Decision Support Systems for University Management ... - IEEE Xplore

2009 Second International Conference on Computer and Electrical Engineering

Decision Support Systems for University Management Processes: An Approach towards Dynamic Simulation Model *Louna Al Hallak, *Algirdas Pakštas, **Peter Oriogun, *'XãLFD1RYDNRYLü *Faculty of Computing, London Metropolitan University 166-220 Holloway Road, London, N7 8DB, England {l.hallak, a.pakstas, d.novakovic}@londonmet.ac.uk **School of Information Technology and Communications, American University of Nigeria, Lamido Zubairu Way, Yola Township By-Pass, PMB 2250, Yola Adamawa State, Nigeria business universities are usually pretty complex organizations, often inheriting legacies from the predecessor institutions and developing layers of complexities by themselves. This complexity can no longer be solved using linear statistical models and forecasting such as regression analysis [3], effective and efficient management of university resources has been recognized as vital in terms of workflow management [4]. Consequently having accurate, relevant and timely information is a key problem that university management encounters in their attempt to make the kind of decisions that current administrative conditions demand. The focus of this paper is to introduce the initial stage of the first author’s doctoral research, which is to investigate the possibility of using dynamic simulation models to model the decision support processes within the context of university environment. The rest of the paper is organized as follow: Section two provides a brief overview on the use of decision support systems within higher education institutions (HEIs). In Section three, we provide a brief introduction to Systems Dynamics Methodology (SDM) and its use within HEIs. In Section four and five, we present SDM case studies, and finally, we conclude in Section six.

Abstract Universities are increasingly large in size, with non-traditional students, inadequate student–teacher ratios, declining financial support from the state, increased competition for external funds and increased competition for limited student demand. The main objective of this ongoing research is to investigate existing decision support systems capable of supporting the provisions of higher education institutions, such as Universities, and to propose and develop an interactive decision support system in the form of a simulation model for university processes with case studies from Mamoun Private University for Science and Technology in Syria.

1. Introduction Over the last twenty years, a number of countries have invested capital to improve their higher education sectors. It is widely accepted that education contributes to the quality of life, both on personal level and across society. However, this brings many challenges, which have to be addressed by higher education institutions (HEIs). According to [1], University provides people with benefits such as teaching, research, and public service that are all related to learning. In [2] it argued that universities have two main functions, namely to educate and to generate knowledge. Universities nowadays are increasingly large in size, with nontraditional students, inadequate student–teacher ratios, declining financial support from the state, increased competition for external funds and increased competition for limited student demand. In addition, the quality of teaching and learning, research and consultancy has to be taking into consideration. Universities most often evolve from the assemblies of the specialist education institutions. Partially due to this genesis process and partially due to its nature of 978-0-7695-3925-6/09 $26.00 © 2009 IEEE DOI 10.1109/ICCEE.2009.264

2. Decision Support Systems in Higher Education Institutions Educational resource planning is a highly complex administrative procedure based on extensive analysis of the entire data related to the educational framework, such as teaching resources, offered degrees, course structure. Strategic management at universities requires a comprehensive analysis of large data sets. Usually the data is not available to decision makers in a useful form or the available data has not been evaluated sufficiently to reveal hidden or crucial details. Rapid 558 556

globalization of universities enables researchers to move from individual solutions to more general strategic management models, which can be appropriately adjusted to serve the needs of particular institution. A number of models now exist with the aim at facilitating strategic decision-making [5]. Repeatedly experienced problems include nonavailability of the data in an appropriate form and lack of tools and approaches for its evaluation. From the early days of information systems, administrative academic processes such as effective resource distribution, management of various academic and service departments, automation of student admission and registration, student record management, has been among the important educationalist issues. In the 1980s, the academic decision theory focused mainly on formulating the general principles and approaches of model-based Decision Support Systems (DSSs) for academic environments [6]. A number of authors ([7], [8], [9], [10], [11], [12], [13], [14], [15], [5], [16]) have discussed various aspects of the DSSs for use within higher education institutions, these include (1) academic resources, academic advising, course scheduling; (2) resource allocation, planning and budgeting, corporate governance, performance assessment, strategic planning; (3) admission policy, analysis of enrolment demand, capacity management and enrolment management.

the information–feedback characteristics of industrial activity to show how organizational structure, amplification (in polices), and time delay (in decisions and actions) interact to influence the success of the enterprise”. The initial name of system dynamics was industrial dynamics but the concept of industrial dynamics was gradually applied to urban systems and social systems, especially world systems [21]. The name of industrial dynamics has changed into system dynamics because the method was adapted to all complex systems beyond the boundary of industrial systems.

