Guess the learning type: A micro-designed gamified approach to machine learning types

Zulkarnain, Nur Zareen and Syed Ahmad, Sharifah Sakinah (2024) Guess the learning type: A micro-designed gamified approach to machine learning types. In: 2024 International Conference on TVET Excellence & Development (ICTeD), 16 December 2024 through 17 December 2024, Melaka, Malaysia.

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Abstract

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.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Federated learning, Education, Active learning, Machine learning, Reinforcement learning, Games, Time factors
Divisions:	Faculty of Information and Communication Technology
Depositing User:	Wizana Abd Jalil
Date Deposited:	26 Feb 2026 04:34
Last Modified:	26 Feb 2026 04:34
URI:	http://eprints.utem.edu.my/id/eprint/29593
Statistic Details:	View Download Statistic

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