Why Students Use Generative Artificial Intelligence for Essay Editing: A Configurational Method and Multidimensional Ethics Scale Perspective

Jorge de Andrés-Sánchez; Antonio Pérez-Portabella; Mario Arias-Oliva; Graciela Padilla-Castillo

doi:10.37497/rev.artif.intell.educ.v7ii.1122

Autores

Jorge de Andrés-Sánchez Universitat Rovira i Virgili, Campus de Bellissens, 43204 Reus, Spain https://orcid.org/0000-0002-7715-779X
Antonio Pérez-Portabella Universitat Rovira i Virgili & Universidad Complutense de Madrid https://orcid.org/0000-0002-9684-9417
Mario Arias-Oliva Universidad Complutense de Madrid https://orcid.org/0000-0002-6874-4036
Graciela Padilla-Castillo Universidad Complutense de Madrid https://orcid.org/0000-0003-1393-4817

DOI:

https://doi.org/10.37497/rev.artif.intell.educ.v7ii.1122

Palavras-chave:

Inteligência Artificial Generativa (IAG), Escrita de Ensaios, Escala Multidimensional de Ética (MES), Análise Configuracional, Análise Qualitativa Comparativa De Conjuntos Fuzzy (FSQCA)

Resumo

Contexto: A rápida emergência da inteligência artificial generativa (IAG) está a ter um impacto substancial em numerosas áreas do ensino superior, incluindo a escrita académica. A sua utilização como assistente linguístico ocupa uma posição eticamente ambígua entre o apoio académico legítimo e práticas que podem fomentar a dependência tecnológica ou comprometer a integridade académica.

Objetivo: Examinar a utilização da IAG por estudantes universitários num cenário académico específico: a sua utilização como assistente linguístico para melhorar a qualidade da escrita e a clareza de ensaios previamente elaborados pelo estudante, sem alterar substancialmente o seu conteúdo. O objetivo é analisar de que modo diferentes juízos éticos moldam a adoção desta prática pelos estudantes, que ocupa uma posição intermédia entre o apoio académico legítimo e os potenciais riscos de dependência tecnológica ou fraude académica.

Métodos: O estudo baseia-se na Escala Multidimensional de Ética, considerando quatro dimensões morais: justiça, relativismo, consequencialismo e deontologia. Incorpora também variáveis sociodemográficas e académicas, incluindo género, situação laboral e desempenho académico percebido. Metodologicamente, aplica-se a análise qualitativa comparativa de conjuntos fuzzy (fsQCA) para identificar configurações causais associadas tanto à utilização como à não utilização da IAG.

Resultados: A aceitação não depende de uma única dimensão ética, mas de combinações específicas de juízos morais. O consequencialismo emerge como a condição mais relevante nas trajetórias que conduzem à utilização e surge frequentemente combinado com perceções favoráveis de justiça e relativismo. Em contraste, a rejeição apresenta uma estrutura mais fragmentada e uma menor cobertura explicativa, particularmente quando avaliações éticas desfavoráveis, especialmente avaliações consequencialistas, se combinam com fatores sociodemográficos.

Conclusão: A aceitação e a rejeição, por parte dos estudantes, da edição de ensaios apoiada pela IAG seguem lógicas configuracionais assimétricas, mostrando como diferentes juízos éticos se combinam para explicar a utilização de tecnologia académica num contexto moralmente ambíguo. Os resultados destacam a necessidade de regras institucionais claras, formação ética e critérios transparentes para a utilização académica da IAG. As universidades devem distinguir entre apoio linguístico aceitável e práticas que possam comprometer a integridade académica, ajudando simultaneamente os estudantes a desenvolver utilizações responsáveis e reflexivas da IAG.

