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Abstract
Previous studies have designed educational methods to cultivate digital citizenship behavior and support the construction of knowledge. However, these methods have not well incorporated personalized feedback mechanisms for enhancing digital citizenship knowledge. Therefore, this study proposed an algorithm that combines concept-effect propagation, fuzzy logic, and decision tree methods to address this drawback and create a personalized, contextual gaming experience. This personalization ensures an engaging and contextually relevant learning experience, addressing learning challenges related to digital citizenship scales. The game was tailored to individual learning experiences and decision-making patterns, with fuzzy logic interpreting nuanced student responses and decision trees guiding learning paths. A digital citizenship knowledge test and an affection questionnaire measured the game’s impact. Moreover, eye tracking was used to ensure attention in the experimental group. Therefore, a quasi-experimental design was conducted to evaluate the influence of a digital citizenship game on 110 students. ANCOVA and the Chi-square tests were performed to analyze students’ knowledge of digital citizenship. Moreover, eye-tracking metrics were used to gain deeper insights into students’ visual attention and engagement. The experimental results reveal that the proposed game enhanced the students’ digital citizenship achievement and promoted their perceptions. Additionally, eye-tracking data showed that the proposed gaming environment positively influenced students’ engagement. Findings indicate that using fuzzy logic and decision trees in educational games significantly promotes affection and alters attention in learning digital citizenship. This study contributes to educational technology by showcasing the potential benefits of personalized educational experiences. The insights gained are valuable for educators and educational game developers focused on digital citizenship education.
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1 Faculty of Education, Khon Kaen University, Khon Kaen, Thailand
2 Graduate Institute of Educational Information and Measurement, National Taichung University of Education, Taichung City, Taiwan; Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taipei City, Taiwan; Yuan Ze University, Taoyuan City, Taiwan
3 Behavioral Science Research Institute, Srinakharinwirot University, Bangkok, Thailand
4 Faculty of Education, Khon Kaen University, Khon Kaen, Thailand; Digital Education and Learning Engineering Association, Nonthaburi, Thailand