AI-Assisted Academic Writing: A Comparative Study of Student-Crafted and ChatGPT-Enhanced Critiques in Ubiquitous Computing

This study examines the impact of Large Language Models (LLMs), such as ChatGPT, on the development of academic critique skills among fourth-year Computer Science undergraduates enrolled in a Ubiquitous Computing course. The research systematically evaluates the differences between student-authored critiques and those revised with the aid of ChatGPT, utilizing established readability metrics such as the Flesch-Kincaid Grade Level, Flesch Reading Ease, and Gunning Fog Index. The findings highlight the potential of AI to enhance readability and analytical depth, while also revealing challenges related to dependency, academic integrity, and algorithmic bias. These results extend implications across learning sciences, pedagogy, and educational technology, providing actionable insights into leveraging AI to augment traditional learning methods and enhance critical thinking and personalized education.