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Performance measurement of e-learning using student satisfaction analysis

Author

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  • Miroslava Raspopovic

    (Belgrade Metropolitan University)

  • Aleksandar Jankulovic

    (Belgrade Metropolitan University)

Abstract

The purpose of this paper is to analyze e-learning system quality through the analysis of student satisfaction and the usage of learning materials. This analysis takes into consideration both online and traditional students who are using the same e-learning system. The goal of the analysis is to identify factors which influence student satisfaction and to address heterogeneous styles and needs of both groups of students, so that future pedagogical and motivational methods in teaching and learning can be appropriately selected, developed and implemented. It was of particular interest to explore student satisfaction with quality of an e-learning system and online study approach. Reasons that may influence opinions of online and traditional students are examined and presented. The results are used to give recommendations for e-learning improvements and to propose the model with 4 groups of dimensions for performance measurement each of which best represents satisfaction of both groups of students.

Suggested Citation

  • Miroslava Raspopovic & Aleksandar Jankulovic, 2017. "Performance measurement of e-learning using student satisfaction analysis," Information Systems Frontiers, Springer, vol. 19(4), pages 869-880, August.
    • Handle: RePEc:spr:infosf:v:19:y:2017:i:4:d:10.1007_s10796-016-9636-z
    DOI: 10.1007/s10796-016-9636-z
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    References listed on IDEAS

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    Cited by:

    1. Elisabeth Bustos-Contell & Luis Porcuna-Enguix & José Serrano-Madrid & Gregorio Labatut-Serer, 2021. "The Role of e-Tutor Competencies in Postgraduate e-Learning Courses: Spotlight on Emotion Management," Sustainability, MDPI, vol. 13(17), pages 1-13, August.
    2. Wala Bagunaid & Naveen Chilamkurti & Prakash Veeraraghavan, 2022. "AISAR: Artificial Intelligence-Based Student Assessment and Recommendation System for E-Learning in Big Data," Sustainability, MDPI, vol. 14(17), pages 1-22, August.
    3. Xiu-Kin Loh & Voon-Hsien Lee & Xiu-Ming Loh & Garry Wei-Han Tan & Keng-Boon Ooi & Yogesh K. Dwivedi, 2022. "The Dark Side of Mobile Learning via Social Media: How Bad Can It Get?," Information Systems Frontiers, Springer, vol. 24(6), pages 1887-1904, December.

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