Enhancing Academic Writing in a Linguistics Course with Generative AI: An Empirical Study in a Higher Education Institution in Hong Kong

The advent of generative artificial intelligence (AI) has transformed information acquisition and utilization in higher education academic writing. This study fills the empirical research gap by examining how university students use generative AI tools for digital academic writing. The study investigates the experiences of 140 undergraduates enrolled in an ‘Introduction to Linguistics’ course at a university in Hong Kong employing generative AI applications, such as ChatGPT3.5 and the AI Image Generation feature in Padlet, for a collaborative multimedia Wikibook project spanning 13 weeks. The mixed-method approach included analyzing AI-generated content integration within 29 multimedia-enhanced Wikibook chapters, development logs with ChatGPT interactions, the assimilation of AI-generated content into drafts, and collaborative composition dynamics. Additionally, a survey with 98 student responses assessed perceptions regarding AI efficacy in academic writing support. Key findings reveal the multifaceted role of ChatGPT in shaping discourse, offering linguistic tools, and structuring information. The students recognized the advantages of leveraging AI tools, rapidly acclimating to their strengths and limitations through practical engagement. The outcomes of this research offer insights into students’ effective utilization of AI-generated content and suggest potential directions for incorporating generative AI tools into academic writing pedagogy.

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Publication Details

Journal
Education Sciences
Published
2024-12-04
DOI
https://doi.org/10.3390/educsci14121329
Citations
19
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
2.29
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article

Enhancing Academic Writing in a Linguistics Course with Generative AI: An Empirical Study in a Higher Education Institution in Hong Kong

Lixun Wang, Boyuan Ren
19 citations
Education Sciences
Artificial Intelligence in Healthcare and Education
2.29
article

Enhancing Academic Writing in a Linguistics Course with Generative AI: An Empirical Study in a Higher Education Institution in Hong Kong

Lixun Wang, Boyuan Ren
article en
19 citations

Abstract

The advent of generative artificial intelligence (AI) has transformed information acquisition and utilization in higher education academic writing. This study fills the empirical research gap by examining how university students use generative AI tools for digital academic writing. The study investigates the experiences of 140 undergraduates enrolled in an ‘Introduction to Linguistics’ course at a university in Hong Kong employing generative AI applications, such as ChatGPT3.5 and the AI Image Generation feature in Padlet, for a collaborative multimedia Wikibook project spanning 13 weeks. The mixed-method approach included analyzing AI-generated content integration within 29 multimedia-enhanced Wikibook chapters, development logs with ChatGPT interactions, the assimilation of AI-generated content into drafts, and collaborative composition dynamics. Additionally, a survey with 98 student responses assessed perceptions regarding AI efficacy in academic writing support. Key findings reveal the multifaceted role of ChatGPT in shaping discourse, offering linguistic tools, and structuring information. The students recognized the advantages of leveraging AI tools, rapidly acclimating to their strengths and limitations through practical engagement. The outcomes of this research offer insights into students’ effective utilization of AI-generated content and suggest potential directions for incorporating generative AI tools into academic writing pedagogy.

Education SciencesVol. 14(12)
Education University of Hong Kong (HK)
Quality Education
Openalex Percentile: Top 11%
Artificial Intelligence in Healthcare and Education
2.29
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Enhancing Academic Writing in a Linguistics Course with Generative AI: An Empirical Study in a Higher Education Institution in Hong Kong — Lixun Wang, Boyuan Ren · Education Sciences (2024) | TGRS Research Map | TGRS