Deep Attentive Study Session Dropout Prediction in Mobile Learning Environment
The paper "Deep Attentive Study Session Dropout Prediction in Mobile Learning Environment" proposes the Deep Attentive Study (DAS) model to predict the probability of student dropout from an ongoing study session. Specifically tailored for mobile learning environments, the study utilizes the Santa dataset (containing student interactions with an AI tutor) to evaluate the DAS model against baseline models such as LSTM and GRU networks.
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Does Time Matter? Modeling the Effect of Time in Bayesian Knowledge Tracing
Deep Attentive Study Session Dropout Prediction in Mobile Learning Environment
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Introduction (Deep Attentive Study Session Dropout Prediction in Mobile Learning Environment)
Related Work (Deep Attentive Study Session Dropout Prediction in Mobile Learning Environment)
Study Session Dropout in Mobile Learning (Deep Attentive Study Session Dropout Prediction in Mobile Learning Environment)
Propose Method (Deep Attentive Study Session Dropout Prediction in Mobile Learning Environment)
Dataset (Deep Attentive Study Session Dropout Prediction in Mobile Learning Environment)
Experiment (Deep Attentive Study Session Dropout Prediction in Mobile Learning Environment)