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ARTIFICIAL INTELLIGENCE AND VOCABULARY DEVELOPMENT: AN EXPERIMENTAL STUDY OF ENGLISH LANGUAGE LEARNERS AT BS-LEVEL
Abstract
Abstract
This experimental study investigates the impact of Artificial Intelligence (AI) tools on the vocabulary development of English language learners at the BS level. The primary objectives were to examine the effectiveness of AI-based vocabulary instruction, compare the performance of students taught with AI tools against those taught through conventional vocabulary learning techniques, and assess learners' attitudes toward the application of AI in vocabulary learning. A quasi-experimental pretest–posttest control group design was employed with 100 BS-level English students divided equally into a control group and an experimental group (n = 50 each). The control group received instruction through traditional methods such as textbook exercises, dictionary use, and teacher-led drills, while the experimental group engaged with AI-powered vocabulary learning tools—ChatGPT, Quizlet AI, and Duolingo Max—featuring adaptive practice, contextual usage, and instant feedback. Data were collected through a vocabulary achievement pretest and posttest, supplemented by a 20-item Likert-scale perception questionnaire administered to the experimental group. Independent- and paired-samples t-tests showed that the experimental group achieved significantly greater gains in vocabulary knowledge than the control group (posttest M = 27.94 vs. M = 21.70, t = 9.64, p < .001), with a very large effect size (Cohen's d = 1.93). Learners also reported markedly positive attitudes toward AI integration, citing engagement, personalization, and ease of access as key benefits (72.0% positive responses overall across the questionnaire). The findings suggest that AI tools can serve as an effective supplement to conventional vocabulary instruction, with implications for curriculum design and technology integration in English language teaching at the tertiary level.
This experimental study investigates the impact of Artificial Intelligence (AI) tools on the vocabulary development of English language learners at the BS level. The primary objectives were to examine the effectiveness of AI-based vocabulary instruction, compare the performance of students taught with AI tools against those taught through conventional vocabulary learning techniques, and assess learners' attitudes toward the application of AI in vocabulary learning. A quasi-experimental pretest–posttest control group design was employed with 100 BS-level English students divided equally into a control group and an experimental group (n = 50 each). The control group received instruction through traditional methods such as textbook exercises, dictionary use, and teacher-led drills, while the experimental group engaged with AI-powered vocabulary learning tools—ChatGPT, Quizlet AI, and Duolingo Max—featuring adaptive practice, contextual usage, and instant feedback. Data were collected through a vocabulary achievement pretest and posttest, supplemented by a 20-item Likert-scale perception questionnaire administered to the experimental group. Independent- and paired-samples t-tests showed that the experimental group achieved significantly greater gains in vocabulary knowledge than the control group (posttest M = 27.94 vs. M = 21.70, t = 9.64, p < .001), with a very large effect size (Cohen's d = 1.93). Learners also reported markedly positive attitudes toward AI integration, citing engagement, personalization, and ease of access as key benefits (72.0% positive responses overall across the questionnaire). The findings suggest that AI tools can serve as an effective supplement to conventional vocabulary instruction, with implications for curriculum design and technology integration in English language teaching at the tertiary level.