Enhancing the emotional aspects of language education through generative artificial intelligence (GenAI): A qualitative investigation

Lucas Mathias Alfred KOHNKE, Benjamin Luke MOORHOUSE

Research output: Contribution to journalArticlespeer-review

Abstract

This qualitative study investigates the impact of generative artificial intelligence (GenAI) on the emotional engagement, motivation and well-being of first-year university students in Hong Kong. We conducted semi-structured interviews with 21 students and three instructors to explore their perceptions of how GenAI influences the affective dimensions of language learning. The data were analyzed using manual coding and inductive thematic analysis to identify key themes. The findings revealed that GenAI generally enhances students’ motivation, reduces anxiety and stress, and fosters an emotionally supportive learning environment. However, challenges related to cultural context and technical issues were also identified. The study highlights the pivotal role of instructors in shaping students’ experiences with GenAI and underscores the need for ongoing support and professional development. It also demonstrates the importance of cultural sensitivity, technological infrastructure and balance. The study is valuable for those who aim to harness GenAI while preserving the irreplaceable human elements of teaching. It contributes to the growing body of knowledge on integrating AI in language learning. Copyright © 2025 The Authors. Published by Elsevier Ltd.

Original languageEnglish
Article number108600
JournalComputers in Human Behavior
Volume167
Early online dateFeb 2025
DOIs
Publication statusE-pub ahead of print - Feb 2025

Citation

Kohnke, L., & Moorhouse, B. L. (2025). Enhancing the emotional aspects of language education through generative artificial intelligence (GenAI): A qualitative investigation. Computers in Human Behavior, 167, Article 108600. https://doi.org/10.1016/j.chb.2025.108600

Keywords

  • GenAI
  • Motivation
  • Emotions
  • Positive psychology

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