subscales are collective value and personal value.Collective value (five items) referred to the college-attendance reasons stemming from socialcriteria (e.g. peer influence, job-seeking term). Personal value (three items) referred to the

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college-attendance reasons stemming from individual criteria (e.g. development of in-depththinking, knowledge exploration).

These eight items were assessed by a four-point Likert-type response ranging from point4 (strongly agree) to point 1 (strongly disagree). Moreover, these items were asked using theitem-stem: what are your reasons for attending college? All the items in the two subscaleswere totaled. A high score corresponds to a high degree of endorsement of CAVS.

2.3.4 Expected terminal degree. Participants’ expected degree was probed with responseof bachelor, master’s, and doctoral degrees. The participants should check one of theresponses. For coding of the responses, the bachelor response was categorized as 0 and themaster’s and doctoral degrees as 1, which distinguished the expectation of engaging ingraduate education from no expectation.

2.3.5 AGQ. The AGQ manifesting a 2 by 2 framework of achievement goals wasadopted (Elliot and McGregor, 2001). This framework subsumed four subconstructs,namely, mastery approach, mastery avoidance, performance approach, and performanceavoidance; each subconstruct was measured by three items, totaling 12 items. These itemsof achievement goals were assessed by a four-point Likert-type response. Similar to CAVS,the responses ranged from point 4 (strongly agree) to point 1 (strongly disagree).For scoring, all the items in the four subscales were totaled. A high score corresponds to ahigh degree of endorsement of the achievement goals. The internal consistency of this scalewas supported by previous studies (mastery-approach goals, mastery-avoidance goals,performance-approach goals, and performance-avoidance goals, with Cronbach’s αs of 0.84,0.88, 0.92, and 0.94, respectively) (Elliot and Murayama, 2008).

2.3.6 CGPA. Permission was obtained from the university for a match between the valuescores and the participants’ CGPA for four semesters (720 participants due to some missingcases), which enabled a subsequent analysis of CGPA, and the CAVS and AGQ scores.

2.4 ProcedureThe eight-item college-attendance motive scale was administered in a university-wide onlinesurvey. The survey was a built-in feature in the university academic information system,which encouraged all the sophomores in the university to participate. The participants filledin the demographic and questionnaire items after reading a letter explaining the surveypurposes. After completing the survey, the participants were eligible for an incentive rafflethat gave a few prizes of popular electronic devices, including an iPad, a transformer, aniPod, and USB flash drives.

2.4.1 Analytical procedure. Data analysis included descriptive statistics, reliability analyses,correlation analysis, and exploratory factor analysis (EFA) using SPSS Version 20, whileconfirmatory factor analysis (CFA) was performed using LISREL 8.8 ( Joreskog and Sorbom,1996). CFA was tested by maximum likelihood estimation and evaluated by the fit indices ofχ2 (low values at a non-significant level), normed χ2 (ranging from 1 to 3), RMSEA (less than 0.08with confidence interval reported), CFI (equal to or larger than 0.95 on the 0-1 scale), NNFI (equalto or larger than 0.95 on the 0-1 scale) (Hair et al., 2010; Kline, 2011). Because these nested modelswere compared, the χ2 value was evaluated (Hair et al., 2010; Kline, 2011).

3. Results3.1 Descriptive statisticsItem analyses on the eight items were conducted using the descriptive statistics of mean,standard deviation, skewness, kurtosis, and reliability analysis (see Table I). The skewnessand kurtosis of the items in terms of the converted z-scores were all below ±1.96, andprovided little evidence of significant deviations from normal distribution, enabling use ofthe maximum likelihood estimation in the following CFA.

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For reliability analysis, correlated item-total correlation and Cronbach’s α if item deleted werecomputed. Overall, the eight items were calculated by their corresponding subscale, collectivevalue and personal value. Results showed that Item 0 (development of social networking) has aweaker function. That is, Item 0 had a lower value in the corrected item-total correlation (0.42;a suggested value is around 0.50, Hair et al., 2010) and a higher value of Cronbach’s α if itemdeleted (0.83) (suggested value is lower than the scale reliability, i.e. 0.82, Hair et al., 2010),indicating that the item was less consistent with the other items in the subscale.

