<![CDATA[Inclusive education requires assessment practices that accommodate diverse learner characteristics, particularly for slow learners. Grounded in cognitive load theory, mastery learning theory, and universal design for learning, this study aims to develop and validate a science microlearning-based assessment instrument designed specifically for slow learners in inclusive science education. This study employed a research and development approach integrated with design-based research principles, consisting of four phases: needs analysis, design and development, expert validation and revision, and field testing. The instrument was developed as a digital science microlearning-based assessment comprising short, focused items targeting single learning objectives with immediate formative feedback. Content validity was evaluated by four experts using the content validity index while reliability was examined through internal consistency and test–retest analysis involving 30 slow learners in inclusive classrooms. The results demonstrated strong psychometric properties. The instrument achieved a scale-level content validity index of 0.92, indicating high expert agreement on relevance and appropriateness. Reliability analysis yielded a Cronbach’s alpha coefficient of 0.87, reflecting high internal consistency, with test–retest stability of r = 0.82. Teachers also reported high practicality and diagnostic usefulness of the instrument for identifying specific learning gaps and supporting instructional decisions. These findings indicate that science microlearning-based assessment provides a valid, reliable, and inclusive approach to evaluating incremental mastery among slow learners. The study offers practical implications for inclusive assessment practices by providing a low-cognitive-load, mastery-oriented evaluation model that supports equitable learning opportunities and informed instructional adaptation]]>
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