Evaluating the effectiveness of Telegram chatbots in enhancing vocabulary acquisition among ESL and EFL learners

This research examines the use of LexiBot, a chatbot hosted on Telegram, in supporting vocabulary learning for English as a Second Language (ESL) students at Universiti Teknologi MARA (UiTM) in Malaysia and English as a Foreign Language (EFL) students at Universitas Dinamika (UD) in Indonesia. Adopting a cross-sectional mixed-methods approach, the project enlisted 49 learners who incorporated LexiBot into their regular language exercises. Survey results yielded encouraging quantitative data, showing that 95% of the UiTM cohort and 91% of the UD group found the chatbot user-friendly. Regarding its overall effectiveness, UD students indicated that LexiBot was helpful 81.5% of the time, whereas UiTM respondents noted that it was very helpful 59.1% of the time. In-person interviews offered qualitative insights that revealed contrasting patterns of engagement: UiTM learners interacted with LexiBot independently, while their UD counterparts tended to rely on teacher-guided use. Although participants valued the contextual assistance LexiBot provided, many called for more interactive elements and detailed explanations. These results highlight how sociocultural and pedagogical environments shape interactions with AI tools. The study concluded that chatbots like LexiBot can effectively foster vocabulary growth if their design is flexible and centred on the learner, accommodating varying degrees of learner autonomy and differing instructional contexts. These findings suggest that course developers should incorporate responsive design, game-like elements, and timely feedback tools into their platforms to maintain learners’ attention and encourage their return. Studies that follow users over an extended period are also needed, along with investigations that test the approach across different language skills and in varied classroom or online environments.