Predicting Attention Drop in Learners Using Interaction-Based Machine Learning Models
DOI:
https://doi.org/10.63949/Keywords:
- Attention Prediction,
- Learning Analytics,
- Machine Learning,
- Student Engagement
Abstract
Digital learning platforms have brought a revolution in the educational world by providing flexible and personalized learning experiences to everyone. The main challenge of these platforms is retaining the learner's attention. The change in attention of the learner results in reduced knowledge gain and learning outcomes. Identifying the core reasons of reduced attention can help learning platforms improve themselves. The purpose of this research is to predict the main reasons and features of the platform for low attention among learners based on the behavioural interaction data obtained from a large database of learners.
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References
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