DPOTS: eXplainable Artificial Intelligence (XAI) Dataset for Predicting Outcomes from Time Sequences and Student Behaviors

Accurately and timely predicting learners' outcomes can assist educators in making instructional decisions or interventions. This helps prevent students from falling into a vicious cycle of decreased academic achievement and increased aversion to learning, potentially leading to dropout. Data-driven models often outperform eXplainable Artificial Intelligence (XAI) models in predicting learning outcomes, yet their lack of interpretability can hinder trust from educators. Therefore, this study developed an XAI information fusion framework that not only extracts potential trends from the time series of student grades to enhance predictive performance but also mines explicit relationships between classroom behaviors and learning outcomes. This reveals the behavioral causes behind changes in grades. Furthermore, we have made public the Dataset for Predicting Outcomes from Time sequences and Student behaviors (DPOTS), and validated the effectiveness of the developed XAI information fusion framework based on DPOTS. The results indicate that, the MAE of CEO-IF was reduced by an average of 26.32% compared to the baseline algorithms, and it showed a 22.63% reduction compared to the averaging-based information fusion method.

Copyright

The Copyright of the DPOTS belongs to the authors and their affiliates. You are free to use DPOTS for research purposes. The authors is not responsible for any consequences of the user's use of the data or code. Papers containing data generated using the data or code should declare the use of the DPOTS , and cite the corresponding references correctly: 

Code: https://doi.org/10.5281/zenodo.14958102

Paper: https://doi.org/10.1145/3706599.3721212

Support

According to ethical requirements, if you need to access this data, please send an email to Zi Wei Chen to apply.

If you have any comments or suggestions, please contact 2220042009@stu.jcu.edu.cn (Zi-Wei Chen). Finally, thank you again for using DPOTS.