Research on Personalized Learning Model Based on Learning Objectives in The Context of Educational Big Data

Qunfeng Wei ； Bin Qi

《International Journal of Social Science and Education Research》 6卷4期 (2023/04) Pp. 101-116

https://doi.org/10.6918/IJOSSER.202304_6(4).0016

摘要

After three years of COVID‐19, Internet‐based online education has developed very well, such as online Moocs, flipped classroom, etc. Such large‐scale online courses provide good support for teaching resource sharing and information exchange. However, for the increasingly large online education data, its effective research and utilization is not deep enough, especially the in‐depth discussion of personalized learning in the big data environment is not sufficient enough. In order to optimize the quality of online education, strengthen the tracking intervention and supervision of online learning, and provide guiding instructional suggestions, this paper proposes an analytic model of online learning behavior. Using the unique large amount of learning data generated through learning, the online learning behavior is studied and analyzed, and the results are applied to the online learning platform. We design the online learning behavior analysis model in the big data environment, and construct the learning behavior analysis model from left to right and top down. In longitudinal data acquisition, use method, process analysis and application, in turn in the horizontal from based on K‐Means algorithm learning resources using cluster analysis, based on A priori learning behavior and learning performance of association rules analysis, based on knowledge error rate group volume strategy, based on TAN network learning style dynamic prediction of four aspects, and based on cluster analysis and association rules give enlightenment, according to the group volume strategy and style prediction effect.

關鍵字

big data ； Online learning behavior analysis ； Learning style prediction ； Data mining ； TAN Bayesian network

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