KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students (2024.emnlp-main)
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| Challenge: | Existing student models use study data like student's past responses to predict the probability a student can recall a flashcard. |
| Approach: | They propose to use student models to predict recall of flashcards to build a content-aware student model that uses deep knowledge tracing, retrieval, and BERT to predict student recall. |
| Outcome: | The proposed content-aware student model outperforms existing student models in AUC and calibration error and is more efficient than SOTA. |
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