This study develops and validates a three-level model of digital learning conditions that reflects the progression from ICT accessibility (“access”) to pedagogical use (“use”) and their influence on student learning outcomes (“impact”). Drawing on secondary analysis of the PISA 2022 ICT Familiarity Questionnaire and applying complex-sample regression together with the logic of structural equation modelling (SEM), the study examines how ICT resources, usage practices, and digital feedback (ICTFEED) interact and how they are associated with Lithuanian fifteen-year-olds’ achievement in mathematics, reading, and science. The three-level model includes: (1) ICT infrastructure—access to technology at home and at school and students’ perceived quality of technological resources; (2) ICT learning practices—use of digital tools in subject lessons, inquiry-based activities, and school-related work outside the classroom; and (3) digital feedback and its relationship with academic achievement. Results show that neither home nor school ICT availability predicts students’ experience of receiving digital feedback. The only significant infrastructure-level predictor is the perceived quality of school ICT resources (ICTQUAL). Digital feedback is most strongly predicted by ICT use in inquiry-based learning and by ICT-supported schoolwork outside the classroom, whereas ICT use in subject lessons has only a minimal effect. Across all domains, digital feedback is negatively associated with student achievement, even when ICT access, resource quality, learning-use variables, and digital leisure are controlled for. This pattern suggests that ICTFEED functions primarily as a compensatory mechanism, being more frequently used with lower-achieving students rather than serving as a direct enhancer of academic performance. The proposed three-level model offers a structured framework for interpreting students’ digital learning experiences and highlights the key components of school ICT ecosystems that shape digital assessment practices and learning outcomes.
Melnikova et al. (Tue,) studied this question.