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Cited by 106Artificial Intelligence in EducationEFL/ESL Teaching and LearningEnglish Language Learning and Teaching

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Using generative artificial intelligence/ChatGPT for academic communication: Students' perspectives

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Liu, Yanhua, Park, Jaeuk, McMinn, Sean·2024·International Journal of Applied Linguistics
DOI 10.1111/ijal.12574
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Abstract

Generative artificial intelligence (GenAI) tools such as ChatGPT with their human‐like intelligence and language processing capabilities are significantly impacting the way we live, work, and communicate with each other. While scholars have increasingly focused on the use of GenAI in higher education since its inception, little is known about how key higher education stakeholders, particularly students, perceive its impact on teaching and learning within the context of academic communication, an area central to students' development of transferable skills and literacy competencies yet heavily influenced by the technology. This empirical study addresses the gap by investigating students' experiences and attitudes toward GenAI tools for English academic communication, focusing on their overall perceptions, perceived benefits, limitations, and challenges. Drawing on data from a questionnaire survey with 475 students and interviews with 12 at two universities in China, our findings indicate that students generally view GenAI positively, considering them useful for learning academic communication skills, particularly in writing, grammar, vocabulary, and reading. However, limitations are recognized in terms of giving feedback on critical thinking, creativity, and speaking skills. In addition, information reliability, ethical issues, and impact on assessment and academic integrity also emerged as important concerns. Our study argues that universities should embrace and capitalize on the affordances of GenAI and address its challenges to better support students' learning of critical academic literacy.

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Research works printed but not linked: 5

  1. Biggs J., 2011, EBOOK: Teaching for quality learning at university
  2. Chakraborty U., 2023, Rise of generative AI and ChatGPT: Understand how generative AI and ChatGPT are transforming and reshaping the business world (English Edition)
  3. Chan C. K. Y. &Zhou W.(2023).Deconstructing student perceptions of generative AI (GenAI) through an expectancy value theory (EVT)‐based instrument.arXiv preprint arXiv:2305.01186. · arXiv
  4. Clarizia F., 2018, Lecture notes in computer science: Volume 11161. Cyberspace safety and security, 291
  5. Raman R. Mandal S. Das P. Kaur T. Sanjanasri J. &Nedungadi P.(2023).University students as early adopters of ChatGPT: Innovation diffusion study.https://doi.org/10.21203/rs.3.rs‐2734142/v1 · DOI

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Metadata

Authors
Liu, Y., Park, J., & McMinn, S.
Affiliations
  • The Hong Kong University of Science and Technology (Guangzhou) (CN)
  • Hong Kong University of Science and Technology (HK)
Corresponding author
Park, Jaeuk
ORCID
Venue
International Journal of Applied Linguistics
Publisher
Wiley
Published
2024-06-27
Volume
34
Issue
4
Pages
1437-1461
ISSN
  • 0802-6106 (ISSN-L)
  • 1473-4192
DOI
10.1111/ijal.12574
OpenAlex
W4400137179
Cited by
106
References
47
Citations by year
2026: 56 · 2025: 46 · 2024: 4
FWCI
39.86
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
  • International Journal of Applied Linguistics (publishedVersion)
  • Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
Topics
  • Social Sciences › Education › Artificial Intelligence in Education
  • Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
  • Social Sciences › Education › English Language Learning and Teaching
Keywords
generative AI, ChatGPT, scholarly communication, student perceptions, English academic writing, academic literacy, higher education, AI in teaching and learning, academic integrity, information reliability, AI ethics, assessment, transferable skills

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