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A Hierarchy-Based Analysis Approach for Blended Learning: A Case Study with Chinese Students

  • Conference paper
  • First Online:
Web and Big Data (APWeb-WAIM 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14332))

  • 137 Accesses

Abstract

Blended learning is generally defined as the combination of traditional face-to-face learning and online learning. This learning mode has been widely used in advanced education across the globe due to the COVID-19 pandemic’s social distance restriction as well as the development of technology. Online learning plays an important role in blended learning, and as it requires more student autonomy, the quality of blended learning in advanced education has been a persistent concern. Existing literature offers several elements and frameworks regarding evaluating the quality of blended learning. However, most of them either have different favours for evaluation perspectives or simply offer general guidance for evaluation, reducing the completeness, objectivity and practicalness of related works. In order to carry out a more intuitive and comprehensive evaluation framework, this paper proposes a hierarchy-based analysis approach. Applying gradient boosting model and feature importance evaluation method, this approach mainly analyses student engagement and its three identified dimensions (behavioral engagement, emotional engagement, cognitive engagement) to eliminate some existing stubborn problems when it comes to blended learning evaluation. The results show that cognitive engagement and emotional engagement play a more important role in blended learning evaluation, implying that these two should be considered to improve for better learning as well as teaching quality.

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Author information

Authors and Affiliations

  1. Chasing Jixiang Life Insurance Co., Ltd., Changsha, China

    Yu Ye & Shenghua Hu

  2. Hunan Chasing Digital Technology Co., Ltd., Changsha, China

    Gongjin Zhang & Yong Li

  3. Hunan Chasing Financial Holdings Co., Ltd., Changsha, China

    Hongbiao Si & Liang Xu

  4. Ping An Technology (Shenzhen) Co., Ltd., Shenzhen, China

    Xulong Zhang

  5. Stony Brook University, Stony Brook, USA

    Kaiyu Hu

  6. Chinasoft Co., Ltd., Beijing, China

    Fangzhou Ye

Authors
  1. Yu Ye
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  2. Gongjin Zhang
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  3. Hongbiao Si
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  4. Liang Xu
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  5. Shenghua Hu
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  6. Yong Li
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  7. Xulong Zhang
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  9. Fangzhou Ye
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Corresponding author

Correspondence to Liang Xu .

Editor information

Editors and Affiliations

  1. Peng Cheng Laboratory, Shenzhen, China

    Xiangyu Song

  2. China University of Geosciences, Wuhan, China

    Ruyi Feng

  3. China University of Geosciences, Wuhan, China

    Yunliang Chen

  4. Deakin University, Burwood, VIC, Australia

    Jianxin Li

  5. University of Exeter, Exeter, UK

    Geyong Min

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

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Ye, Y. et al. (2024). A Hierarchy-Based Analysis Approach for Blended Learning: A Case Study with Chinese Students. In: Song, X., Feng, R., Chen, Y., Li, J., Min, G. (eds) Web and Big Data. APWeb-WAIM 2023. Lecture Notes in Computer Science, vol 14332. Springer, Singapore. https://doi.org/10.1007/978-981-97-2390-4_7

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  • DOI: https://doi.org/10.1007/978-981-97-2390-4_7

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-2389-8

  • Online ISBN: 978-981-97-2390-4

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