AI-enhanced English writing instruction for engineering students: A framework centering pedagogical relevance and knowledge acquisition

This case study employs the AIKRA (AI-Integrated Knowledge and Relevance in Academic Writing) Framework to investigate AI-infused writing education in engineering students of three Chennai colleges. This case study tackles issues of avoiding cognitive disengagement, over-reliance on technology, separating skill acquisition from AI-assisted delivery. The results indicate that all explicit transparency procedures, high support to minimal support phased scaffolds in a topic-related and context-related way in education through a high degree of adaptation to various levels of proficiency and multilingual environments are required in AI-assisted education. The results on problematic cases illustrated over-reliance on technologies with superior capabilities and high-performing cases illustrated metacognition and self-authoring capabilities. This study contends that AIKRA frameworks make sure that AI-assisted education does not dislodge traditional education but aids in skill development rather than improving performativity in multilingual engineering education. It shows that AI-assisted education is not dependent on technical know-how but on education know-how.

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Publication Details

Journal
Social Sciences & Humanities Open
Published
2026-11-06
DOI
https://doi.org/10.1016/j.ssaho.2026.103980
Primary Topic
Artificial Intelligence in Education
Type
article
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article

AI-enhanced English writing instruction for engineering students: A framework centering pedagogical relevance and knowledge acquisition

K. Savitha, M Ramesh, Ramesh Pettela, PREMKUMAR J et al.
4 links
Social Sciences & Humanities Open
Artificial Intelligence in Education
article

AI-enhanced English writing instruction for engineering students: A framework centering pedagogical relevance and knowledge acquisition

K. Savitha, M Ramesh, Ramesh Pettela, PREMKUMAR J, Arun G
article en

Abstract

This case study employs the AIKRA (AI-Integrated Knowledge and Relevance in Academic Writing) Framework to investigate AI-infused writing education in engineering students of three Chennai colleges. This case study tackles issues of avoiding cognitive disengagement, over-reliance on technology, separating skill acquisition from AI-assisted delivery. The results indicate that all explicit transparency procedures, high support to minimal support phased scaffolds in a topic-related and context-related way in education through a high degree of adaptation to various levels of proficiency and multilingual environments are required in AI-assisted education. The results on problematic cases illustrated over-reliance on technologies with superior capabilities and high-performing cases illustrated metacognition and self-authoring capabilities. This study contends that AIKRA frameworks make sure that AI-assisted education does not dislodge traditional education but aids in skill development rather than improving performativity in multilingual engineering education. It shows that AI-assisted education is not dependent on technical know-how but on education know-how.

Social Sciences & Humanities OpenVol. 14
Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN), St. Joseph’s College of Engineering (IN), Aditya University (IN), Sri Ramakrishna Engineering College (IN)
Quality education
Openalex Percentile: Top 79%
Artificial Intelligence in Education
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AI-enhanced English writing instruction for engineering students: A framework centering pedagogical relevance and knowledge acquisition — K. Savitha, M Ramesh, et al. · Social Sciences & Humanities Open (2026) | TGRS Research Map | TGRS