The Effectiveness of AI-Based Vocabulary Learning Platforms in Enhancing Academic Lexical Competence of University Students in AJK, Pakistan

Abstract

This paper has discussed how an artificial intelligence-based vocabulary learning tool can effectively improve academic lexical competence of Pakistani university students at the University of Poonch, Azad Jammu and Kashmir (AJK). Quasi experimental pretest post-test control group design was used. To conduct this study, two groups control and experimental groups were formed for undergraduate students. Experimental who were taught using an AI-based vocabulary learning system and control who were taught using the traditional vocabulary instruction. The Academic Vocabulary Test (AVT) and the Productive Academic Vocabulary Test (PAVT) were used to determine academic lexical competence in terms of receptive and productive vocabulary knowledge. The analysis showed that there was greater improvement in both receptive and productive academic vocabulary in the experimental group as compared to the control group. The findings point to the idea that AI-driven vocabulary learning platforms yield successful assistance in vocabulary development based on the adaptable practice, contextualized learning, and instant feedback. The paper concludes that AI-based learning tools can be used in the field of upper secondary language teaching and learning and allow students to achieve better academic lexical competence as well as better vocabulary acquisition methods.

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