3. 1 Use of System Dynamics Methodology for Higher Education Institutions The first attempts to implement simulation models to handle educational resource management go back to the 1960s [22] with renewed enthusiasm in the 1990s, apparently encouraged by the overall advancement of Information Technology (IT). It is believed [23] that system dynamics is an appropriate modelling technique for higher education management because universities are dynamic, complex, non-linear systems. Using system dynamic methodology can be characterized by interactions of closed chains (or feedback loops), that when combined, define the structure of the system and it’s behaviour over time. System dynamics tools could allow academic decision makers to better keep under control the complete and dynamic university system and to explore the consequences of polices and decisions that academic management is currently taking [4]. There are a few research groups of system dynamicists working on models of university management systems. They use various tools, which help to visualize relevant concepts. The main commercial tools are summarized in the Table 1. In Table 1 “Demo” means that a free demo is available over the web. “Run Time” means that you can download and test a version that is fully functional, except it does not allow you to save changes to models. “Extendible” systems offer tools to incorporate some additional user-defined functionality. “Userfriendliness” (max=5) is a subjective estimate of how easy it is to use the software once you have learned how to use it. “Learning curve” (max=5) is an estimate of how easy it is to learn to use the software based on the number of hours needed to formulate a simple onevariable model and run it starting from scratch. Learning curve=5 means a very easy to learn system. Learning curve=1 means a very difficult to learn system. Research related to universities is mostly using Stella/IThink and Vensim.

3. System Dynamics Methodology System Dynamics is a modelling method to understand the dynamics of systems that contain feedback. The dynamics of change over time include patterns of change such as growth, decay and oscillations [17]. It combines the theory, methods and philosophy needed to analyze the behavior of systems and it has been used in many fields such as corporate planning, policy design, biological and medical modelling, and theory development in the natural and social sciences. It is a powerful tool that helps assess complex issues involving delays, feedback and nonlinearities [18]. System dynamics assumes that dynamic behavior is common in all systems. Feedback means a process where one factor impacts another factor until the last factor influences the first factor, completing a cycle of influence [19]. Forrester and colleagues developed the idea of system dynamics at the early 1960s at the Massachusetts Institute of Technology [20]. At the beginning this work was focused on modeling and problem solving in industrial system, especially management systems with emphasis on the “study of

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No

5

5

Lots of users. most used in academia and business

3. 2 Case Studies For this doctoral work, the first author proposes to use real world data from Mamoun University for Science and Technology in Syria. This is privately funded institution what will affect types of models to be used for funding cycles. This will provide good opportunity to compare “value-for-money” effects between “state-owned” and “independent” education providers in the quickly developing sector.

Comments

Learning curve

Mac/ Win

Extendible

User-friendliness

Stella/ IThink

Platform

Demo/run time

Name

Table 1. Brief comparison of three most popular systems dynamics modeling tools (Adapted from [23]).

Vensim

Demo

Mac/ Win

No

5

5

Inexpensive

Powersim

Demo

Win

somewhat

5

4

Growing fast. Weboriented

4. Conclusions The social and economic development of a country and its competitiveness in continuously shifting international markets depends on the skills and competencies of people achieved through higher education. This ongoing research undertaking is to explore various avenues of modeling the decisionmaking processes of universities, in particular, a typical private university in Syria. It is hoped that using Systems Dynamics modeling techniques will further assist in shaping higher education.

Stella. In [25] is reported the developing and using the system dynamics models for planning and budgeting purposes in Arizona and Houston Universities, they chose to use system dynamics to help meet their goal of achieving greater diversity among their students and serve the higher education needs. Information generated by system dynamics models (using tool IThink) is being used in preparing for future growth in college enrolment. The impact of management policy on institutional performance with particular emphasis on the time delays between the policy decision-making and its implementation is investigated in [8]. In this paper the question” Are universities learning organizations?” and showed that the pressure on universities is due to governmental interventions which have created tensions between achievement of academic and fiscal goals. Teaching quality investigated in [23]. It identified sectors e.g. administration, staff performance, departmental effectiveness, funding, and research, which have to be considered for a future quality management model.

5. References [1]. [2]. [3].

[4].

Vensim. A Dynamic interactive game, which mimics decision-making at the university, is described in [26]. The focus is on long-term strategic problem that are dynamically persist in nature such as growing students staff ratio, poor teaching quality and low research productivity. Issues related to strategic management and decision making and opportunities to use a dynamic simulation model as a system for the support of decision-making processes, namely for selected activities of a university faculty (college) is reported in [26].

[5].

[6].

[7].

