A Dataset for Learning University STEM Courses at Scale and Generating Questions at a Human Level

Abstract

We present a new dataset for learning to solve, explain, and generate university-level STEM questions from 27 courses across a dozen departments in seven universities. We scale up previous approaches to questions from courses in the departments of Mechanical Engineering, Materials Science and Engineering, Chemistry, Electrical Engineering, Computer Science, Physics, Earth Atmospheric and Planetary Sciences, Economics, Mathematics, Biological Engineering, Data Systems, and Society, and Statistics. We visualize similarities and differences between questions across courses. We demonstrate that a large foundation model is able to generate questions that are as appropriate and at the same difficulty level as human-written questions.

Cite

Text

Drori et al. "A Dataset for Learning University STEM Courses at Scale and Generating Questions at a Human Level." AAAI Conference on Artificial Intelligence, 2023. doi:10.1609/AAAI.V37I13.27091

Markdown

[Drori et al. "A Dataset for Learning University STEM Courses at Scale and Generating Questions at a Human Level." AAAI Conference on Artificial Intelligence, 2023.](https://mlanthology.org/aaai/2023/drori2023aaai-dataset/) doi:10.1609/AAAI.V37I13.27091

BibTeX

@inproceedings{drori2023aaai-dataset,
  title     = {{A Dataset for Learning University STEM Courses at Scale and Generating Questions at a Human Level}},
  author    = {Drori, Iddo and Zhang, Sarah J. and Chin, Zad and Shuttleworth, Reece and Lu, Albert and Chen, Linda and Birbo, Bereket and He, Michele and Lantigua, Pedro and Tran, Sunny and Hunter, Gregory and Feng, Bo and Cheng, Newman and Wang, Roman and Hicke, Yann and Surbehera, Saisamrit and Raghavan, Arvind and Siemenn, Alexander E. and Singh, Nikhil and Lynch, Jayson and Shporer, Avi and Verma, Nakul and Buonassisi, Tonio and Solar-Lezama, Armando},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2023},
  pages     = {15921-15929},
  doi       = {10.1609/AAAI.V37I13.27091},
  url       = {https://mlanthology.org/aaai/2023/drori2023aaai-dataset/}
}