AI Literacy and Self-Regulated Learning as Drivers of Academic Readiness
DOI:
https://doi.org/10.5281/zenodo.22952561Keywords:
academic readiness, AI literacy, Artificial intelligence, secondary learners, self-regulated learning, technology-supported learningAbstract
This study investigated how AI literacy and self-regulated learning contributed to the academic readiness of secondary learners in Roxas, Isabela. Using an explanatory-predictive cross-sectional design, data were gathered from 222 Grade 8 learners selected through probability-proportional-to-size systematic sampling. AI literacy, self-regulated learning, and academic readiness were assessed using validated instruments, while Partial Least Squares Structural Equation Modeling, PLSpredict, and importance-performance map analysis were employed to test explanatory and predictive relationships. Results showed moderate levels of AI literacy, self-regulated learning, and academic readiness. Learners demonstrated stronger information-seeking and technology-use behaviors but showed weaker performance in time management, self-evaluation, AI evaluation, and ethical use. Both AI literacy and self-regulated learning significantly predicted academic readiness, with self-regulated learning emerging as the stronger driver. The model explained 56.3% of the variance in academic readiness and demonstrated moderate out-of-sample predictive power. Importance-performance analysis further identified time management and planning, AI evaluation, and ethical judgment as priority areas for learner support. The findings indicate that readiness for technology-supported learning depends not only on familiarity with AI tools but also on learners' capacity to regulate their learning and critically assess AI-generated information. Schools are therefore encouraged to integrate AI literacy development with structured self-regulation activities that strengthen independent, responsible, and reflective learning.
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