Guess the learning type: A micro-designed gamified approach to machine learning types
Gamification has increasingly been adopted in teach- ing and learning, especially to boost student engagement and aid comprehension. Complex topics are often better understood when broken down into smaller micro-topics. This study explores the implementation of a micro-designed gamified approach, “G...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
2024
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| Online Access: | http://eprints.utem.edu.my/id/eprint/29593/1/Guess%20the%20Learning%20Type_%20A%20Micro-Designed%20Gamified%20Approach%20to%20Machine%20Learning%20Types.pdf http://eprints.utem.edu.my/id/eprint/29593/ https://ieeexplore.ieee.org/document/10844636/ |
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| Summary: | Gamification has increasingly been adopted in teach- ing and learning, especially to boost student engagement and aid comprehension. Complex topics are often better understood when broken down into smaller micro-topics. This study explores the implementation of a micro-designed gamified approach, “Guess the Learning Type” to enhance undergraduate students’ understanding of machine learning types. Conducted over four semesters in an Artificial Intelligence course at a Malaysian public university, the activity leverages gamification elements such as competition, time constraints, points, and penalties to increase student engagement and promote collaborative learning. Students participate in group-based activities where they must identify machine learning types based on given scenarios. The competitive nature of the activity encourages active participation and quick thinking, while immediate feedback reinforces learning outcomes. This paper examines the design and execution of the activity, its impact on student engagement, and its effectiveness in improving comprehension of supervised, unsupervised, and reinforcement learning. Results indicate that the gamified activity significantly enhances both engagement and understanding, offering a practical and alternative approach to teaching complex topics in machine learning. |
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