Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/12296
Title: A Survey of Research Trends in University Websites’ Usability Evaluation
Authors: Adepoju, Solomon Adelowo
Oyefolahan, Ishaq Oyebisi
Abdullahi, Muhammad Bashir
Mohammed, Adamu Alhaji
Keywords: Usability
Websites
Multi Criteria Decision Making
Website Evaluation
University Websites
Issue Date: May-2019
Publisher: i-manager
Citation: Solomon A. Adepoju, Ishaq O. Oyefolahan, Muhammad B. Abdullahi, and Adamu A. Mohammed. A Survey of Research Trends in University Websites’ Usability Evaluation. i-manager’s Journal on Information Technology (JIT), Vol. 8, No. 2, pp. 11-19, March - May 2019
Series/Report no.: Vol. 8, No. 2, March - May 2019.;
Abstract: Research on website usability evaluation have been growing in recent times as a result of increased internet penetration rate globally. In view of this, several efforts have been made to develop usability evaluation methods for different genre of websites. Due to its uniqueness, university websites which is a class of academic websites require further attention. This paper hence provides a brief survey of various usability evaluation methods used in university websites and with special focus on Multi Criteria Decision Making (MCDM) approaches. A total of thirty five scholarly articles were retrieved from online database from year 2000 to 2018. The review was classified based on usability evaluation methods, MCDM approaches, and automated tools. Results from the trend analysis shows that automated tools, heuristic evaluation, and user testing methods are the mostly used usability evaluation methods. MCDM approach usage in usability evaluation is also found to be on the increase as well. It is therefore recommended that more attention should be given to the usage of this methodology in the usability evaluation of this important genre of websites.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/12296
ISSN: 2277-5110
Appears in Collections:Computer Science

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