For the factor analysis, the participants were randomly divided into Sample 1 (n¼ 364)and Sample 2 (n¼ 365). Sample 1 served as the calibration sample for the EFA by theextraction method of principal component analysis (PCA). Sample 2 served as the validationsample for the CFA.

3.2 EFA resultsFirst, using the calibration sample (n¼ 364), CAVS with a two-factor model was examinedby PCA with a promax rotation. The Kaiser-Meyer-Olkin statistic of 0.77 revealed that thesample size was adequate for the procedure. Factor extraction was determined byeigenvalues greater than 1 and the leveling-off point on the scree plot. The results showed atwo-factor solution, accounting for 66.68 percent of the total variance (eigenvalues of 3.38and 1.95, respectively).

In evaluating factor loadings, a cutoff of 0.45 was adopted to reveal a significantassociation between the item and its corresponding factor. Table II shows that the factorloadings of most items ranged from 0.73 to 0.93. However, Item 0 double-loaded on bothfactors (0.35 and 0.43 on collective value and personal value, respectively), once againrevealing that Item 0 appeared less effective in reflecting a single construct. Also, eachloading of Item 0 was lower than 0.45, failing to explain at least 20 percent of the sharedvariance between the item and the factor. Notably, Item 0 showed poorer performance in thereliability analysis as well. Item 0 was then deleted in subsequent analysis to ensure that allitems in CAVS effectively reflected the designated single factor.

After the deletion, EFA was recomputed on the remaining seven items. The Kaiser-Meyer-Olkin statistic was 0.74, indicating that the sample size was adequate, and the total varianceexplained was 71.91 percent of the total variance (eigenvalues of 3.08 and 1.95, respectively).

Mean SD Skewness KurtosisCorrected item-total

correlationCronbach’s α ifitem deleted

Item 1. Family expectation 3.11 0.72 −0.73 0.90 0.61 0.78Item 2. Peer influence 2.99 0.77 −0.61 0.31 0.69 0.75Item 3. Social trend 3.25 0.76 −0.98 0.97 0.72 0.75Item 4. Job-seeking term 3.31 0.72 −1.01 1.17 0.61 0.78Item 0. Expansion of socialnetworking 2.96 0.76 −0.45 0.01 0.42 0.83

Collective valueCronbach’s α¼ 0.82Item 5. Knowledge exploration 3.25 0.66 −0.81 1.50 0.76 0.84Item 6. Development ofin-depth thinking 3.22 0.67 −0.59 0.57 0.82 0.79Item 7. Self-exploration andself-actualization 3.28 0.68 −0.81 1.07 0.73 0.87

Personal valueCronbach’s α¼ 0.88Notes: n¼ 729. SD, standard deviation

Table I.Descriptive statistics

of CAVS

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The factor loading ranged from 0.73 to 0.92 (see Table II). Since these seven items all loaded onthe designated factors, the naming of these two factors follows our hypothetical framework.Items 1-4 were named “collective value,” while Items 5-7 were named “personal value.”

3.3 CFA resultsSecond, the seven items in the second EFA were further validated by a CFA on thevalidation sample (n¼ 365). The hypothetical CFA model subsumed two factors, collectivevalue and personal value.

3.3.1 Model testing. Table III shows the fit indices of the three competing models testedin the two phases. First, the proposed two-factor model (Model 2) was tested against the one-factor model (Model 1) serving as a null hypothesis. Model 1 had a rather poor fit( χ2¼ 623.60 (14), po0.05, normed χ2¼ 44.54, RMSEA¼ 0.35, CFI¼ 0.53, and NNFI¼ 0.30),justifying the rejection of the one-factor model. This rejection provides discriminant validityevidence of the two-factor model. Likewise, Model 2 was tested. From Model 1 to Model 2,there was a decrease of 535.95 at an expense of one degree of freedom, indicating asignificant improvement in the χ2 value (a drop of less than 5.00 is considered as showinglittle improvement in fit) (Byrne, 1989; Gagne et al., 1995). However, as shown in the fitindices, Model 2 did not adequately explain the data. Model modification was conducted bymodification indices from the LISREL program.

