Research Article

The use of AI tools in English academic writing by Saudi undergraduates

Burhan Ozfidan 1 2 , Dina Abdel Salam El-Dakhs 2 * , Lama Adel Alsalim 2
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1 Florida Gulf Coast University, Fort Myers, FL, USA2 Prince Sultan University, Riyadh, SAUDI ARABIA* Corresponding Author
Contemporary Educational Technology, 16(4), October 2024, ep527, https://doi.org/10.30935/cedtech/15013
Published Online: 31 August 2024, Published: 01 October 2024
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ABSTRACT

This study explores Saudi undergraduate students’ perceptions of artificial intelligence (AI) tools in academic writing. Despite extensive research on AI in higher education, there is limited focus on academic writing, especially in the Saudi context. A survey of 189 students, proficient in English and enrolled in freshmen academic writing courses, was conducted. The students frequently used ChatGPT, Grammarly, and Google Translate. Exploratory factor analysis identified two factors: “instructional support of AI tools” and “instructional practices of AI tools,” explaining 55.302% of the variance. Descriptive analysis revealed strong student agreement on AI tools’ benefits, including idea generation, outline preparation, grammar and spell-check improvements, and time-saving. However, concerns about reliability, contextual accuracy, and ethical implications were noted. The study indicates the need for proper training and clear guidelines to make the most of AI in academic writing. The participants, in various responses, indicated how AI helps develop their writing accuracy and come up with new ideas although some participants worry about relying too much on technology. The study recommends that AI tools can be very helpful, but we need to use them thoughtfully to cater to different student experiences and concerns.
Keywords: AI tools, academic writing, undergraduate students

CITATION (APA)

Ozfidan, B., El-Dakhs, D. A. S., & Alsalim, L. A. (2024). The use of AI tools in English academic writing by Saudi undergraduates. Contemporary Educational Technology, 16(4), ep527. https://doi.org/10.30935/cedtech/15013

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