An artificial intelligence-assisted adaptive gamification model integrating Ngada culture for physics learning

Abstract

Physics learning often remains abstract and insufficiently connected to students' cultural backgrounds, limiting both conceptual understanding and learning motivation. This study aimed to develop and evaluate an artificial intelligence-assisted adaptive gamification model integrating Ngada local culture to create a more meaningful, personalized, and culturally responsive physics learning environment. The study employed a Design-Based Research (DBR) approach integrated with the ADDIE framework. The model was developed, validated, and implemented with 150 senior high school students and 20 physics teachers from nine schools in Ngada Regency, Indonesia. Data were collected through expert validation sheets, practicality questionnaires, learning motivation questionnaires based on the ARCS framework, classroom observations, and pretest-posttest assessments of conceptual understanding. The findings demonstrated that the developed model achieved high content validity (S-CVI/Ave > 0.88) and high practicality according to teachers (83.3%) and students (84.8%). Students in the experimental group showed substantially greater improvement in conceptual understanding (N-gain = 0.71) than those in the control group (N-gain = 0.18). Learning motivation also improved across all ARCS dimensions, particularly in relevance, attention, and satisfaction. These findings indicate that integrating AI-assisted adaptive learning, gamification, and culturally contextualized content can enhance students' engagement, motivation, and conceptual understanding in physics. The proposed model offers a practical framework for designing technology-enhanced, culturally responsive science learning that may be adapted to similar educational contexts.