Students’ Perceptions of a Lopi Sandeq Racing Game Simulation Based on Mandar Local Wisdom Using Gemini Canvas
DOI:
https://doi.org/10.59110/edutrend.889Keywords:
Artificial Intelligence, Gemini Canvas, Game-Based Learning, Local Wisdom, Physics LearningAbstract
Although digital simulations and game-based learning have been widely discussed in physics education, limited studies have examined AI-assisted simulations that integrate local wisdom into contextual science learning. This study aims to examine senior high school students’ perceptions of a Gemini Canvas-based Lopi Sandeq racing simulation as a contextual physics learning medium based on Mandar local wisdom. This study employed a quantitative descriptive approach using a survey method. The participants consisted of 25 senior high school students who had participated in physics learning activities using the Lopi Sandeq racing simulation. Data were collected through a student perception questionnaire and supported by observation and documentation. The questionnaire data were analyzed using descriptive statistics by calculating the average score and percentage for each assessed aspect. The findings show that students’ overall perception of the simulation was categorized as good, with an average score of 3.98 and a percentage of 79.6%. The aspects of relevance to Mandar local wisdom and visual appearance and interactivity were categorized as very good, while ease of use, understanding of physics concepts, and learning motivation and interest were categorized as good. These findings suggest that the simulation was positively received as a supplementary medium for contextual physics learning. The study contributes to educational technology and science education by showing the potential of integrating AI-assisted simulation, game-based learning, and local wisdom in developing culturally meaningful physics learning media. However, teacher guidance remains necessary to help students connect simulation activities with formal physics concepts and mathematical reasoning.References
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