How does AI-based Canva enhance cooperative literacy learning? Insight from a CIRC-based PLS-SEM model
DOI:
https://doi.org/10.60923/issn.1970-2221/24719Keywords:
AI assisted learning, Cooperative Integrated Reading and Composition (CIRC), reading skills, self-regulated learning, writing skillsAbstract
The integration of artificial intelligence (AI) into collaborative learning offers new opportunities to enhance literacy education in higher education. However, empirical evidence regarding the role of AI-based tools in supporting collaborative literacy learning remains limited. This study investigates the effect of AI-Based Canva on the effectiveness of the Cooperative Integrated Reading and Composition (CIRC) model. A quantitative explanatory design was employed, involving 243 undergraduate students from Indonesian Language and Literature Education programs across Indonesia. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that AI-Based Canva significantly improves the effectiveness of the CIRC model (β = 0.802, p < 0.001). Self-regulated learning, reading skills, writing skills, and social skills were also found to significantly predict students’ use of AI-Based Canva. The findings highlight AI-Based Canva as a key technological mediator that enhances collaborative literacy learning and supports student autonomy and engagement.
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