Fostering collaborative learning in ESP: AI-driven approaches integrating learning styles and multiple intelligences
The growing demand for English for Specific Purposes (ESP) calls for innovative learning methodologies that address diverse cognitive profiles. However, traditional ESP education often overlooks individual learning styles and multiple intelligences. This study explores how AI can enhance collaborative ESP learning by accommodating varied learning preferences, asking: How can AI improve collaborative ESP training by adapting to diverse learning styles and intelligences? A mixed-methods experimental design involved 100 university students from Engineering, Medicine, and Business, divided into experimental and control groups. The experimental group received AI-supported collaborative ESP training tailored to their learning styles and intelligences, while the control group followed conventional methods. Results showed the experimental group demonstrated significantly higher motivation, engagement, learning outcomes, and improved communication and collaboration skills. These findings suggest that integrating AI with cognitive-based learning models enhances collaborative ESP environments through adaptive content delivery, dynamic grouping, and personalized feedback, fostering more inclusive and effective professional language learning.
Authors
- Luís Cardoso
- Andi Asrifan (ORCID: https://orcid.org/0000-0002-9934-6129)
- K. J. Vargheese (ORCID: https://orcid.org/0000-0002-5755-3808)
Publication Details
- Journal
- Englisia Journal of language education and humanities
- Published
- 2025-05-07
- DOI
- https://doi.org/10.22373/ej.v12i2.29330
- Primary Topic
- Learning Styles and Cognitive Differences
- Type
- article
- Field-Weighted Citation Impact
- 0.00