Measuring performance of virtual learning environment system in higher education

Purpose – The purpose of this paper is to measure the performance of commercial virtual learning environment (VLE) systems, which helps the decision makers to select the appropriate system for their institutions. Design/methodology/approach – This paper develops an integrated multiple criteria decision making approach, which combines the analytic hierarchy process (AHP) and quality function deployment (QFD), to evaluate and select the best system. The evaluating criteria are derived from the requirements of those who use the system. A case study is provided to demonstrate how the integrated approach works. Findings – The major advantage of the integrated approach is that the evaluating criteria are of interest to the stakeholders. This ensures that the selected system will achieve the requirements and satisfy the stakeholders most. Another advantage is that the approach can guarantee the benchmarking to be consistent and reliable. From the case study, it is proved that the performance of a VLE system being used at the university is the best. Therefore, the university should continue to run the system in order to support and facilitate both teaching and learning. Originality/value – It is believed that there is no study that measures the performance of VLE systems, and thus decision makers may have difficulties in system evaluation and selection for their institutions.

[1]  B. Williams,et al.  Operations management. , 2001, Optometry.

[2]  S. G. Deshmukh,et al.  Total quality management (TQM) in self‐financed technical institutions: A quality function deployment (QFD) and force field analysis approach , 2006 .

[3]  Helen E. Higson,et al.  Multiple criteria decision-making techniques in higher education , 2006 .

[4]  Younghwa Lee,et al.  The Competitiveness of the Information Systems Major: An Analytic Hierarchy Process , 2006, J. Inf. Syst. Educ..

[5]  Shieu-Ming Chou,et al.  Evaluating the service quality of undergraduate nursing education in Taiwan--using quality function deployment. , 2004, Nurse education today.

[6]  James W. Denton,et al.  Curriculum and Course Design: A New Approach Using Quality Function Deployment , 2005 .

[7]  N. K. Kwak,et al.  A multicriteria decision-making approach to university resource allocations and information infrastructure planning , 1998, Eur. J. Oper. Res..

[8]  Sanjaya Mishra,et al.  Using C&IT to support teaching , 2004, Br. J. Educ. Technol..

[9]  Helen E. Higson,et al.  An integrated multiple criteria decision making approach for resource allocation in higher education , 2007 .

[10]  Veli Deniz,et al.  Quality Function Deployment in Education: A Curriculum Review , 2005 .

[11]  Masood A. Badri,et al.  Awards of excellence in institutions of higher education: an AHP approach , 2004 .

[12]  Salih O. Duffuaa,et al.  Quality function deployment for designing a basic statistics course , 2003 .

[13]  Majid Jaraiedi,et al.  Total Quality Management Applied to Engineering Education , 1994 .

[14]  Sehun Kim,et al.  A Curriculum Design for E-Commerce Security , 2005, J. Inf. Syst. Educ..

[15]  Xiande Zhao,et al.  An application of quality function deployment to improve the quality of teaching , 1998 .

[16]  Rafail N. Gasimov,et al.  The analytic hierarchy process and multiobjective 0-1 faculty course assignment , 2004, Eur. J. Oper. Res..

[17]  H. Brian Hwarng,et al.  Translating customers’ voices into operations requirements ‐ A QFD application in higher education , 2001 .

[18]  Gülser Köksal,et al.  Planning and design of industrial engineering education quality , 1998 .

[19]  Håkan Wiklund,et al.  Student focused design and improvement of university courses , 1999 .

[20]  S. Sahney,et al.  A SERVQUAL and QFD approach to total quality education , 2004 .

[21]  M. Bohanec,et al.  The Analytic Hierarchy Process , 2004 .

[22]  D. K. Banwet,et al.  Enhancing quality in education: application of quality function deployment – an industry perspective , 2003 .