Learner Readiness for Personalized Learning in Higher Education: A Scoping Review of Conceptualizations and Measurement Approaches

Personalized learning is increasingly supported by artificial intelligence, learning analytics, adaptive learning systems, and other digital technologies in higher education. However, the effectiveness of personalized learning also depends on whether learners are prepared to manage, regulate, and sustain their learning. This scoping review examined how personalized learning readiness (PLR) has been conceptualized and measured in higher education. Searches were conducted in Scopus, Web of Science Core Collection, China National Knowledge Infrastructure (CNKI), and ERIC. After deduplication, 601 unique records were screened, and 24 studies published between 2017 and 2026 were included. Only two studies directly examined PLR, while the remaining 22 provided contextual evidence through related constructs such as digital and technological readiness, digital competence, self-directed learning, self-regulated learning, learning autonomy, learning preferences, technology acceptance, and trust. Existing measurement approaches were grouped into four broad types: direct PLR assessment, adaptation of related readiness measures, indirect assessment through learner-process constructs, and behavioral or outcome indicators. No common PLR definition or measurement instrument was repeatedly used across the included studies. Based on the evidence, PLR is best understood as learners’ psychological and behavioral readiness to manage their learning, make learning decisions, and sustain participation in personalized learning. Future research should develop and validate PLR-specific measures and examine their predictive value across longitudinal and cross-cultural contexts.

personalized learning readiness, higher education, personalized learning, learner readiness, scoping review

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