Academic integrity in the age of Artificial Intelligence (AI) authoring apps
Open accessAbstract
What does it mean to write, learn to write, and teach writing in an age when students can use the latest artificial intelligence (AI) co‐authoring tools to produce entire essays without even adding an original idea or composing a single sentence? This article addresses questions of authorship and academic integrity concerning the use of AI writing assistants and the latest GPT‐3 (Generative Pre‐trained Transformer, Version 3) tools. It begins by problematizing the use of these tools, and then illustrates how students can use these tools to paraphrase, summarize, extend, and even create original texts with minimal original input, raising questions about authorship and academic integrity. The author argues that as these tools become more widespread, teachers must find creative ways to integrate them into the teaching and learning process and offer practical suggestions for classroom practice. The author hopes to raise awareness about threats to academic integrity brought about by the use of the latest AI co‐authoring tools and aims to equip teachers with strategies to embrace the use of these new digital technologies in the teaching of writing.
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Inconsistently practiced policies in uncertain learning environments foster doubts about fairness and have an unequal effect on already vulnerable student populations.
“Inconsistently practiced policies in uncertain learning environments tend to foster doubts about fairness and have an unequal effect on already vulnerable student populations [9].”
From Evaluating the Effectiveness and Ethical Implications of AI Detection Tools in Higher Education (2025) · cites this paper as [9]
Section 3, “Academic Integrity and ‘Authorship’” (page not specified), says AI-assisted assignments can put the fairness of assessment at risk. Section 3.1.2 also notes that students may struggle to distinguish ethical from unethical uses of AI tools. Neither passage links fairness concerns to inconsistently practiced policies or says vulnerable student populations are affected unequally. (LLM, conf=0.83)
Experimental — accuracy not yet measuredStudents tend to be bewildered or inconsistently informed about acceptable usage of AI tools.
“Students tend to be bewildered or inconsistently informed about the acceptable usage of such tools.”
From Evaluating the Effectiveness and Ethical Implications of AI Detection Tools in Higher Education (2025) · cites this paper as [9]
Section 3.1.2 (For assessment; page not given) warns that students may be unable to distinguish when using AI-authoring tools is ethical during learning versus summative assessment. This supports possible confusion about acceptable use, but does not establish that students generally are bewildered or receive inconsistent information. (LLM, conf=0.84)
Experimental — accuracy not yet measuredStudents with access to premium AI tools that can rephrase or humanize content can easily bypass detection systems, putting less-resourced students at a disadvantage.
“Students with access to premium AI tools that can rephrase or “humanize” content can easily bypass detection systems, putting less-resourced students at a disadvantage [9].”
From Evaluating the Effectiveness and Ethical Implications of AI Detection Tools in Higher Education (2025) · cites this paper as [9]
Section 2.1 (Wordtune; page not provided) says the paid version can rewrite whole paragraphs and has no daily rewrite limit, unlike the free version. Section 2.2 (Jenni; page not provided) describes a plagiarism check, but says its functions are available in both free and paid versions. The paper does not establish that premium tools easily bypass detection systems or that less-resourced students are disadvantaged as a result. (LLM, conf=0.86)
Experimental — accuracy not yet measuredBy integrating these elements, higher education can uphold its core mission of advancing meaningful learning while safeguarding academic integrity.
“By integrating these elements, higher education can uphold its core mission of advancing meaningful learning while safeguarding academic integrity [9].”
From Evaluating the Effectiveness and Ethical Implications of AI Detection Tools in Higher Education (2025) · cites this paper as [9]
Section 3.1.2 recommends assessment that emphasizes learning while distinguishing ethical AI use from submitting AI-generated assignments. The Conclusion advocates teaching learners to use AI ethically to achieve learning goals. These passages support the proposed balance, but the paper focuses on writing and language teaching rather than establishing the broader claim about higher education’s core mission. (LLM, conf=0.78)
Experimental — accuracy not yet measuredTeaching students to use these tools for tasks such as brainstorming or editing while maintaining originality can enhance digital literacy and promote inclusivity.
