Designing e-learning environment based on student preferences: Conjoint analysis approach

Author:

Kuzmanović Marija1ORCID,Andjelković-Labrović Jelena1ORCID,Nikodijević Ana1ORCID

Affiliation:

1. University of Belgrade, Faculty of Organizational Sciences, Serbia

Abstract

The aim of this paper was to determine students’ preferences towards e-learning environment in order to select and design its components that suit the needs of student’s best. The research was implemented using conjoint analysis. Three dimensions of interest were considered: e-learning technology, teaching method and knowledge assessment and the results show that knowledge assessment is the most important e-learning attribute for both traditional and online students. Adding into consideration the teaching method as well, further analysis showed that students can be profiled in two segments: oriented on results or process, which can be used at the beginning of studies to adjust e-learning environment. Research findings emphasized student preferences as essential for designing e-learning system, while student satisfaction turned out to be a key factor determining their persistence for studying in e-learning environment. Finally, recommendations for improvement of existing e-learning system were given.

Funder

Ministry of Education, Science and Technological Development of the Republic of Serbia

Publisher

FSFEI HE Don State Technical University

Subject

Cognitive Neuroscience,Experimental and Cognitive Psychology,Education

Reference42 articles.

1. Acharya, B., & Lee, J. (2018). Users' perspective on the adoption of e-learning in developing countries: The case of Nepal with a conjointbased discrete choice approach. Telematics and Informatics, 35(6), 1733-1743. https://doi.org/10.1016/j. tele.2018.05.002;

2. Azarcon Jr, D. E., Gallardo, C. D., Anacin, C. G., & Velasco, E. (2014). Attrition and retention in higher education institution: A conjoint analysis of consumer behavior in higher education. Asia Pacific Journal of Education, Arts and Sciences, 1(5), 107-118. Retrieved from http://apjeas.apjmr.com/wp-content /uploads/2014/11/APJEAS-2014-1-091.pdf;

3. Black, E. W., Ferdig, R. E., & DiPietro, M. (2008). An overview of evaluative instrumentation for virtual high schools. The Amer. Jrnl. of Distance Education, 22(1), 24-45. https://doi. org/10.1080/08923640701713422;

4. Bouhnik, D., & Marcus, T. (2006). Interaction in distance-learning courses. Journal of the American Society for Information Science and Technology, 57(3), 299-305. https://doi. org/10.1002/asi.20277;

5. Carey, J. M., Carman, K. R., Clayton, K. P., Horiuchi, Y., Htun, M., & Ortiz, B. (2018). Who wants to hire a more diverse faculty? A conjoint analysis of faculty and student preferences for gender and racial/ethnic diversity. Politics, Groups, and Identities, 1-19. https://doi.org/10.1080/215655 03.2018.1491866;

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3