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Deep Learning vs. Bayesian Knowledge Tracing: Student Models for Interventions
| Content Provider | Semantic Scholar |
|---|---|
| Author | Lin, Chen |
| Copyright Year | 2018 |
| Abstract | Bayesian Knowledge Tracing (BKT) is a commonly used approach for student modeling, and Long Short Term Memory (LSTM) is a versatile model that can be applied to a wide range of tasks, such as language translation. In this work, we directly compared three models: BKT, its variant Intervention-BKT (IBKT), and LSTM, on two types of student modeling tasks: post-test scores prediction and learning gains prediction. Additionally, while previous work on student learning has often used skill/knowledge components identified by domain experts, we incorporated an automatic skill discovery method (SK), which includes a nonparametric prior over the exercise-skill assignments, to all three models. Thus, we explored a total of six models: BKT, BKT+SK, IBKT, IBKT+SK, LSTM, and LSTM+SK. Two training datasets were employed, one was collected from a natural language physics intelligent tutoring system named Cordillera, and the other was from a standard probability intelligent tutoring system named Pyrenees. Overall, our results showed that BKT and BKT+SK outperformed the others on predicting post-test scores, whereas LSTM and LSTM+SK achieved the highest accuracy, F1-measure, and area under the ROC curve (AUC) on predicting learning gains. Furthermore, we demonstrated that by combining SK with the BKT model, BKT+SK could reliably predict post-test scores using only the earliest 50% of the entire training sequences. For learning gain early prediction, using the earliest 70% of the entire sequences, LSTM can deliver a comparable prediction as using the entire training sequences. The findings yield a learning environment that can foretell students' performance and learning gains early, and can render adaptive pedagogical strategy accordingly. |
| Starting Page | 28 |
| Ending Page | 54 |
| Page Count | 27 |
| File Format | PDF HTM / HTML |
| DOI | 10.5281/zenodo.3554691 |
| Volume Number | 10 |
| Alternate Webpage(s) | https://jedm.educationaldatamining.org/index.php/JEDM/article/download/318/96 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