“Teaching students to use these tools for tasks such as brainstorming or editing while maintaining originality can enhance digital literacy and promote inclusivity [9].”
From Evaluating the Effectiveness and Ethical Implications of AI Detection Tools in Higher Education (2025) · cites this paper as [9]
Section 3.1.1 recommends teaching students to revise writing with AI tools, and the Conclusion urges teachers to show learners how to use AI authoring ethically. The paper discusses originality and authorship, but the cited passages do not establish that this instruction enhances digital literacy or promotes inclusivity. (LLM, conf=0.85)
Experimental — accuracy not yet measured
This finding suggests a conceptual murkiness among the students.
“This finding suggests a conceptual murkiness among the students, one that echoes the findings of Yeo (2023).”
From Student Perceptions of AI-Assisted Writing and Academic Integrity: Ethical Concerns, Academic Misconduct, and Use of Generative AI in Higher Education (2025) · cites this paper as Yeo (2023)
In §3.1.2 (page unavailable), Yeo warns that students may not distinguish between ethical and unethical uses of AI authoring tools, which supports the idea of conceptual murkiness. But the passage presents this as a possible danger, not an observed finding about students. (LLM, conf=0.84)
Experimental — accuracy not yet measuredScholars have suggested the process-based approach to assessments to mitigate AI-related misconduct.
“Scholars have also suggested the process-based approach to assessments to mitigate AI-related misconduct (Yeo, 2023).”
From Artificial Intelligence for Academic Purposes (AIAP): Integrating AI literacy into an EAP module (2025) · cites this paper as Yeo, 2023
Broader use of AI co-writing tools puts at risk perceived notions of authorship and intellectual integrity.
“Broader use of AI co-writing tools, which enable students to author complete essays while contributing minimally, puts at risk perceived notions of authorship and intellectual integrity [9].”
From Evaluating the Effectiveness and Ethical Implications of AI Detection Tools in Higher Education (2025) · cites this paper as [9]
Students may struggle to discern when using AI authoring tools is appropriate, indicating a lack of clarity around ethical usage at different stages of the learning process.
“Students may struggle to discern when using AI authoring tools is appropriate, indicating a lack of clarity around ethical usage at different stages of the learning process [9].”
From Evaluating the Effectiveness and Ethical Implications of AI Detection Tools in Higher Education (2025) · cites this paper as [9]
Educators are forced to look at alternative methods of assessment that value critical thinking, originality, and process more highly than highly polished products.
“Educators thus find themselves forced to look at alternative methods of assessment that value critical thinking, originality, and process more highly than highly polished products [9].”
From Evaluating the Effectiveness and Ethical Implications of AI Detection Tools in Higher Education (2025) · cites this paper as [9]
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Evaluating AI-Enhanced Collaboration in EFL Academic Writing: A Longitudinal Mixed-Methods Study
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Educational Chatbots: A Systematic Mapping Study
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University Instructors’ Reactions and Adjustments to Generative Artificial Intelligence
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Usage of ChatGPT on English Language Skills of Students at Maputi Senior High School
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The Integration of Artificial Intelligence Into Saudi Educational Settings
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- Authors
- Yeo, M. A.
- Affiliations
- SEAMEO Regional Language Centre (SG)
- Corresponding author
- Yeo, Marie Alina
- ORCID
- Yeo, Marie Alina
- Venue
- TESOL Journal
- Publisher
- Wiley
- Published
- 2023-03-27
- Volume
- 14
- Issue
- 3
- ISSN
- 1056-7941 (ISSN-L)
- 1949-3533
- OpenAlex
- W4360989442
- Semantic Scholar
- 0b0230fbb32ee3b81eb8d56c83a683b2eb03b6ec
- Cited by
- 142
- References
- 29
- Citations by year
- 2026: 49 · 2025: 41 · 2024: 39 · 2023: 13
- FWCI
- 35.53
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- TESOL Journal (publishedVersion)
- Topics
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Discourse Analysis in Language Studies
- Keywords
- academic integrity, generative AI, GPT-3, authorship, writing instruction, AI writing tools, classroom technology integration, student originality
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