Second, Model 2 was tested against Model 3, which further specified the two-factor modelby an error covariance. Model 3 showed a good fit ( χ2¼ 23.37 (12), po0.05, normed χ2¼ 1.95,RMSEA¼ 0.05, CFI¼ 0.99, and NNFI¼ 0.98). From Model 2 to Model 3, there was a decreaseof 64.28 at an expense of one degree of freedom, indicating another significant improvement infit (Byrne, 1989; Gagne et al., 1995). Model 3 was therefore accepted as the final model.

1st EFA 2nd EFAItem/Factor 1 2 1 2

2. Family influence 0.85 −0.03 0.85 −0.023. Social trend 0.84 0.00 0.85 0.021. Family expectation 0.80 −0.12 0.80 −0.114. Job-seeking term 0.73 0.12 0.73 0.126. Development of in-depth thinking −0.05 0.93 −0.02 0.925. Knowledge exploration −0.02 0.88 0.02 0.897. Self-exploration and self-actualization −0.03 0.87 0.00 0.870. Expansion of social networking 0.35 0.43Note: EFA, exploratory factor analysis

Table II.Results of exploratoryfactor analysis(rotated matrix)

Model χ2 (df) Normed χ2 Δχ2 (df) RMSEA CFI NNFI

Model 1 623.60 (14) 44.54 0.35 (0.33-0.37) 0.53 0.301-factor (null)Model 2 87.65 (13) 6.74 535.95 (1)* 0.13 (0.11-0.15) 0.94 0.912-factor po0.05Model 3 23.37 (12) 1.95 64.28 (1)* 0.05 (0.016-0.081) 0.99 0.982-factor with 1 error cov. po0.05Suggested value Smaller, the better o3.00 o0.08 W0.95 W0.95Notes: n¼ 365. χ2, χ2 indices; Δχ2(df), Δχ2 indices; error cov., error covariance. Model 3 had a better fit withthe data, as shown by the indices of RMSEA, CFI, and NNFI

Table III.Model-fit indices

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Notably, in Model 3, an additional parameter of error covariance was estimated between Items3 and 4 in the collective value subscale, which may be justified. This parameter often reflectsnon-random measurement error that is attributable to method effect on item measures of thesame subscale (Byrne, 1989; Gagne et al., 1995), accounting for minor covariance not capturedby the hypothesized model. Model 3 with an error covariance appeared justifiable.

3.3.2 Construct validity evidence. Construct validity evidence is of great importance toensure that a set of indicators adequately reflects the theoretical latent constructs that theindicators were designed to measure (Hair et al., 2010; Kline, 2011). Specifically in CFA,Kline (2011) stated that construct validity is often evaluated by convergent validity anddiscriminant validity which evaluate measures against each other, rather than against anexternal criterion. Here, convergent validity evidence was collected from the factor loading,composite reliability, and average variance extracted (AVE) estimate (Hair et al., 2010;Kline, 2011). Discriminant validity evidence was collected by comparing AVE estimateswith the square of the correlation between the latent constructs (Farrell, 2010).

3.3.3 Convergent validity. Table IV presents convergent validity evidence of Model 3,including standardized factor loadings, composite reliability, and AVE. First, except for Item 4(0.52), all other items had a loading higher than the 0.60 cutoff (Hair et al., 2010). All residualsranged from 0.17 to 0.73. Second, composite reliability values were 0.80 and 0.88 higher thanthe 0.70 cutoff, while the AVE estimates were 0.51 and 0.71 higher than the 0.50 cutoff(Hair et al., 2010). These statistics provide convergent validity evidence for CAVS.

3.3.4 Discriminant validity. Discriminant validity evidence was examined by comparingAVE estimates with the square of the correlation between the theoretical latent constructs(Farrell, 2010). In Table IV, below the diagonal was the correlation of the two constructs (0.22)(ϕ estimate in the LISREL output), while above the diagonal was the square of the correlation.As can be seen, the square of the correlation (0.05) is much lower than the two AVEs (0.51 and0.71, respectively), providing discriminant validity evidence for CAVS (Farrell, 2010).

