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An Analysis of Learning Analytics Approaches for Course Evaluation

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Blended Learning. Intelligent Computing in Education (ICBL 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14797))

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Abstract

Course evaluation plays a crucial role in analysing the effectiveness of a course. Despite the emerging trend of applying learning analytics approaches to course evaluation, only limited research has been conducted on reviewing and examining the features of relevant practices. This study analysed the learning analytics approaches used for supporting course evaluation. It covered 27 empirical studies collected from Scopus that were published between 2013 and 2022. The results show the purposes of course evaluation based on learning analytics, including the enhancement of learning experience, effectiveness in learning and teaching, and learning performance and engagement. They also highlight the popular types of data for the learning analytics approaches, such as student performance, feedback, and online learning behaviours, as well as the analytical methods frequently applied, such as statistical tests, content analysis, and descriptive statistics. Additionally, the data visualisation methods most frequently used are also identified, such as tables, bar charts, and line charts. These findings inform the use of learning analytics in course evaluation and provide practical references for its implementation.

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Acknowledgments

The work described in this paper was partially supported by a grant from Hong Kong Metropolitan University (CP/2022/04).

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Authors and Affiliations

  1. Hong Kong Metropolitan University, Hong Kong, China

    Billy T. M. Wong, Kam Cheong Li & Mengjin Liu

Authors
  1. Billy T. M. Wong
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  2. Kam Cheong Li
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  3. Mengjin Liu
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Corresponding author

Correspondence to Billy T. M. Wong .

Editor information

Editors and Affiliations

  1. Tung Wah College, Hong Kong, China

    Will W. K. Ma

  2. The Hong Kong Polytechnic University, Hong Kong, China

    Chen Li

  3. University of Macau, Macau, China

    Chun Wai Fan

  4. University of Macau, Macau, China

    Leong Hou U

  5. City University of Hong Kong, Hong Kong, China

    Angel Lu

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Wong, B.T.M., Li, K.C., Liu, M. (2024). An Analysis of Learning Analytics Approaches for Course Evaluation. In: Ma, W.W.K., Li, C., Fan, C.W., U, L.H., Lu, A. (eds) Blended Learning. Intelligent Computing in Education. ICBL 2024. Lecture Notes in Computer Science, vol 14797. Springer, Singapore. https://doi.org/10.1007/978-981-97-4442-8_17

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  • DOI: https://doi.org/10.1007/978-981-97-4442-8_17

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  • Print ISBN: 978-981-97-4441-1

  • Online ISBN: 978-981-97-4442-8

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