Аннотация
This study tackles the need for objective assessment of learning dynamics among students with special educational needs (SEN) in inclusive education in Kazakhstan. Conventional summative and criteria-based assessment mainly records outcomes. They often do not capture individual learning pace, cognitive demand, recurring error patterns, or the degree of independence demonstrated during task completion. These limitations are especially important in natural science subjects, where learners must work with abstract concepts, visual representations, formulas, and causal relationships. The purpose of the study was to develop and empirically test a model of digital screening and continuous pedagogical monitoring in inclusive sixth-grade natural science classes. The study involved 34 students with SEN and was conducted from January to May 2026. Google Classroom and electronic progress logs were used to record digital learning indicators, including task scores, completion time, number of attempts, regularity of participation, and use of learning resources. The data were evaluated using descriptive statistics, a paired-samples Student’s t-test, and Pearson correlation analysis. The mean achievement score increased from 61.8% at pre-test to 76.9% at post-test, while variability decreased. The difference was statistically significant, t(33) = 6.18, p < .001. Digital task scores were strongly associated with final achievement (r = .74, p < .001), and regular task completion also showed a positive relationship with performance (r = .66, p < .001). The findings show that digital screening supports early identification of learning difficulties, timely feedback, and more flexible adjustment of individual educational trajectories in inclusive natural science education.