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

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
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article

Fostering collaborative learning in ESP: AI-driven approaches integrating learning styles and multiple intelligences

Luís Cardoso, Andi Asrifan, K. J. Vargheese
Englisia Journal of language education and humanities
Learning Styles and Cognitive Differences
article

Fostering collaborative learning in ESP: AI-driven approaches integrating learning styles and multiple intelligences

Luís Cardoso, Andi Asrifan, K. J. Vargheese
article en

Abstract

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.

Englisia Journal of language education and humanitiesVol. 12(2)
Openalex Percentile: Top 90%
Learning Styles and Cognitive Differences
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