3.4 Predictive validity evidenceTo evaluate the predictive validity evidence of CAVS, a few analyses of Pearsonproduct-moment correlation, multiple regression, and logistic regression were performed.

CFASubscale/Item Factor loading Residual

Convergent validity evidenceCollective valueItem 1. Family expectation 0.72* 0.49*Item 2. Peer influence 0.90* 0.19*Item 3. Social trend 0.67* 0.55*Item 4. Job-seeking term 0.52* 0.73*Composite reliability 0.80

Personal valueItem 5. Knowledge exploration 0.83* 0.31*Item 6. Development of in-depth thinking 0.91* 0.17*Item 7. Self-exploration and self-actualization 0.78* 0.40*Composite reliability 0.88

Discriminant validity evidenceCollective value 0.51 0.05Personal value 0.22 0.71Notes: n¼ 365. CFA, confirmatory factor analysis. *po0.05

Table IV.Evidence of

convergent validityand discriminant

validity

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First, Table V shows the correlation analysis results. Overall, CAVS showed a mediumcorrelation with AGQ (r¼ 0.39), a small correlation with CGPA (r¼ 0.10), and a smallcorrelation with expected degree (r¼ 0.17) (Cohen, 1988). As expected, if undergraduateshighly endorsed college-attendance value, they tended to highly endorse AGQ, tooutperform academically, and to expect to continue with a graduate degree.

On the subscale, collective value had small correlations with AGQ (r ranging from0.14 to 0.29) but neither with CGPA nor expected degree, while personal valuecorrelated with all of the measures (r ranging from 0.08 to 0.47). First with higherendorsement of collective value, the participants tended to highly endorseachievement goals, particularly the performance-approach and performance-avoidancegoals (r¼ 0.22, 0.29), consistent with previous studies (Elliot and McGregor, 2001;Elliot and Murayama, 2008). However, they would not necessarily have higheracademic performance or greater expectations to take a graduate degree, consistentwith previous studies (Liem et al., 2012). Second with higher endorsement of personalvalue, the participants tended to highly endorse achievement goals, particularly themastery-approach and mastery-avoidance goals (r¼ 0.47, 0.44), consistent with previousstudies (Elliot and McGregor, 2001; Elliot and Murayama, 2008). Also consistently, theytended to outperform academically (Liem et al., 2012), and to hold higher expectations oftaking a graduate degree (Battle and Wigfield, 2003).

Second, a multiple regression analysis was performed, with CGPA as the criterion andCAVS and AGQ as predictors. The results in Table VI reveal two effective predictors ofCGPA: performance-approach goal ( β¼ 0.28, standard error (SE) of B¼ 0.49; t¼ 5.88,po0.000) and performance-avoidance goal ( β¼−0.13, SE of B¼ 0.45; t¼−2.91, po0.000).None of personal value, collective value, or the mastery-approach and mastery-avoidancegoals were predictive, consistent with previous studies (Bernardo, 2008; Liem et al., 2012).

Third, a logistic regression analysis was performed, with expected terminal degree as thecriterion, and CGPA, CAVS, and AGQ as predictors. The results in Table VII show that theexpected terminal degree can be predicted by personal value (B¼ 0.87, SE of B¼ 0.21,Wald χ2¼ 17.09, po0.000) but not the other variables, which is partly consistent withprevious studies (Battle and Wigfield, 2003; Eccles, 2009).

