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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2510.22392 |
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| _version_ | 1866915576968904704 |
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| author | Ameen, Mohd Ruhul Islam, Akif Miah, Abu Saleh Musa Rafat, M. Saifuzzaman Shin, Jungpil |
| author_facet | Ameen, Mohd Ruhul Islam, Akif Miah, Abu Saleh Musa Rafat, M. Saifuzzaman Shin, Jungpil |
| contents | Teaching complex machine learning concepts such as reinforcement learning and Markov Decision Processes remains challenging in engineering education. Students often struggle to connect abstract mathematics to real-world applications. We present LearnML@Cricket, a 12-week curriculum that uses cricket analytics to teach these concepts through practical, hands-on examples. By mapping game scenarios directly to ML algorithms, students learn through doing rather than memorizing. Our curriculum includes coding laboratories, real datasets, and immediate application to engineering problems. We propose an empirical study to measure whether this approach improves both understanding and practical implementation skills compared to traditional teaching methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_22392 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Teaching Machine Learning Through Cricket: A Practical Engineering Education Approach Ameen, Mohd Ruhul Islam, Akif Miah, Abu Saleh Musa Rafat, M. Saifuzzaman Shin, Jungpil Human-Computer Interaction Teaching complex machine learning concepts such as reinforcement learning and Markov Decision Processes remains challenging in engineering education. Students often struggle to connect abstract mathematics to real-world applications. We present LearnML@Cricket, a 12-week curriculum that uses cricket analytics to teach these concepts through practical, hands-on examples. By mapping game scenarios directly to ML algorithms, students learn through doing rather than memorizing. Our curriculum includes coding laboratories, real datasets, and immediate application to engineering problems. We propose an empirical study to measure whether this approach improves both understanding and practical implementation skills compared to traditional teaching methods. |
| title | Teaching Machine Learning Through Cricket: A Practical Engineering Education Approach |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2510.22392 |