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Application Technology on Collaborative Training of Interactive Learning Activities and Tendency Preference Diversion

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  • Xiaona Xia

Abstract

Mining problems and exploring rules are the key problems in the learning process, and also the difficulties in education big data. Therefore, taking learning behavior as the research objective, this study demonstrates the collaborative training method of multi view learning interaction process driven by big data, so as to realize the tendency preference diversion of learning behavior. Based on collaborative training method of learning behavior. Through adequate experiments, we get the suitable and valuable rules, constructs the directed topological relationship of tendency preference division, and mines the feasible improvement measures and intervention mechanism. Experiments and practices show that the potential topological relationship can effectively improve and enable learning, and improve the assessment results.

Suggested Citation

  • Xiaona Xia, 2022. "Application Technology on Collaborative Training of Interactive Learning Activities and Tendency Preference Diversion," SAGE Open, , vol. 12(2), pages 21582440221, April.
    • Handle: RePEc:sae:sagope:v:12:y:2022:i:2:p:21582440221093368
    DOI: 10.1177/21582440221093368
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    References listed on IDEAS

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    1. Ayman G. Fayoumi & Amjad Fuad Hajjar, 2020. "Advanced Learning Analytics in Academic Education: Academic Performance Forecasting Based on an Artificial Neural Network," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 16(3), pages 70-87, July.
    2. Antonio Matas-Terrón & Juan José Leiva-Olivencia & Cristina Negro-Martínez, 2020. "Tendency to Use Big Data in Education Based on Its Opportunities According to Andalusian Education Students," Social Sciences, MDPI, vol. 9(9), pages 1-12, September.
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    Cited by:

    1. Xiaona Xia & Wanxue Qi, 2024. "Driving STEM learning effectiveness: dropout prediction and intervention in MOOCs based on one novel behavioral data analysis approach," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-19, December.
    2. Tianjiao Wang & Xiaona Xia, 2023. "The Study of Hierarchical Learning Behaviors and Interactive Cooperation Based on Feature Clusters," SAGE Open, , vol. 13(2), pages 21582440231, April.
    3. Xia, Xiaona & Qi, Wanxue, 2024. "Multilayer knowledge graph construction and learning behavior routing guidance based on implicit relationships of MOOCs," Technological Forecasting and Social Change, Elsevier, vol. 204(C).

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