Cloud-based learning and cognitive development among lower-secondary students (Grades 8–9): evidence from schools in Kazakhstan

Despite growing attention to the digitalization of education and the development of AI-supported learning in Kazakhstan, as well as broader international agendas, the empirical evidence on whether cloud-based learning (CBL) strengthens adolescents’ cognitive development and under what conditions and through which mechanisms remain fragmented. This study aimed to assess the prospects for implementing CBL in Kazakhstani schools and to empirically determine how, under which conditions, and to what extent CBL influences the cognitive development of adolescents aged 14–15. In a cluster randomized controlled trial with an explanatory mixed-methods design, 66 intact classes ( N = 1,650; experimental group: 33 classes; control group: 33 classes) from 18 public schools (9 urban, 9 rural) were assigned to a 12-week Informatics intervention supported by CBL or to traditional Informatics instruction. Assessments were administered at baseline, immediately post-intervention, and 12 weeks later to examine effect durability. Cognitive outcomes were measured using performance-based tasks and validated questionnaires capturing perceived teacher competence (PTC), self-regulated learning (SRL), and cognitive engagement (CE). Between-group differences were examined using ANCOVA with baseline adjustment and standardized mean differences, and hypothesized mechanisms were tested via structural equation modeling (SEM). The intervention produced a statistically significant overall gain at posttest (Hedges’ g = 0.21), which increased at delayed follow-up (Hedges’ g = 0.28, p = 0.025). The largest improvements were observed in computational thinking ( g = 0.31) and algorithmic problem solving ( g = 0.25), with smaller yet significant gains in logical-analytical reasoning ( g = 0.20) and metacognitive strategies (g = 0.24); adjusted posttest differences were also significant (partial η 2 = 0.062, p < 0.001). The SEM model demonstrated good fit (χ 2 (36) = 49.73, p > 0.05; RMSEA = 0.045; CFI = 0.975; TLI = 0.963) and indicated predominantly indirect effects of CBL, higher PTC was associated with stronger SRL and CE, which in turn predicted improved cognitive outcomes. Explained variance was substantial for cognitive abilities (R 2 = 0.664) and cognitive skills (R 2 = 0.647). Overall, the findings suggest that CBL can deliver durable and meaningful improvements when a synergistic set of readiness conditions positively associated with implementation quality is in place, particularly teachers’ preparedness and pedagogical expertise, adequate infrastructure, and purposeful strengthening of students’ self-regulation and engagement. Study limitations include school selection and reliance on self-report measures, which should be considered when generalizing and scaling the results.