Demographic Heterogeneity in the Vocabulary Gains from Generative AI-Supported Task-Based Instruction among Chinese EFL Undergraduates

Authors

  • Peng Liu Fakulti Pendidikan Universiti Kebangsaan Malaysia, Bangi Selangor, 43600, Malaysia
  • Nur Ainil Sulaiman Fakulti Pendidikan Universiti Kebangsaan Malaysia, Bangi Selangor, 43600, Malaysia
  • Wahiza Wahi Fakulti Pendidikan Universiti Kebangsaan Malaysia, Bangi Selangor, 43600, Malaysia

DOI:

https://doi.org/10.70917/ijcisim-2026-1897

Keywords:

Second language acquisition; Vocabulary instruction; Task-based approach; Generative artificial intelligence; Demographics

Abstract

Traditional vocabulary instruction emphasizes the role of the teacher while neglecting the student’s active role in learning. A rote-learning approach to vocabulary instruction prevents students from grasping the basic meanings of words and effective learning strategies, and fails to stimulate their interest in learning. To address these issues, this study draws on second language acquisition theory and the three-phase “pre-task, during-task, post-task” framework of task-based teaching to explore implementation pathways for using Generative Artificial Intelligence (GAI) to enhance English vocabulary instruction for undergraduate students. By leveraging GAI’s capabilities in corpus generation, intelligent dialogue, and real-time assessment, this study enriches teaching materials, creates immersive contexts, and provides personalized feedback. These approaches address the pain points of traditional teaching, enhancing students’ vocabulary, fluency, and logical reasoning, with the aim of providing a theoretical reference for improving the quality and efficiency of English vocabulary instruction in higher education. The results indicate that GAI-enhanced task-based English vocabulary instruction for undergraduates effectively promotes students’ learning motivation, learning strategies, and vocabulary size. Regarding demographic heterogeneity, significant differences were observed between males and females in vocabulary tests (males: 73.18, females: 72.00), as well as in learning motivation and learning strategies, with males demonstrating greater improvement compared to females; Furthermore, significant differences in student motivation were observed across different parental education levels (t = 4.3058, p < 0.01). This disparity stems from the fact that parents with higher educational attainment generally recognize the long-term value of learning English and prioritize the cultivation of comprehensive competencies such as language proficiency and vocabulary acquisition, thereby subtly shaping students’ intrinsic motivation.

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Published

2026-06-28

How to Cite

Liu, P., Sulaiman, N. A., & Wahi, W. (2026). Demographic Heterogeneity in the Vocabulary Gains from Generative AI-Supported Task-Based Instruction among Chinese EFL Undergraduates. International Journal of Computer Information Systems and Industrial Management Applications, 18, 11. https://doi.org/10.70917/ijcisim-2026-1897

Issue

Section

Original Articles