Measuring Personalized Learning in the Smart Classroom Learning Environment: Development and Validation of an Instrument

Abstract

Smart classrooms leverage intelligent and mobile technologies to create highly interactive, student-centered environments conducive to personalized learning. However, measuring students’ personalized learning experiences in these technologically advanced spaces remains a challenge. This study addresses the gap by developing and validating a Smart Classroom Environment–Personalized Learning Scale (SCE-PL). Drawing on a comprehensive literature review, content-expert feedback, and iterative item refinement, an initial pool of 48 items was reduced to 39 and subsequently to 34 following item-level analyses. Two datasets were collected from Chinese middle-school students across three provinces, capturing diverse socio-economic contexts and grade levels (7th, 8th, and 9th). EFA on the first dataset (n = 424) revealed a nine-factor structure collectively explaining 78.12% of the total variance. Confirmatory factor analysis (CFA) on the second dataset (n = 584) verified an excellent model fit. Internal consistency indices (Cronbach’s α > 0.87, composite reliability > 0.75) and strong convergent and discriminant validity evidence (based on AVE and inter-factor correlations) further support the scale’s psychometric soundness. The SCE-PL thus offers researchers, policymakers, and practitioners a robust, theory-driven instrument for assessing personalized learning experiences in smart classroom environments, paving the way for data-informed pedagogy, optimized learning spaces, and enhanced technological integration.