EVALUATING THE IMPACT OF THE AI “WORD-BOT” ON TERTIARY - LEVEL ENGLISH VOCABULARY LEARNING

Abstract

This study investigates the role of AI-based “Word-Bot” chatbot in enhancing the English Vocabulary of undergraduate students. It is underpinned by Nation’s (2001) Vocabulary Learning Theory, which advocates for balanced approaches involving meaning-focused inputs and output along with form-focused instruction, and Siemens’ (2005) Connectivism Theory, which emphasizes the importance of digital networks and technologies in a modern learning environment. The study employed a mixed-methods design. The study used a pretest and a posttest to measure vocabulary gains and found a statistically significant improvement (M = 20.50 to M = 24.21, p = .035), with a small to moderate effect size (Cohen’s d = 0.38), suggesting that the Word-Bot contributed positively to learners’ vocabulary development. Qualitative findings through thematic analysis revealed that students perceived the Word-Bot as engaging, contextually supportive, and useful in building confidence and vocabulary retention. However, limitations include a small sample size (35 chemical engineering students), short duration, and lack of a control group, which restricts the generalizability of the findings. Future research should adopt longitudinal approaches with diverse participants and include controlled conditions to better assess the integration of AI tools in language instruction. The study has pedagogical value by demonstrating how AI-driven platforms can complement traditional vocabulary learning and support personalized, tech-enhanced education.