<![CDATA[This study aims to develop and evaluate the quality of microlearning-based teaching materials for Grade 11 Sociology education and to assess their feasibility, practicality, and acceptability from the perspectives of experts, teachers, and students. The study employed a Research and Development (R&D) design using the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model. Data were collected through interviews, observations, document analysis, expert validation sheets, and user response questionnaires. The participants comprised subject-matter experts, media experts, instructional practitioners, Sociology teachers, and Grade 11 students involved in the limited trial phase. Quantitative data were analyzed using descriptive statistical techniques to calculate feasibility and response percentages, while qualitative data were analyzed through data reduction, data presentation, and conclusion drawing based on interview findings and open-ended responses. The findings indicated that the microlearning-based teaching materials developed for Grade 11 Sociology achieved an average feasibility score of 91.83%, placing them in the “highly feasible” category. Specifically, the materials received scores of 92.50% from the subject-matter expert, 89.00% from the media expert, and 94.00% from the instructional practitioner. The trial results also demonstrated high levels of practicality and acceptability, with average response scores of 91.56% from students and 92.80% from the teacher. The overall evaluation yielded an integrated score of 92.06%. These findings indicate that the developed teaching materials meet established content and media feasibility criteria, are easy to implement, and are well received by students, while supporting the understanding of sociological concepts and improving instructional efficiency in the digital era. Theoretically, this study contributes to the literature on digital instructional design in secondary education by highlighting the relevance of microlearning to cognitive load theory. Practically, the findings provide educators with a foundation for designing digital learning resources that are adaptive, cognitively manageable, and aligned with the demands of twenty-first-century education.]]>