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Leslie, L. L., Brinkman, P. T. ‘The Economic Value of Higher Education’, San Francisco, Jossey-Bass. (1988) Becker, W.: ‘The Demand for Higher Education. The Economics of American Universities’. State University of New York Press, New York. (1990). Galbraith, P.L.: ‘System Thinking; A Missing Component in Higher Education Planning?’, Higher Education Policy, (1999), Vol .12, No.5, P. 141-157. Barnabe, F.: ‘From Ivory Towers to Learning Organizations; the Role of System Dynamics in the Managerialization of Academic Institutions’, Proc. 22 System Dynamics International Conference, Oxford, England, (2004), P.40-59. Vinnik, S., Scholl, M.: ‘UNICAP: Efficient Decision Support For Academic Resource and Capacity Management’, New Direction for Institutional Research, (2005), Vol.5, No.76, P.3042. (Proc. TED Conference on Government Consequences). Kassicieh, S.K.., Nowak, J.W.: ‘Decision Support Systems in Academic Planning: Important Considerations and Issues’, Information Processing and Management, (1986), Vol. 22, No. 5, P. 395403. Franz, L. S. et al.: ‘An Adaptive Decision Support System for Academic Resource Planning’ Decision Sciences, (1981), Vol. 12, No. 2, P. 276-293.

[8].

[9].

[10].

[11].

[12]. [13].

[14].

[15].

[16].

[17]. [18]. [19]. [20]. [21].

[22].

[23]. [24].

Galbraith, P.L.: ‘Strategies for Institutional Resource Allocation: Insights from a Dynamic Model’, Higher Education Policy, (1989), Vol.2, No2, P.31-38. Elimam, A.: ‘A Decision Support System for University Admission Policies’, European Journal of Operational Research, Vol.50, No.2, P.140-156. (1991) Jordan, S. M. ‘Enrolment Demand in Arizona Policy Choices and Social Consequences’, New Direction for Institutional Research, (1992), Vol.5, No.76, P.30-42. Murray, W. S., Le Blanc, L.: ‘A Decision Support System for Academic Advising’, Proc. ACM Symposium on Applied Computing, Nashville, TN, USA, (1995), P. 38-49. Saeed, K.: ‘The Dynamic of Collegial Systems in the Developing Countries’, Higher Education Policy, (1996), Vol.9, No.1, P.75-86. Borden V.M., Dalphin, J.F., Carson, L.: ‘Simulating the Effect of Student Profile Changes on Retention and Graduation Rates: A Markov Chain Analysis’, Proc.38th Annual Forum of the Association for Institutional Research, Minneapolis, USA, (1998), P. 17-20. Barlas, Y. et al.: ‘A Dynamic Simulation Game (UNIGAME) for Strategic University Management’, Simulation Gaming, (2000), Vol.31, No.5, P.331-358. Deniz, D. Z., Ersan, I.: ‘Using an Academic DSS for Student, Course and Program Assessment’: Proc. Conf. on Engineering Education, Oslo, Norway, (2001), P. 236-244. Ford, D., Sterman, J.: ‘Expert Knowledge Elicitation for Improving Mental and Formal Models’, System Dynamics Review, (1998), Vol.14, No. 4, P.309-340. Capra, F.: ‘The Web of Life; A New Scientific Understanding of Living Systems’. New York: Doubleday. (1997). Harris, B., Williams, B.: ‘System Dynamics; Enhancing Evaluation Using Systems Concepts’, WK Kellogg Foundation. (2005). Forrester, J.: ‘Industrial Dynamics’. Portland, MIT Press. (1961) Forrester, J.: ‘World Dynamics’. Cambridge, Wright-Allen Press. (1971) Levine, J. B.: ‘Application of the CAMPUS Simulation Models to the Major Planning Decisions of a Large University’, Proc. Second Conference on Applications of Simulations, New York, USA, (1968), P.317-328. Kennedy, M.: ‘Towards Taxonomy of System Dynamics Models of Higher Education’, Proc. 18th System Dynamics Conference, Bergen, Norway, (2000), P.30-40. Costanza, R, Voinova, A. ‘Modeling Ecological and Economic System with Stell”, Ecological Modeling, (2001), Vol 143, No.1-2, P.1-7. Frances, C. ‘Using System Dynamics Technology to Improve Planning for Human Resource

[25].

[26].

559 561

Development’, Proc. 6th System Dynamic International Conference, Seoul, Korea, (1995), P. 30-40. Barlas, Y., Diker. V.G.: ‘Decision Support Strategic University Management Dynamic Game’, Proc. 14th International Dynamic Conference, Boston, USA, (1996), P. 21–25. Burianová, E.: ‘Dynamic Simulation Model as a Decision Support of Management at Ostrava University’, (2007) .Proc. Enase Conference, Grenoble, France, P.171.