Evaluation of Malaysian Universities Websites based on Quality in Use Evaluation Model

Nedal Nwasra (1), Nurlida Basir (2), Mohd Fadzli Marhusin (3)
(1) Universiti Sains Islam Malaysia (USIM), Faculty of Science and Technology, Nilai 71800, Malaysia
(2) Universiti Sains Islam Malaysia (USIM), Faculty of Science and Technology, Nilai 71800, Malaysia
(3) Universiti Sains Islam Malaysia (USIM), Faculty of Science and Technology, Nilai 71800, Malaysia
Fulltext View | Download
How to cite (IJASEIT) :
Nwasra, Nedal, et al. “Evaluation of Malaysian Universities Websites Based on Quality in Use Evaluation Model”. International Journal on Advanced Science, Engineering and Information Technology, vol. 8, no. 4-2, Sept. 2018, pp. 1417-22, doi:10.18517/ijaseit.8.4-2.6828.
Quality-in-Use (QinU) is one of the important quality factors in measuring website quality. Most existing studies on measuring website quality only focuses on evaluating quality from the user point of view but not on the similarities and the differences between the users and decision-makers perspective. Different stakeholders have different preference in term of quality aspects that are important. Therefore, the objective of this study is to analyse the quality aspects of the websites from different stakeholders’ perspectives and rank the websites based on the results. In this study, we develop a Quality-in-Use Evaluation Model (QinUEM) to identify the quality aspects' priorities. Two quantitative approaches were used for this purpose. The first was a Multi Criteria Decision Making (MCDM) approach using the Fuzzy Analytic Hierarchy Process (FAHP) method to determine the priority and the weight of each quality aspect from the users’ viewpoint. Then the statistical analysis was used to determine the priority of the same quality aspect from the developers’ perspective. To evaluate the model, we conducted a survey. The respondents of the survey were the students (users) and developers (decision-makers) from six Malaysian universities with 486 numbers of questionnaires been distributed. Based on the results, it shows users (students) prefer Functional Quality rather than Content and Appearance Qualities while the decision makers (developers) favour on Content rather than Appearance and Functional Qualities. These results shows different viewpoint and priority in quality aspects needed for users and decision-makers. Based on the results we then used the QinUEM to rank the universities websites according to the defined QinU.

Kim, S., & Stoel, L. (2004). Dimensional hierarchy of retail website quality. Information & management, 41(5), 619-633.

OrehovaÄki, T., Granić, A., & Kermek, D. (2013). Evaluating the perceived and estimated quality in use of Web 2.0 applications. Journal of Systems and Software, 86(12), 3039-3059.

International Organization for Standardization. Systems and Software Engineering -- Systems and Software Quality Requirements and Evaluation (SQUARE) - System and Software Quality Models. ISO. 2011;2011(25010):34.

Lin, H. F. (2010). An application of fuzzy AHP for evaluating course website quality. Computers & Education, 54(4), 877-888.

Jabar, M. A., Usman Abbas Usman, and F. Sidi. "Usability Evaluation of Universities' Websites." International Journal of Information Processing and Management 5.1 (2014): 10

Manzoor M, Hussain W. A Web Usability Evaluation Model for Higher Education Providing Universities of Asia. Sci, Tech Dev. 2012;31(2):183-192.

Dominic, P. D. D., & Jati, H. (2010, June). Evaluation method of Malaysian university website: Quality website using hybrid method. In Information Technology (ITSim), 2010 International Symposium in (Vol. 1, pp. 1-6). IEEE.

Mustafa, S. H., & Al-Zoua’bi, L. F. (2008, December). Usability of the academic websites of Jordan's universities an evaluation study. In Proceedings of the 9th International Arab Conference for Information Technology (pp. 31-40).

Plaza, I., Marcuello, J. J., Igual, R., & Arcega, F. (2009, June). Proposal of a quality model for educational software. In EAEEIE Annual Conference, 2009 (pp. 1-6). IEEE.

OrehovaÄki, T., Babić, S., & Jadrić, M. (2014, June). Exploring the validity of an instrument to measure the perceived quality in use of Web 2.0 applications with educational potential. In International Conference on Learning and Collaboration Technologies (pp. 192-203). Springer, Cham.

Hwang, G. J., Huang, T. C., & Tseng, J. C. (2004). A group-decision approach for evaluating educational web sites. Computers & Education, 42(1), 65-86.

Huang, T. C. K., & Huang, C. H. (2010). An integrated decision model for evaluating educational web sites from the fuzzy subjective and objective perspectives. Computers & Education, 55(2), 616-629.

Nwasra, N., Basir, N., & Marhusin, M. F. (2015, December). A framework for evaluating QinU based on ISO/IEC 25010 and 25012 standards. In Software Engineering Conference (MySEC), 2015 9th Malaysian (pp. 70-75). IEEE.

International Organisation for Standardization ISO. Systems and Software Engineering - Vocabulary. ISO/IEC/IEEE 247652010E. 2010;(1):1-418. doi:10.1109/IEEESTD.2010.5733835.

Srichetta, P., & Thurachon, W. (2012). Applying fuzzy analytic hierarchy process to evaluate and select product of notebook computers. International Journal of Modeling and Optimization, 2(2), 168.

Universities. www.usim.edu.my, www.ukm.edu.my www.upm.my ,www.msu.edu.my, www.mmu.edu.my, www.iukl.edu.my. Accessed: June 2016

Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and psychological measurement, 30(3), 607-610.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis (Vol. 5, No. 3, pp. 207-219). Upper Saddle River, NJ: Prentice Hall.

Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics. Allyn & Bacon/Pearson Education.

Field, A. (2009). Discovering statistics using SPSS. Sage publications.

Kline, R. B., & Santor, D. A. (1999). Principles & practice of structural equation modelling. Canadian Psychology, 40(4), 381.

Saaty TL. The Analytic Hierarchy Process. McGraw-Hill Inc. 1980:17-34.

Zadeh, L. A. (1965). Information and control. Fuzzy sets, 8(3), 338-353.

Yang, C. C., & Chen, B. S. (2004). Key quality performance evaluation using fuzzy AHP. Journal of the Chinese Institute of Industrial Engineers, 21(6), 543-550.

Torfi, F., Farahani, R. Z., & Rezapour, S. (2010). Fuzzy AHP to determine the relative weights of evaluation criteria and Fuzzy TOPSIS to rank the alternatives. Applied Soft Computing, 10(2), 520-528.

Erensal, Y. C., í–ncan, T., & Demircan, M. L. (2006). Determining key capabilities in technology management using fuzzy analytic hierarchy process: A case study of Turkey. Information Sciences, 176(18), 2755-2770.

Saaty, T. L. (1990). How to make a decision: the analytic hierarchy process. European journal of operational research, 48(1), 9-26.

Gogus, O., & Boucher, T. O. (1998). Strong transitivity, rationality and weak monotonicity in fuzzy pairwise comparisons. Fuzzy Sets and Systems, 94(1), 133-144.

Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy sets and systems, 17(3), 233-247.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
    2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
    3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).