These findings of predictive validity and the cross-group analysis indicate three points.First, the CAVS can measure sophomores’ personal and collective values of attending college.Second, generally, the inter-correlations of the variables suggest that if undergraduates havehigher college-attendance value, they tend to also have higher achievement goals, to

CAVS CV PV AGQ MAp MAv PAp PAv CGPA ETD

CAVS 1CV 0.850** 1PV 0.705** 0.225** 1AGQ 0.390** 0.266** 0.362** 1MAp 0.354** 0.141** 0.465** 0.762** 1MAv 0.344** 0.149** 0.435** 0.796** 0.715** 1PAp 0.280** 0.224** 0.217** 0.831** 0.513** 0.477** 1PAv 0.256** 0.292** 0.079** 0.733** 0.248** 0.392** 0.548** 1CGPA 0.095* 0.040 0.123** 0.274** 0.266** 0.231** 0.295** 0.076* 1ETD 0.171** 0.055 0.242** 0.181** 0.195** 0.166** 0.144** 0.075* 0.096* 1Notes: n¼ 720. CAVS, college-attendance value scale; CV, collective value; PV, personal value; AGQ,Achievement Goal Questionnaire; MAp, mastery approach; MAv, mastery avoidance; PAp, performanceapproach; PAv, performance avoidance; CGPA, cumulative general point average; ETD, expected terminaldegree. *po0.05; **po0.001

Table V.Pearson correlationsamong CAVS,AGQ, academicperformance, andexpected terminaldegree

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outperform academically, and to expect a post-graduate-program terminal degree. Third, thetwo values were not predictive of academic achievement, but personal value was predictive ofexpected terminal degree.

4. ConclusionCollege-attendance values or expectations of undergraduates have gained increasing attentionfor stakeholders in higher education because they are more likely to drive the subsequentlearning engagement and outcomes, and aspirations for further studies of undergraduates(Battle andWigfield, 2003; Chen and Lu, 2015; Kuh et al., 2006; Whitt et al., 2008). In this study,we developed a CAVS. The results have two major implications. First, the two-factor model ofcollege-attendance value can manifest Taiwanese undergraduates’ reasons for or benefits ofpursuing college education, particularly by seven-item measures. This CAVS development isthus more likely to be replicated and contextualized to other universities that also stress theimportance of learning and utilizing college-attendance values for optimal learning. Second,the CAVS should be used for tracing the learning path along which individuals with highereducation values are motivated to aim for and then perhaps achieve the desired learningoutcomes. Such investigation would thus advance our understanding of undergraduates’more positive learning experiences, and perhaps they will be more willing to and capable ofachieving higher academic performances, and have greater expectations of pursuing graduatestudies. This understanding should be appropriately applied to evaluate the institutionaleffectiveness in terms of the learning success of each college student, and signaling thedirections of institutional improvement, particularly through the lenses of institutionalresearchers (Kelly et al., 2016; Kuh et al., 2006; Volkwein, 2011; Wu, 2016).

B SE(B) β t(B) p

CV −0.10 0.44 −0.01 −0.23 0.82PV −0.09 0.48 −0.01 −0.19 0.85MAp 1.26 0.67 0.10 1.88 0.06MAv 1.04 0.70 0.08 1.48 0.14PAp 2.86 0.49 0.28 5.88 0.00**PAv −1.31 0.45 −0.13 −2.91 0.00**Notes: n¼ 720, R2¼ 0.12. B, unstandardized coefficients, SE(B), standard error associated withunstandardized coefficients, β, beta; t(B), t-value; p, p-value; CV, collective value; PV, personal value; AGQ,Achievement Goal Questionnaire; MAp, mastery approach; MAv, mastery avoidance; PAp, performanceapproach; PAv, performance avoidance. **po0.001

Table VI.Results of a multipleregression analysis

on cumulative gradepoint average

B SE(B) p Odds ratio 95% CI Wald

CV −0.08 0.20 0.68 0.92 [0.63, 1.14] 0.17PV 0.87 0.21 0.00 2.39 [1.58, 3.60] 17.09MAp 0.34 0.30 0.26 1.41 [0.78, 2.55] 1.28MAv −0.12 0.32 0.71 0.89 [0.48, 1.66] 0.14PAp 0.23 0.23 0.31 1.26 [0.81, 1.98] 1.04PAv 0.05 0.22 0.81 1.05 [0.69, 1.60] 0.06CGPA 0.01 0.02 0.40 1.01 [0.98, 1.05] 0.70Notes: n¼ 720, Nagelkerke R2¼ 0.11. B, unstandardized coefficients, SE(B), standard error associated withunstandardized coefficients; p, p-value; CI, the confidence interval for odds ratio; Wald, the Wald χ2 value

