Which one’s more work? Predicting effective credit hours between courses
Author:
Affiliation:
1. University of California Berkeley, United States
2. New York University, United States
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3448139.3448204
Reference19 articles.
1. Design and Deployment of a Better Course Search Tool: Inferring Latent Keywords from Enrollment Networks
2. Domain-Aware Grade Prediction and Top-n Course Recommendation
3. Qian Hu and Huzefa Rangwala. 2019. Academic Performance Estimation with Attention-based Graph Convolutional Networks. arXiv preprint arXiv:2001.00632(2019). Qian Hu and Huzefa Rangwala. 2019. Academic Performance Estimation with Attention-based Graph Convolutional Networks. arXiv preprint arXiv:2001.00632(2019).
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1. A Human-Centered Review of Algorithms in Decision-Making in Higher Education;Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems;2023-04-19
2. Credit hours is not enough: Explaining undergraduate perceptions of course workload using LMS records;The Internet and Higher Education;2023-01
3. Forecasting Undergraduate Majors: A Natural Language Approach;AERA Open;2022-01
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