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Student's classroom behaviour recognition method based on abstract hidden Markov model

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  • Guojuan Li

Abstract

In order to improve the standardisation of mutual information index, accuracy rate and recall rate of student classroom behaviour recognition method, this paper proposes a student's classroom behaviour recognition method based on abstract hidden Markov model (HMM). After cleaning the students' classroom behaviour data, improve the data quality through interpolation and standardisation, and then divide the types of students' classroom behaviour. Then, in support vector machine, abstract HMM is used to calculate the output probability density of support vector machine. Finally, according to the characteristic interval of classroom behaviour, we can judge the category of behaviour characteristics. The experiment shows that normalised mutual information (NMI) index of this method is closer to one, and the maximum AUC-PR index can reach 0.82, which shows that this method can identify students' classroom behaviour more effectively and reliably.

Suggested Citation

  • Guojuan Li, 2024. "Student's classroom behaviour recognition method based on abstract hidden Markov model," International Journal of Information Technology and Management, Inderscience Enterprises Ltd, vol. 23(3/4), pages 232-243.
    • Handle: RePEc:ids:ijitma:v:23:y:2024:i:3/4:p:232-243
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