Aug 2026· Review of Artificial Intelligence in Education· Vol 7, pp. e01122· 0 citations· 39 references
TL;DR
Students’ acceptance and rejection of GAI-supported essay editing follow asymmetric configurational logics, showing how different ethical judgments combine to explain academic technology use in a morally ambiguous context.
Abstract
Background: The rapid emergence of generative artificial intelligence (GAI) is having a substantial impact across numerous areas of higher education, including academic writing. Its use as a linguistic assistant occupies an ethically ambiguous position between legitimate academic support and practices that may foster technological dependence or compromise academic integrity.
Objective: Examining the use of GAI among university students in a specific academic scenario: its use as a linguistic assistant to improve the writing quality and clarity of essays previously produced by the student, without substantially altering their content. The objective is to analyze how different ethical judgments shape students’ adoption of this practice, which occupies an intermediate position between legitimate academic support and potential risks of technological dependence or academic fraud.
Methods: The study draws on the Multidimensional Ethics Scale, considering four moral dimensions: justice, relativism, consequentialism, and deontology. It also incorporates sociodemographic and academic variables, including gender, employment status, and perceived academic performance. Methodologically, fuzzy-set qualitative comparative analysis is applied to identify causal configurations associated with both the use and nonuse of GAI.
Results: Acceptance does not depend on a single ethical dimension but on specific combinations of moral judgments. Consequentialism emerges as the most relevant condition in the pathways leading to use and is often combined with favorable perceptions of justice and relativism. In contrast, rejection shows a more fragmented structure and lower explanatory coverage, particularly when unfavorable ethical assessments, especially consequentialist assessments, are combined with sociodemographic factors.
Conclusion: Students’ acceptance and rejection of GAI-supported essay editing follow asymmetric configurational logics, showing how different ethical judgments combine to explain academic technology use in a morally ambiguous context. The findings highlight the need for clear institutional rules, ethical training, and transparent criteria for academic GAI use. Universities should distinguish between acceptable linguistic support and practices that may compromise academic integrity, while helping students develop responsible and reflective uses of GAI.
Generative Artificial Intelligence (GenAI) is profoundly transforming higher education. Although its use can enhance the quality, efficiency, and equity of learning, it also raises ethical dilemmas related to authorship, academic integrity, and technological dependence. Understanding the ethical factors that influence students’ intention to use GenAI is therefore crucial for designing responsible educational policies. This study examines how different ethical frameworks—justice (JUST), relativism (REL), consequentialism (CON), and deontology (DEO)—affect the behavioral intention to use GenAI as an assistant in the editing of academic essays. To this end, the Multidimensional Ethics Scale was applied to a sample of 151 university students enrolled in social science programs in Spain. Data were analyzed using decision tree models, incorporating three control variables: gender, employment status, and academic performance. The results show that ethical perceptions are the main determinants of behavioral intention, whereas gender and individual student circumstances exert only a residual influence. CON emerges as the most influential factor, followed by JUST, while REL and DEO are the least relevant ethical constructs. Overall, the findings indicate that students primarily value the usefulness and fairness of using GenAI.
Unknown authors· The Journal of Interactive L...· 0 citations
The findings suggest that while students possess foundational knowledge and ethical awareness regarding GenAI use, gaps remain in translating awareness into consistently responsible practices, which underscores the need for comprehensive AI literacy programs, explicit institutional guidelines, and ethics-focused educational interventions.
Christianne Mae R. Rivas, Mardie E. Bucjan· International journal of res...· 0 citations
An examination of ethical concerns is necessary for analyzing AI's use in detecting and deterring academic dishonesty in higher education. Although AI-powered systems (incorporating natural language processing, stylometry, and machine learning classifiers) could offer solutions to academic integrity concerns that would scale, such systems are vulnerable to algorithmic bias against non-native English speakers, constrained transparency in algorithmic decision-making, and privacy and academic freedom violations from increased surveillance. A systematic literature review was undertaken of English-language peer-reviewed literature over the period 2012–2024, identified across six databases (Scopus, Web of Science, ERIC, IEEE Xplore, ACM Digital Library, and PhilPapers) and hand-searched reference lists, drawing on theories of AI ethics, procedural justice, epistemic injustice, and critical algorithm studies. Four major themes emerged from the literature review, which included fairness and algorithmic bias, transparency and accountability and due process, student privacy and surveillance and agency, and context-dependent justice in under-resourced settings. No study in the corpus was based in, or focused specifically on, Palestinian higher education; the implications drawn for Palestinian universities are therefore theoretical extrapolations from evidence generated elsewhere, not a synthesis of local empirical findings. All current ethical guidelines were intended for resource-rich western institutions and disregarded the specific context in which universities face resource and digital inequality. Six principles of governance of ethical AI are provided, and an emphasis is placed on how AI is a supplement to human judgment in academia and should therefore be implemented with attention to the specific context.
Walid Salamah· Frontiers in Education· 0 citations
The growing presence of artificial intelligence (AI) in higher education has changed the way students approach academic writing. While AI-powered tools offer practical support in generating ideas, organizing texts, and refining language, their increasing use has also raised concerns about the originality and authenticity of students’ written work. This study aims to examine how AI influences students’ authentic academic writing skills and to identify the patterns of dependence that emerge during the writing process. A convergent mixed-methods design was employed by integrating quantitative data from questionnaires completed by 71 third-semester English education students in Makassar, Indonesia, with qualitative evidence drawn from fifteen empirical and conceptual studies published between 2024 and 2025. Descriptive statistics were used to analyze the survey data, whereas thematic synthesis was applied to the literature findings. The results indicate that students rely on AI to varying degrees across different stages of academic writing. Five interrelated forms of dependence were identified, namely dependence on idea generation, language and text organization, revision and editing, cognitive and metacognitive processes, and writing autonomy. However, the findings suggest that AI is not inherently responsible for weakening students’ writing abilities. Instead, the erosion of authentic writing tends to occur when technological assistance replaces the reflective, critical, and self-regulatory processes that are central to academic writing. These findings underscore the importance of developing educational practices that encourage students to use AI responsibly while maintaining intellectual ownership and academic integrity.
Muhammad Yahrif, Suharti Sirajuddin, Muhamad Khaedar· Al Qodiri : Jurnal Pendidika...· 0 citations
Investigation of how university students negotiate autonomy, ethical responsibility, and cognitive engagement in the context of integrating AI into a Process-Based Approach to academic writing indicates that AI-mediated writing is not only a matter of tool use but a site of negotiation, in which learners negotiate efficiency, autonomy, and authenticity.
The results revealed relevant differences between the analyzed papers: texts produced in 2023 showed greater stylistic variation, the presence of authorial markers, and irregularities typical of human writing, whereas texts from 2025 presented a higher concentration of indicators associated with linguistic standardization, structural uniformity, and a reduction of individual markers of authorship.
Gabriela Pereira da Silva, I. Rhuan, G. Tardo et al.· 0 citations
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