Citation

Seran, Carl Errol and Tan, Myles Joshua Toledo and Abdul Karim, Hezerul and AlDahoul, Nouar A conceptual exploration of generative AI-induced cognitive dissonance and its emergence in university-level academic writing. Frontiers in Artificial Intelligence, 8 (157336). ISSN 2624-8212

Text frai-2-1573368.pdf - Published Version Restricted to Repository staff only Download (342kB)

Abstract

University-level academic writing is a form of scholarly communication that demands precision, clarity, and adherence to established conventions. It is a skill fundamental to science education, best honed through continuous practice (Moskovitz and Kellogg, 2011). However, rising academic demands and evolving educational environments, such as shifts to online learning, introduce new challenges. Students often view writing as a daunting task, largely due to insufficient instruction bridging technical composition and creative expression in their coursework (Stride, 2024). Non-native speakers find this struggle compounded, grappling with the linguistic precision and stylistic conventions of academic writing (Nazaroff, 2011). Furthermore, traditional academic writing has also suffered from an overemphasis on technical correctness at the expense of fostering creative expression. In many cases, the perceived marginal role of writing in research and teaching has led educators to delegate writing instruction solely to language departments (Alley, 2024). Such delegation has resulted in a fragmented approach to teaching writing skills, leaving many students underprepared. In the advent of Generative Artificial Intelligence (GenAI), some students now assume that technology can fully compensate for their underdeveloped writing abilities, inadvertently undervaluing the importance of building a strong writing foundation.

Item Type:	Article
Uncontrolled Keywords:	academic integrity, AI literacy, cognitive dissonance, ethical AI use, generative AI (GenAI), learning behavior, university writing
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28-70 Management. Industrial Management > HD30.2 Electronic data processing. Information technology. Including artificial intelligence and knowledge management
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	28 Jul 2025 04:17
Last Modified:	28 Jul 2025 04:17
URII:	http://shdl.mmu.edu.my/id/eprint/14287

Downloads

Edit (login required)