The Effect of AI-Supported Microlearning on the Development of Language Skills
Keywords:
AI-supported microlearning, language skill development, EFL learners, listening, speaking, reading, writing, instructional technology, adaptive learningAbstract
Purpose: The present study aimed to investigate whether AI-supported microlearning significantly improves listening, speaking, reading, and writing skills of intermediate EFL learners compared with conventional language instruction.
Methods and Materials: This study employed a quasi-experimental research design with pre-test and post-test measures. Sixty intermediate Iranian EFL learners enrolled in a private language institute were selected through convenience and purposive sampling and randomly assigned to an experimental group (n = 30) and a control group (n = 30). Both groups followed the same Touchstone 3 curriculum for eight weeks; however, the experimental group received AI-supported microlearning activities in addition to regular instruction, while the control group received traditional instruction only. AI-supported microlearning consisted of short, adaptive digital learning units including listening exercises, pronunciation practice, vocabulary repetition, reading comprehension tasks, micro-speaking activities, and AI-based feedback mechanisms accessible via mobile and computer devices. Standardized pre- and post-tests assessing listening, speaking, reading, and writing skills were administered under controlled conditions. Data were analyzed using descriptive statistics, independent-samples t-tests, normality tests, and effect size calculations to determine the statistical and practical significance of learning gains.
Findings: Inferential analyses revealed no statistically significant differences between the experimental and control groups at the pre-test stage, confirming baseline equivalence across all four language skills. Post-test comparisons demonstrated statistically significant differences favoring the experimental group in listening (p < .05), speaking (p < .01), reading (p < .05), and writing (p < .01). Effect size estimates indicated moderate to large practical impacts of AI-supported microlearning across skills, with particularly strong effects observed in speaking and writing performance. These findings indicate that integrating artificial intelligence with microlearning significantly enhances overall language skill development beyond conventional instruction.
Conclusion: The results demonstrate that AI-supported microlearning constitutes an effective, learner-centered instructional approach capable of improving receptive and productive language skills simultaneously.
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Copyright (c) 2026 Ali Bahremand (Author); Neda Fatehi Rad; Valeh Jalali (Author)
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