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Emerging Techniques for Online Learning Analytics

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Technology in Education. Innovative Practices for the New Normal (ICTE 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1974))

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Abstract

The rapid growth of online learning platforms presents both challenges and opportunities for educational institutions. Online learning analytics has the potential to extract valuable insights from student learning behaviours, and such insights could offer learners flexible access to educational resources and foster lifelong learning opportunities. This paper reviews the research progress and emerging techniques in online learning analytics. We first outline the objectives of learning analytics, emphasising its potential to enhance personalised learning experiences, and examine key challenges faced in such platforms. We also review state-of-the-art techniques and explore emerging trends, natural language processing and multimodal learning analytics in particular. The paper discusses the implications of online learning analytics for educators and instructional designers, identifies open research challenges, and inspires further research and innovation to support learners in their educational journey.

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Acknowledgement

The authors acknowledge the support of the 2022 Open University of China Youth Research Grant (Q22A0009).

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Authors and Affiliations

  1. School of Computer Science, The Open University of China, Beijing, China

    Yidan Wang & YuXuan Lai

  2. School of Architecture and Arts, North China University of Technology, Beijing, China

    Xiaoran Huang

  3. Academic Affairs Department, The Open University of China, Beijing, China

    Qijing Yu

Authors
  1. Yidan Wang
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  2. Xiaoran Huang
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  3. Qijing Yu
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  4. YuXuan Lai
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Corresponding author

Correspondence to Yidan Wang .

Editor information

Editors and Affiliations

  1. Hong Kong Metropolitan University, Hong Kong, China

    Simon K. S. Cheung

  2. Hong Kong Metropolitan University, Hong Kong, China

    Fu Lee Wang

  3. Kasetsart University, Bangkok, Thailand

    Naraphorn Paoprasert

  4. Kasetsart University, Bangkok, Thailand

    Peerayuth Charnsethikul

  5. Hong Kong Metropolitan University, Hong Kong, China

    Kam Cheong Li

  6. Kasetsart University, Bangkok, Thailand

    Kongkiti Phusavat

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Wang, Y., Huang, X., Yu, Q., Lai, Y. (2024). Emerging Techniques for Online Learning Analytics. In: Cheung, S.K.S., Wang, F.L., Paoprasert, N., Charnsethikul, P., Li, K.C., Phusavat, K. (eds) Technology in Education. Innovative Practices for the New Normal. ICTE 2023. Communications in Computer and Information Science, vol 1974. Springer, Singapore. https://doi.org/10.1007/978-981-99-8255-4_10

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  • DOI: https://doi.org/10.1007/978-981-99-8255-4_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8254-7

  • Online ISBN: 978-981-99-8255-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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