AI in Graduation Project Writing: Analyzing Lexical Patterns to Measure Chat GPT's Impact in Technical Institutes

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Asmaah Salim Salim Aejaal
Ziaulhaq Dhau E. obeid

Abstract

This study investigates the use of Artificial Intelligence (AI) in graduation project writing within technical institutes, addressing a significant gap in existing research. It examines the frequency and contextual usage of specific lexical items in 60 graduation projects across engineering, information technology, and applied sciences disciplines, aiming to identify patterns indicative of AI-generated content. Employing a systematic comparison of projects submitted before and after the release of ChatGPT (November 30, 2022), the research tracks targeted lexical items. Findings reveal a dramatic increase in AI-associated vocabulary, with the AI index average rising from 6 (pre-ChatGPT) to 25 (post-ChatGPT). Notable increases include "underscore/underscoring" (2200%) and "navigate/navigating" (1900%). The study concludes that while AI tools can enhance technical writing quality and reduce plagiarism, they also lead to homogenized writing styles and raise concerns about academic integrity and practical skill development in technical education.

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How to Cite
Asmaah Salim Salim Aejaal, & Ziaulhaq Dhau E. obeid. (2024). AI in Graduation Project Writing: Analyzing Lexical Patterns to Measure Chat GPT’s Impact in Technical Institutes. Surman Journal of Science and Technology, 6(2), 595–600. Retrieved from https://sjst.scst.edu.ly/index.php/sjst/article/view/216
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Science and Technology