The Use of Artificial Intelligence Tools in English Academic Writing among University Students: A Scoping Review
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| Title: | The Use of Artificial Intelligence Tools in English Academic Writing among University Students: A Scoping Review |
|---|---|
| Language: | English |
| Authors: | Zhou Bo (ORCID |
| Source: | Language Teaching Research Quarterly. 2025 53:95-114. |
| Availability: | European Knowledge Development (EUROKD). e-mail: editorial@eurokd.com; Web site: https://www.eurokd.com/journal/jd/1 |
| Peer Reviewed: | Y |
| Page Count: | 20 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Information Analyses |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Artificial Intelligence, Technology Uses in Education, English (Second Language), Academic Language, Writing (Composition), College Students, Writing Skills, Writing Instruction, Higher Education, Educational Research, Research Methodology, Affective Behavior, Student Motivation, Cognitive Processes, Metacognition, Feedback (Response), Pedagogical Content Knowledge, Technological Literacy |
| ISSN: | 2667-6753 |
| Abstract: | As artificial intelligence (AI) use in English academic writing instruction has increased, this scoping review reviews empirical studies in higher education. However, the studies differ in theory use and teaching practice. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) protocol and the Population-Concept-Context (PCC) framework, a systematic Web of Science (WoS) Core Collection search yielded 20 eligible peer-reviewed studies published post-2020. Most studies were carried out in English as a Foreign Language (EFL) contexts, aiming to improve writing performance and learner motivation via AI-assisted tools. Common platforms encompass automated writing assessment systems. Theoretical frameworks were frequently limited to self-efficacy and scaffolding, with scant consideration for cognitive load, sociocultural adaptation, or ethical governance. Methodologically, most studies relied on short-term experimental designs, lacking longitudinal or classroom-based rigor. Future research should employ mixed-methods and longitudinal designs, include diverse learner demographics, and prioritize teacher preparation and ethical AI literacy to guarantee sustainable and equitable implementation. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1494864 |
| Database: | ERIC |
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