Abstract
Intuitively, students who start a homework assignment earlier and spend more time on it should receive better grades on the assignment. However, existing literature on the impact of time spent on homework is not clear-cut and comes mostly from K-12 education. It is not clear that these prior studies can inform coursework in deep learning due to differences in demographics, as well as the computational time needed for assignments to be completed. We study this problem in a post-hoc study of three semesters of a deep learning course at the University of Maryland, Baltimore County (UMBC), and develop a hierarchical Bayesian model to help make principled conclusions about the impact on student success given an approximate measure of the total time spent on the homework, and how early they submitted the assignment. Our results show that both submitting early and spending more time positively relate with final grade. Surprisingly, the value of an additional day of work is apparently equal across students, even when some require less total time to complete an assignment.
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Notes
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Available at https://www.manning.com/books/inside-deep-learning.
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Start time potentially impacted propensity to engage in academic misconduct, amongst other stressors with the pandemic. These considerations are critical but beyond our scope and data.
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In this context B is the beta function, and is not used in this context anywhere else in the manuscript.
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Raff, E., Matuszek, C. (2024). Does Starting Deep Learning Homework Earlier Improve Grades?. In: Nowaczyk, S., et al. Artificial Intelligence. ECAI 2023 International Workshops. ECAI 2023. Communications in Computer and Information Science, vol 1948. Springer, Cham. https://doi.org/10.1007/978-3-031-50485-3_38
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