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January 14, 2026The Korean Association of General Education0 citationsOpen Access

A Comparative Study of Generative AI and Human Texts: Limits and Possibilities of Academic Writing

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JPJong Hyang ParkEKEun Young Kim

Key Points

  • This research aims to compare the impact of generative AI on students' academic writing.
  • Collected 69 term papers from two cohorts (2021 without AI, 2025 with AI).
  • Employed text-mining techniques to analyze sentence length, lexical diversity, conjunction use, and sentiment scores.
  • Conducted qualitative reviews of writing style and reference practices by the course instructor.
  • AI-assisted papers were shorter and had lower lexical diversity than non-AI papers.
  • Conjunction use was similar, though AI writing relied more on emphatic connectors.
  • Instructor feedback noted AI writing's uniformity and occasional fabrication of references.

Abstract

This study examines how the use of generative AI tools influences the content and style of university students’ writing and explores its educational implications. Despite the rapid spread of generative AI such as ChatGPT in higher education, empirical comparisons of its actual impact on student writing remain limited. To address this gap, 69 term papers were collected from the liberal arts course the ‘Philosophy of Life and Ecology in the 21st Century’ at D. University in Seoul, covering two cohorts: 2021 (without AI) and 2025 (with AI). A mixed-methods approach was adopted: text-mining techniques were employed to quantitatively compare sentence length, lexical diversity (TTR, MATTR), conjunction use, and sentiment scores, while the course instructor qualitatively reviewed rhetorical features, writing style, and reference practices.The analysis showed that AI-assisted papers were shorter and more concise, with lower lexical diversity than those written without AI. While overall conjunction frequency and variety revealed no significant difference, AI-assisted writing tended to rely more on illustrative and emphatic connectors rather than conditional ones. Sentiment scores were largely similar across both groups; however, from the instructor’s perspective, AI-assisted writing often reflected uniformity of thought and style, sometimes including fabricated references, which revealed the issue of AI hallucination. At the same time, a few students demonstrated critical engagement by explicitly reporting how and why they used AI tools.These findings suggest that prohibiting AI use in academic writing is insufficient. Instead, pedagogical design and assessment criteria should guide students to employ AI critically and creatively while ensuring fact-checking and personal interpretation. This study offers empirical evidence on the opportunities and challenges of AI-assisted writing, providing a foundation for balanced discussions in higher education.

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Cite This Study

Park et al. (2025) studied this question.

synapsesocial.com/papers/6966e74713bf7a6f02bfff48https://doi.org/10.46392/kjge.2025.19.6.71
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Also Consider

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  1. 1Artificial Intelligence and Academic Writing: A Case Study of STEM Undergraduates2025 · 1 citations
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  4. 4Exploring the boundaries of authorship: a comparative analysis of AI-generated text and human academic writing in English literature2024 · 91 citations
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