Junjie Wei, Yiming Shang
School-reported provision was associated with achievement directly, with no statistical mediation by self-regulation or school climate. Home musical and cultural resources were associated with both outcomes indirectly-through self-regulation and, to a smaller degree, school climate-and for wellbeing the indirect association exceeded the direct one. Self-regulation was the strongest correlate of wellbeing across all methods, though this association is inflated by conceptual overlap with wellbeing and is interpreted with caution.
Generative artificial intelligence (GenAI) can support explanation and feedback while also producing fluent claims that are incomplete, unsupported, or false. Higher-education research increasingly examines how students judge, check, and use such outputs, yet adjacent measures can represent different kinds of critical engagement. This Mini Review distinguishes seven analytically ordered measurement targets: epistemic evaluation, verification initiation, process quality, success, reliance decisions, immediate task performance, and independent learning. Reliance calibration is treated separately as an output-contingent classification of reliance decisions. Targeted Web of Science Core Collection searches (2022-2026) yielded 493 unique records; 10 related reviews and 14 priority empirical studies were examined. The searches were targeted rather than systematic. Among the 14 priority studies, none jointly measured verification success and subsequent reliance calibration against an independently adjudicated reference standard; delayed retention or transfer was also uncommon. We identify boundary conditions including prior knowledge, learner characteristics, task stakes, task verifiability, verification costs, accountability, AI system/configuration, and multidimensional AI literacy. The map is an analytic ordering rather than a validated causal model. Educational interventions should therefore be evaluated for the specific process they target, from verification quality to reliance decisions and learning that persists without AI support.