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Generative Artificial Intelligence (GenAI) for Academic Writing in Higher Education: A Scoping Review of Applications, Challenges, and Implications

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Title: Generative Artificial Intelligence (GenAI) for Academic Writing in Higher Education: A Scoping Review of Applications, Challenges, and Implications
Language: English
Authors: Renz Alvin E. Gabay (ORCID 0000-0002-8108-4589), Aaron A. Funa (ORCID 0000-0002-6648-8825), Jhonner D. Ricafort (ORCID 0000-0001-8980-6681)
Source: International Journal of Education in Mathematics, Science and Technology. 2026 14(1):200-232.
Availability: International Journal of Education in Mathematics, Science and Technology. Necmettin Erbakan University, Ahmet Kelesoglu Education Faculty, Meram, Konya, 42090, Turkey. e-mail: ijermst@gmail.com; Web site: https://www.ijemst.net/index.php/ijemst/index
Peer Reviewed: Y
Page Count: 33
Publication Date: 2026
Document Type: Journal Articles
Information Analyses
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Academic Language, Higher Education, Barriers, Technology Uses in Education, Educational Research, Writing (Composition), Opportunities, Ethics, Risk
ISSN: 2147-611X
Abstract: Generative artificial intelligence (GenAI) is reshaping academic writing in higher education faster than institutions can develop evidence-informed guidance, leaving practice ahead of proof. To clarify what is happening and where benefits and risks cluster, the researchers conducted a scoping review structured by a Population-Concept-Context (PCC) frame and aligned with PRISMA-ScR procedures. Peer-reviewed, English-language empirical studies published from 2024 through Q2 2025 in higher-education settings were included, and findings were synthesized via convergent integration that juxtaposed quantitative distributions with qualitative themes. A total of 25 studies met criteria. Across populations and contexts, GenAI was most often positioned as assistive scaffolding across the planning-to-revision span of writing; reported benefits concentrated on organization, fluency, efficiency, and language support (notably for multilingual writers). Recurrent risks included hallucinations and unreliable or fabricated citations, inconsistent disclosure or attribution, and overreliance when use was unscaffolded; the limited reliability of AI-detection tools complicated integrity judgments. Context shaped practice: clearer policies and better access supported more constructive use, while the evidence base skews toward English-medium, well-resourced institutions and relies heavily on short-term or proxy outcomes. By integrating counts and themes within a PCC frame, this review offers an up-to-date evidence map that distinguishes where benefits reliably cluster (process-level supports) and where risks persist (source work and attribution), while surfacing salient gaps (faculty/postgraduate cohorts and Global South contexts). Overall, the pattern supports an assistive, not substitutive stance in which GenAI complements--rather than replaces--human judgment in argument construction, source interrogation, and synthesis.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1494380
Database: ERIC
FullText Text:
  Availability: 0
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  Data: Generative Artificial Intelligence (GenAI) for Academic Writing in Higher Education: A Scoping Review of Applications, Challenges, and Implications
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  Data: <searchLink fieldCode="AR" term="%22Renz+Alvin+E%2E+Gabay%22">Renz Alvin E. Gabay</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-8108-4589">0000-0002-8108-4589</externalLink>)<br /><searchLink fieldCode="AR" term="%22Aaron+A%2E+Funa%22">Aaron A. Funa</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-6648-8825">0000-0002-6648-8825</externalLink>)<br /><searchLink fieldCode="AR" term="%22Jhonner+D%2E+Ricafort%22">Jhonner D. Ricafort</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-8980-6681">0000-0001-8980-6681</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22International+Journal+of+Education+in+Mathematics%2C+Science+and+Technology%22"><i>International Journal of Education in Mathematics, Science and Technology</i></searchLink>. 2026 14(1):200-232.
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  Data: International Journal of Education in Mathematics, Science and Technology. Necmettin Erbakan University, Ahmet Kelesoglu Education Faculty, Meram, Konya, 42090, Turkey. e-mail: ijermst@gmail.com; Web site: https://www.ijemst.net/index.php/ijemst/index
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  Data: 33
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Generative artificial intelligence (GenAI) is reshaping academic writing in higher education faster than institutions can develop evidence-informed guidance, leaving practice ahead of proof. To clarify what is happening and where benefits and risks cluster, the researchers conducted a scoping review structured by a Population-Concept-Context (PCC) frame and aligned with PRISMA-ScR procedures. Peer-reviewed, English-language empirical studies published from 2024 through Q2 2025 in higher-education settings were included, and findings were synthesized via convergent integration that juxtaposed quantitative distributions with qualitative themes. A total of 25 studies met criteria. Across populations and contexts, GenAI was most often positioned as assistive scaffolding across the planning-to-revision span of writing; reported benefits concentrated on organization, fluency, efficiency, and language support (notably for multilingual writers). Recurrent risks included hallucinations and unreliable or fabricated citations, inconsistent disclosure or attribution, and overreliance when use was unscaffolded; the limited reliability of AI-detection tools complicated integrity judgments. Context shaped practice: clearer policies and better access supported more constructive use, while the evidence base skews toward English-medium, well-resourced institutions and relies heavily on short-term or proxy outcomes. By integrating counts and themes within a PCC frame, this review offers an up-to-date evidence map that distinguishes where benefits reliably cluster (process-level supports) and where risks persist (source work and attribution), while surfacing salient gaps (faculty/postgraduate cohorts and Global South contexts). Overall, the pattern supports an assistive, not substitutive stance in which GenAI complements--rather than replaces--human judgment in argument construction, source interrogation, and synthesis.
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  Data: EJ1494380
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      – Text: English
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        PageCount: 33
        StartPage: 200
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      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Academic Language
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      – SubjectFull: Higher Education
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      – SubjectFull: Technology Uses in Education
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      – SubjectFull: Educational Research
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      – SubjectFull: Writing (Composition)
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