The effect of AI-supported collaborative learning on EFL students’ grammar achievement
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Abstract
The current research explores the role of collaborative learning mediated by Artificial Intelligence (AI) technology in enhancing English as a Foreign Language (EFL) grammar achievement at a university level. A quasi-experiment has been carried out at a Cypriot higher education institution where the sample involved 40 undergraduate participants classified as having intermediate proficiency in English. Two intact classes have been selected: one class served as a control group exposed to conventional teacher-centred instruction and another as an experimental one engaged in AI-mediated collaborative learning. The pre-test-post-test design was employed for data collection regarding the change in grammatical proficiency. Data were analysed using the following procedures: paired-samples t-test, independent-samples t-test, and ANCOVA which was performed with the use of IBM SPSS Statistics. It was found that both groups made progress but the improvement made by the latter turned out to be more substantial. There was a significant difference between the pre-test and post-test means which corresponded to a very large effect size, thus, implying great practical significance of results. Cognitive load theory and the notion of entangled cognition have been used for the interpretation of data as the findings reflect how the introduction of AI reduced extraneous cognitive load and promoted deeper engagement via collaboration (Sweller, 1998; Clark & Chalmers, 1998). Learners received immediate personal feedback when co-creating grammatical concepts with the help of AI tools. Thus, it can be concluded that AI-based collaborative learning is a better alternative to grammar instruction.
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