International Journal of Academic Research in Business and Social Sciences

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Impact of Data Mining Techniques and Self-Regulated Learning (SRL) in Predicting TVET Student Performance: A Review

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Educational Data Mining (EDM) and Self-Regulated Learning (SRL) show promise in predicting student success in TVET programs. This review evaluates literature from 2010-2023 using 45 studies via the PRISMA approach. Integrating EDM with SRL enhances TVET performance using classification algorithms and personalised interventions. Critical interventions include adaptive feedback, customised learning plans, and resource suggestions to aid struggling students, focusing on formative assessment. Students reflect after milestones to adjust study strategies, while teachers use real-time data for guidance. An effective feedback loop refines predictions and interventions. Findings influence TVET policy, emphasising data-driven methods to boost student autonomy.
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