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https://doi.org/10.21256/zhaw-26814| Publication type: | Working paper – expertise – study |
| Title: | A learned simulation environment to model student engagement and retention in automated online courses |
| Authors: | Imstepf, Nicolas Senn, Saskia Fortin, Antonio Russell, Benjamin Horn, Claus |
| et. al: | No |
| DOI: | 10.48550/arXiv.2212.14693 10.21256/zhaw-26814 |
| Extent: | 6 |
| Issue Date: | 22-Dec-2022 |
| Publisher / Ed. Institution: | arXiv |
| Other identifiers: | arXiv:2212.14693 |
| Language: | English |
| Subjects: | Education technology; Student modeling; Deep reinforcement learning |
| Subject (DDC): | 378: Higher education |
| Abstract: | We developed a simulator to quantify the effect of exercise ordering on both student engagement and retention. Our approach combines the construction of neural network representations for users and exercises using a dynamic matrix factorization method. We further created machine learning models of success and dropout prediction. As a result, our system is able to predict student engagement and retention based on a given sequence of exercises selected. This opens the door to the development of versatile reinforcement learning agents which can substitute the role of private tutoring in exam preparation. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/26814 |
| License (according to publishing contract): | CC BY-NC-ND 4.0: Attribution - Non commercial - No derivatives 4.0 International |
| Departement: | Life Sciences and Facility Management |
| Organisational Unit: | Institute of Chemistry and Biotechnology (ICBT) Institute of Computational Life Sciences (ICLS) |
| Published as part of the ZHAW project: | Optimierung von Online-Bildungssystemen mit Hilfe von Reinforcement Learning |
| Appears in collections: | Publikationen Life Sciences und Facility Management |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2022_Imstepf-etal_Learned-simulation.environment-student-engagement-retention.pdf | 738 kB | Adobe PDF |  View/Open |
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Imstepf, N., Senn, S., Fortin, A., Russell, B., & Horn, C. (2022). A learned simulation environment to model student engagement and retention in automated online courses. arXiv. https://doi.org/10.48550/arXiv.2212.14693
Imstepf, N. et al. (2022) A learned simulation environment to model student engagement and retention in automated online courses. arXiv. Available at: https://doi.org/10.48550/arXiv.2212.14693.
N. Imstepf, S. Senn, A. Fortin, B. Russell, and C. Horn, “A learned simulation environment to model student engagement and retention in automated online courses,” arXiv, Dec. 2022. doi: 10.48550/arXiv.2212.14693.
IMSTEPF, Nicolas, Saskia SENN, Antonio FORTIN, Benjamin RUSSELL und Claus HORN, 2022. A learned simulation environment to model student engagement and retention in automated online courses. arXiv
Imstepf, Nicolas, Saskia Senn, Antonio Fortin, Benjamin Russell, and Claus Horn. 2022. “A Learned Simulation Environment to Model Student Engagement and Retention in Automated Online Courses.” arXiv. https://doi.org/10.48550/arXiv.2212.14693.
Imstepf, Nicolas, et al. A Learned Simulation Environment to Model Student Engagement and Retention in Automated Online Courses. arXiv, 22 Dec. 2022, https://doi.org/10.48550/arXiv.2212.14693.
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