@inproceedings{8a201225548540d9b100950d11e0a02c,
title = "Leveraging Book Indexes for Automatic Extraction of Concepts in MOOCs",
abstract = "Concepts are basic elements in any learning module and are thus very useful for modeling, summarizing, and previewing the content of any module. Automatic extraction of the major concepts from online education materials enables many useful applications. In this paper, we propose to leverage textbooks and their back-of-the-book indexes as training data to train a supervised machine learning algorithm for automatic extraction of concepts from text data in the education domain. We evaluate this idea by training neural networks on three textbooks and applying the trained neural networks to extract concepts from the lecture transcripts of two MOOCs. Our results suggest great promise for further exploration of this direction.",
keywords = "back-of-the-book index, concept extraction, lstm, mooc, neural networks",
author = "Assma Boughoula and Aidan San and Zhai, \{Cheng Xiang\}",
note = "This material is based upon work supported by the National Science Foundation under Grant No. 1801652.; 7th Annual ACM Conference on Learning at Scale, L@S 2020 ; Conference date: 12-08-2020 Through 14-08-2020",
year = "2020",
month = aug,
day = "12",
doi = "10.1145/3386527.3406749",
language = "English (US)",
series = "L@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale",
publisher = "Association for Computing Machinery",
pages = "381--384",
booktitle = "L@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale",
address = "United States",
}