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Found 6 papers, 3 papers with code
Prescribing Deep Attentive Score Prediction Attracts Improved Student Engagement
To that end, we apply a state-of-the-art deep attentive neural network-based score prediction model to Santa, a multi-platform English ITS with approximately 780K users in South Korea that exclusively focuses on the TOEIC (Test of English for International Communications) standardized examinations.
Deep Attentive Study Session Dropout Prediction in Mobile Learning Environment
First, we define the concept of the study session, study session dropout and study session dropout prediction task in a mobile learning environment.
Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing
To the best of our knowledge, this is the first work to suggest an encoder-decoder model for knowledge tracing that applies deep self-attentive layers to exercises and responses separately.
Ranked #2 on
Knowledge Tracing
on EdNet
Assessment Modeling: Fundamental Pre-training Tasks for Interactive Educational Systems
However, such methods fail to utilize the full range of student interaction data available and do not model student learning behavior.
EdNet: A Large-Scale Hierarchical Dataset in Education
With advances in Artificial Intelligence in Education (AIEd) and the ever-growing scale of Interactive Educational Systems (IESs), data-driven approach has become a common recipe for various tasks such as knowledge tracing and learning path recommendation.
Creating A Neural Pedagogical Agent by Jointly Learning to Review and Assess
Our model outperforms existing approaches over several metrics in predicting user response correctness, notably out-performing other methods on new users without large question-response histories.