Table VII.Results of a logisticregression analysis

on expected terminaldegree

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4.1 Construct validity of CAVSCAVS was supported by the preliminary validity evidence, suggesting that the latentconstruct of college-attendance value can be manifested and measured by two subscales:collective value and personal value. The validity evidence for CAVS supports thegeneralizability of the expectancy-value theory to an Asian country (Battle and Wigfield,2003; Eccles, 2009). CAVS serves as an effective measure for a contextualized capture ofTaiwanese undergraduates’ value of college attendance.

4.2 Predictive validity of CAVS4.2.1 Value as a non-predictor of CGPA. Performance-approach and performance-avoidancegoals are predictive of CGPA, while the two values and mastery-approach andmastery-avoidance goals were not predictive, consistent with previous studies(Bernardo, 2008; Eccles 1987, 2009; Elliot and Murayama, 2008). Task value(e.g. collective value and personal value) has been found to be less predictive ofachievement (Eccles, 1987, 2009; Jones et al., 2010). A possible explanation is that thetask-value effect on achievement is greatly mediated by achievement goals. For instance,such a mediated effect of task value can be seen in Liem et al.’s (2012) study whichdemonstrated a motivated model of secondary school students’ achievement in Singapore.

4.2.2 Value as a predictor of expected terminal degree. As expected, personal value ispredictive of expected terminal degree, while collective value is not. This findingcorresponds to Battle and Wigfield’s (2003) study which found intrinsic-attainment value(the strongest predictor) and utility value to be predictive of undergraduates’ intention togo to graduate school. Similarly, the study indicated that personal value is the solepredictor of expected terminal degree.

This difference in predictors may be partly attributed to what values are addressed.This study addressed undergraduates’ college-attendance values, while Battle andWigfield (2003) addressed undergraduates’ graduate-education values. This wordingnuance may contribute to the difference. Undergraduates’ values of graduate education referto their perceived reasons for receiving graduate education (Battle and Wigfield, 2003).This graduate-education value was found to be predictive of intention to pursue graduateeducation. In the study, undergraduate students’ college-attendance values refer to anongoing judgment of their prior choice of undergraduate education. Less surprisingly,collective value (e.g. job-seeking term) does not suffice in explaining our sophomoreparticipants’ expectations regarding a graduate degree. Interestingly, personal value relatesto the expected terminal degree, consistent with Battle and Wigfield’s (2003) finding thatpersonal value was the strongest predictor of intention to pursue graduate education.Apparently, personal value triumphs over collective value. Personal value not only justifiesour sophomores’ prior choices of college attendance, but largely initiates their expectationsof pursuing a graduate degree, even though gaining a graduate degree appears to be achoice to be made a few years ahead.

Of course, enrolling in graduate programs may not necessarily be the best choice for allundergraduates. However, graduate programs generally enable individuals to reach higherpotential in educational terms, to accumulate their human capital (Schultz, 1982), and tohave a more prosperous career (Betz, 1993; Battle and Wigfield, 2003). If stakeholders ofhigher education attempt to encourage more undergraduates to enroll in graduateprograms, promoting higher personal value seems a promising direction. Such valuepromotion may be launched by offering college students enjoyable learning experiences(Eccles, 2009; Kember et al., 2008).

This perspective is elaborated below (Kember et al., 2008). First, personal value ishighly interactive with collective value, according to Eccles’ (2009) theoretical proposal and

