Understanding the impact of self-regulation on perceived learning outcomes based on social cognitive theory.

CROSS-sectional method; MATHEMATICAL variables; SCALE analysis (Psychology); STATISTICAL models; STATISTICAL correlation; CRONBACH'S alpha; MINDFULNESS; QUESTIONNAIRES; SELF-control; EVALUATION of medical care; DESCRIPTIVE statistics; SOCIAL learning theory; EMAIL; SURVEYS; ONLINE education; RESEARCH; LEARNING strategies; PATIENT monitoring; HEALTH outcome assessment; RELIABILITY (Personality trait)

This study aims to understand how self-regulation can improve perceived e-learning outcomes. We build on social cognitive theory to explore the antecedents and consequences of self-regulation. Self-regulation is captured as IT mindfulness and self-regulated learning. The proposed hypotheses are largely supported, showing that self-regulated learning affects perceived e-learning outcomes and is influenced by IT mindfulness and its antecedents, in terms of individual and contextual factors. This study collected questionnaire data from an e-learning system of university (i.e. Zuvio). This system provides both learning and social interaction features. This study provides a systematic analysis of self-regulation, which integrates social cognitive theory and the monitoring and controlling aspect to analyse how e-learners improve outcomes through self-regulation. [ABSTRACT FROM AUTHOR]

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