McGinley, Tex (2024) Designing Game-Based Machine Learning Education for Dutch High School Students. Bachelor's Thesis, Artificial Intelligence.
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Abstract
This paper explores the use of game-based learning (GBL) to teach machine learning (ML) concepts, specifically recommender systems, to Dutch high school students in the VWO educational stream. The study addresses the gap in AI education within the Dutch curriculum by developing an engaging and accessible educational program. This program includes a comprehensive teaching guide, presentation slides, and the Movie Ranker game, which simulates a Netflix-style recommendation system to illustrate ML principles. The program was created using the preparation, design, and improvement methodology adapted from Park and Kwon’s South Korean paper, with the goal of demystifying AI, educating about recommender systems, introducing reinforcement learning (RL) concepts through the Multi-Armed Bandit (MAB) problem, and highlighting the ethical considerations and implications of these systems. The created Movie Ranker game incorporates a competitive mechanic through the use of an ε-Greedy bandit, which the player must compete against. The results of the implemented ε-Greedy algorithm showed that it is effective in the created environment, performing better than a random agent in a statistically significant manner. This competitive element not only engages students but also helps them understand RL concepts like the exploration vs. exploitation dilemma. While the program has yet to be tested and evaluated in a real-world classroom setting, preliminary findings suggest that the game’s interactiv
| Item Type: | Thesis (Bachelor's Thesis) |
|---|---|
| Supervisor name: | Cardenas Cartagena, J. D. |
| Degree programme: | Artificial Intelligence |
| Thesis type: | Bachelor's Thesis |
| Language: | English |
| Date Deposited: | 30 Jul 2024 10:01 |
| Last Modified: | 30 Jul 2024 10:01 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/33548 |
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