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Kember et al.’s (2008) qualitative findings on undergraduates in Hong Kong. For instance,individuals may enter college mainly with collective values (i.e. career) at the outset.Throughout their college studies, they may gradually develop their personal value of collegeattendance by acquiring disciplinary knowledge and enjoying knowledge acquisition in itsown right (Kember et al., 2008). This study found that development of personal value willcontribute to greater expectations of pursuing a graduate degree. Second, development ofpersonal value and collective value usually occurs over time, through subjectiveinterpretations, and within a certain context (Eccles, 2009). Specifically, personal value ofcollege attendance can be viewed as a function of curriculum choice, learning experiences,and college environment (Kember et al., 2008). In this sense, if individuals are satisfied withtheir curriculum choice and learning, and with the college environment, they tend to assignhigher personal value, which in turn contributes to greater expectations of pursuing agraduate degree. Thus, personal value, as an effective predictor of expected terminal degree,may serve as a key criterion for IR. IR often attempts to use evidence-based data to revealthe learning experiences of most college students, to predict the seniors’ choices aftergraduation (e.g. finding a job or entering graduate school), and then perhaps to signaldirections for innovation in the curriculum and instruction at the institution.

4.3 ImplicationsIn terms of its implication, CAVS may benefit undergraduates and university administratorand educators, particularly for personal value being adaptive for more academic-pursuitchoices (e.g. higher expected terminal degree). On one hand, undergraduates should learnthe importance and the current state of their personal value, and then actively enhance it.For instance, undergraduates should take a proactive role in relating their college educationto their intrinsic reasons and needs for continuing development, such as the need forintellectual development, the drive for personal actualization, or even perpetuating curiosityregarding the world (Kember et al., 2008; Loughlin et al., 2013).

On the other hand, university administrators and educators should examine and thenensure that the learning experience enables each student to increase their personal value ofattending college. For instance, the learning experience should empower college students toautonomously explore and reflect upon their personal needs and pursuits in their collegeeducation. Such personalized reflection has been found to be conducive to a boost inundergraduates’ personal value (Chen and Lu, 2015; Kember et al., 2008; Loughlin et al., 2013),since undergraduates are learning to actively make sense of college education, mainly byconnecting it to their personal needs, curiosity, or reasons to learn.

In terms of the policy implications, university administrators should recognize, measure,and apply the undergraduates’ college-attendance value in question for better institutionaleffectiveness at present or in the future. First of all, university administrators should makethe undergraduates’ college-attendance values important and salient to both collegestudents and educators institution wide, such as by administering the scale contextualizedto the undergraduates in question, and by circulating the scale responses institution wide.Notably, university administration should make possible tracking of undergraduates’values by continuing to administer value scales (e.g. collective value and personal value) anddisseminating the scale responses, so as to better capture fluctuations in these valuesthroughout the students’ college life, and to apply these fluctuations for improvement in thelearning experiences of most students (e.g. motivating strategies, goal-setting support forstimulating and maintaining higher values of college education, etc.).

Second, university administrators should encourage wider application of the valueresponses to improvement in learning experiences and innovation in curriculum andinstruction design. Taking the learning goals in college education for instance, undergraduates

51


should be aware of and then be able to relate college education to their individual goals orpursuits in life, while college educators should greatly accommodate undergraduates’ needs toachieve their individual goals in their college education.

Third, using the value responses for planning the future learning experience ofundergraduates, university administrators and educators should offer correspondingpreparation. For individuals holding higher collective value of college attendance andgreater intentions to get a job, university administrators should offer job preparation, such aspre-service training on professional and interpersonal skills. University administrators andeducators should try to equip individuals with sufficient skills for pursuing their intendedcareer (Lin et al., 2014). For individuals holding higher personal value and greater expectationsof graduate education, universities should offer graduate-education preparation, such asadvancing the disciplinary knowledge essential for graduate education, and sharpening skillsof conducting disciplinary research. These university preparations may be effective in aidingundergraduates to better achieve their varying goals in life. Once more undergraduatessuccessfully attain their goals, the preparations can be deemed supportive of the institutionaleffectiveness in terms of the learning success of college students in their college studies or overthe course of their lives, corresponding to the IR implications stated in previous studies(Kelly et al., 2016; Kuh et al., 2006; Volkwein, 2011; Wu, 2016).

