Students’ Perceptions and Academic Outcomes: The Impact of Meta AI on Vocabulary Learning in Higher Secondary ESL Contexts in Multan

Abstract

In artificial intelligence, students of English vocabulary, particularly learners of English as a Second Language, are learning differently. This paper examined the impact of the Meta AI on vocabulary acquisition among higher secondary learners in Multan, Pakistan. I concentrated on two aspects, one being student academic performance, and the other being what they felt about the use of AI in their lessons. I worked with 120 students using a quasi-experimental mixed-methods design. I split them into two groups. One group was taught vocabulary using Meta AI tools, whereas the other was taught using conventional methods. To monitor progress, I administered pre- and post-tests on vocabulary and employed a questionnaire to obtain students' genuine views. Statistics show that students exposed to Meta AI demonstrated an actual improvement in vocabulary compared to those who attended regular classes. Still, it was not only about scores. Students who were using AI reported being more engaged and motivated. They prefer immediate feedback and believe their learning is more in their control. In short, it is not that Meta AI helped them remember words; they were eager to learn. In accordance with these findings, I will suggest introducing Meta AI into ESL instruction. It not only improves academic performance but also makes students more interested in the entire process.