Exploring Computational Thinking Concepts in the "Magic Potion" Game: An Analysis of Student Motivation
DOI:
https://doi.org/10.23917/ieltech.v1i1.16636Keywords:
computational thinking, game-based learning, Bebras Challenge, student motivation, ARCS model, IMMSAbstract
Computational thinking (CT) has emerged as a fundamental twenty-first-century skill; however, its instruction continues to face challenges related to student motivation and engagement. This study aims to explore the computational thinking concepts embedded in the "Magic Potion" game, a digital adaptation of a Bebras Challenge task, and to analyze students' learning motivation after engaging with the game. Employing a Design and Development Research (DDR) approach, the study was conducted through four phases: needs analysis, game development, implementation with 64 eighth-grade students, and motivation evaluation using the Instructional Materials Motivation Survey (IMMS) based on the ARCS model (Attention, Relevance, Confidence, Satisfaction). The analysis revealed that the game integrates four core CT concepts: abstraction, decomposition, pattern recognition, and algorithmic thinking. The IMMS results yielded an overall mean score of 4.19 (High category), with Attention receiving the highest score (M=4.28, Very High), followed by Satisfaction (M=4.22, Very High), Relevance (M=4.19, High), and Confidence (M=4.08, High). These findings indicate that the "Magic Potion" game not only effectively integrates CT concepts but also generates positive motivational responses from students, particularly in capturing attention and providing learning satisfaction. This study contributes to the development of game-based learning media for CT and demonstrates the potential of adapting Bebras tasks as motivating instructional resources. Limitations include the sample being restricted to a single school and the one-shot case design without a control group; therefore, future research is recommended to employ experimental designs with broader samples and to directly measure gains in CT competencies.
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