In a nutshell, with a clearer understanding of undergraduates’ values of college attending,undergraduates themselves can better achieve their desired learning outcomes, collegeeducators can thus plan both formal and informal curricula to better facilitate students’learning development, and university administrators can improve the learning environment formore optimal development of each student (Kuh et al., 2008; Lin et al., 2014). In this sense,college-attendance value should be included as evidence of college students’ learningexperience that can indicate the learning effectiveness at present and the improvementdirections for the future, corresponding to the common implications of the IR (Hossler et al.,2001; Kelly et al., 2016; Kuh et al., 2006; Volkwein, 2011; Wu, 2016). Once universityadministrators can better estimate and then apply the students’ college-attendance value tointerpretations of learning outcomes, they are more likely to better facilitate the development ofeach student, which subsequently constitutes evidence for institutional effectiveness in termsof promoting the learning success of each college student (Kelly et al., 2016; Volkwein, 2011).

4.4 LimitationsTwo major study limitations warrant attention, namely, the sampling and the contextualizedcollege-attendance value. First, in this study, we computed and interpreted the sampled dataon the basis of a 47.31 percent response rate to the university-wide sophomore survey, ratherthan computing the data by sampling weight. While sampling weight is seen as a dependentvariable in regression model analysis, it often involves great complexity (Winship and Radbill,1994), such as how many variables should be included as the sampling weight, and the extentto which the weighted computations are similar to those of the entire population. This concernprevented us from computing by the sampling weight. Such a limitation in the sampling willthus require some caution in the generalization of the study findings.

Second, the college-attendance value is contextualized into a research-oriented universitythat is renowned for the STEM fields in Taiwan, and thus should not be over-generalizedworldwide. Future studies are highly encouraged to adopt this lens of contextualized value,and thus are more likely to be capable of effectively describing the learning paths of collegestudents (such as from the college-attendance value, via achievement goals, to academicperformance, in turn making choices for jobs or post-graduate programs after graduation).Also, when using the value to explain the learning path, it is critical to note the collectivisticculture or individualistic culture background (e.g. serving as antecedents of educationvalues) from which students come. Therefore, future studies on the contextualized

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college-attendance values, specifically against the culture backdrop, will shed new light onthe relative effectiveness of education value or additional motivational beliefs in terms ofchanneling students’ energy appropriately to the more desired learning paths, acrossdiverse universities worldwide.

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Corresponding authorEric S. Lin can be contacted at: [email protected]


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EDITORS-IN-CHIEFSAngela Yung-Chi Hou Higher Education Evaluation and Accreditation Council of Taiwan (HEEACT) & Asia-Pacific Quality Network (APQN),TaiwanJagannath PatilNational Assessment and Accreditation Council (NAAC) & Asia Pacific Quality Network (APQN), IndiaSheng-Ju ChanHigher Education Evaluation and Accreditation Council of Taiwan (HEEACT) and National Chung Cheng University, TaiwanHomepage: www.emeraldgrouppublishing.com/services/publishing/heed/index.htmEXECUTIVE EDITORHua-Chi ChouHigher Education Evaluation and Accreditation Council of Taiwan (HEEACT), TaiwanEDITORIAL ASSISTANTCindy ChenHigher Education Evaluation and Accreditation Council of Taiwan (HEEACT), Taiwan

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Higher Education Evaluation and Accreditation Council of Taiwan

Volume 11 Number 1 ISSN: 2514-5789

Volume 11 Number 1 2017

Higher Education Evaluation and Development

Higher Education Evaluationand Development

Access this journal online:www.emeraldinsight.com/journal/heed

Number 1 1 Editorial boards

2 Institutional research as a bridge: aligning institutional internal data needs and external information requirements from a strategic viewChester D. Haskell

12 A comparative study of student mobility programs in SEAMEO-RIHED, UMAP, and Campus Asia: regulation, challenges, and impacts on higher education regionalizationAngela Yung Chi Hou, Christopher Hill, Karen Hui-Jung Chen, Sandy Tsai and Vivian Chen

25 The development of Malaysian universities: exploring characteristics emerging from interaction between Western academic models and traditional and local culturesMolly Lee, Morshidi Sirat and Chang Da Wan

38 Development of the college-attendance value scale for second-year students in TaiwanMing-chia Lin and Eric S. Lin

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Higher Education Evaluation and Development