Biografia do Autor

Jorge de Andrés-Sánchez, Universitat Rovira i Virgili, Campus de Bellissens, 43204 Reus, Spain

Jorge de Andrés-Sánchez (ORCID: 0000-0002-7715-779X) holds a Ph.D. from Rovira i Virgili University (Spain) and is a professor in the Business Management Department at the same university. He is an expert in the applications of soft computing to actuarial, economic, and social issues. His primary research areas include technology acceptance, the ethical implications of emerging technologies in society, and adolescents' attitudes toward issues such as substance use and misuse of new information technologies. Dr. de Andrés-Sánchez has published in various high-impact international journals on social and health issues, including Technology in Society, International Journal of Human-Computer Interaction, Nature Communications in Social Sciences and Humanities, and PeerJ.

Antonio Pérez-Portabella, Universitat Rovira i Virgili & Universidad Complutense de Madrid

Antonio Pérez-Portabella López (ORCID: 0000-0002-9684-9417) is a tenured lecturer at the Universitat Rovira i Virgili (URV), where he belongs to the Department of Communication Studies. His work covers audiovisual communication, media studies and innovation in mass media. His is currently researching in on the ethical and educational implications of generative artificial intelligence in higher education.

Mario Arias-Oliva, Universidad Complutense de Madrid

Mario Arias-Oliva (ORCID: 0000-0002-6874-4036) holds a Ph.D. in Marketing and Finance by Rovira i Virgili University and a Ph.D. in Information Science by Complutense University of Madrid. He is member of the International Advisory Board of the Centre for Business Information Ethics (Meiji University, Tokyo, Japan) and International Research Associate of the Centre for Computing and Social Responsibility (De Montfort University, Leicester, UK). His research filed is technology acceptance, publishing in international top journals papers about cryptocurrency acceptance, cyborg technologies and robotics. He has presented papers in more than a hundred International Conferences. Currently he is developing his academic activity in Complutense University of Madrid (Spain).

Graciela Padilla-Castillo, Universidad Complutense de Madrid

Graciela Padilla-Castillo (ORCID: 0000-0003-1393-4817) is a tenured professor at the Complutense University of Madrid, where she also serves as Vice Dean for Research and Scientific Policy at the Faculty of Information Sciences. She holds a PhD in Information Sciences and completed postdoctoral training at UCLA. Her research focuses on information theory, communication ethics, television fiction, and gender studies, and she directs the journal Investigaciones Feministas.

Referências

Ahadzadeh, A. S., Ong, F. S., Deng, R., & Ali, R. S. (2024). Unravelling the Relationship between Competitiveness Trait and Intention to Use Memory Implants: The Moderating Roles of Moral Equity, Egoism, and Utilitarianism. International Journal of Human–Computer Interaction, 40(24), 8922–8936. https://doi.org/10.1080/10447318.2023.2291621 DOI: https://doi.org/10.1080/10447318.2023.2291621

Alexander, L., & Moore, M. (2024). Deontological ethics. In E. N. Zalta & U. Nodelman (Eds.), The Stanford Encyclopedia of Philosophy (Winter 2024 Edition). Metaphysics Research Lab, Stanford University. https://plato.stanford.edu/archives/win2024/entries/ethics-deontological/

Amin, M. Al, Kim, Y. S., & Noh, M. (2025). Unveiling the drivers of ChatGPT utilization in higher education sectors: the direct role of perceived knowledge and the mediating role of trust in ChatGPT. Education and Information Technologies, 30(6), 7265–7291. https://doi.org/10.1007/s10639-024-13095-y DOI: https://doi.org/10.1007/s10639-024-13095-y

Andersen, S., & Hjortskov, M. (2019). The unnoticed influence of peers on educational preferences. Behavioural Public Policy, 6(4), 530–553. https://doi.org/10.1017/bpp.2019.1 DOI: https://doi.org/10.1017/bpp.2019.14

Andrés-Sánchez, J., Arias-Oliva, M., & Pelegrín-Borondo, J. (2021). The influence of ethical judgements on acceptance and non-acceptance of wearables and insideables: Fuzzy set qualitative comparative analysis. Technology in Society, 67, 101689. https://doi.org/10.1016/j.techsoc.2021.101689 DOI: https://doi.org/10.1016/j.techsoc.2021.101689

Arli, D., Tjiptono, F., & Porto, R. (2015). The impact of moral equity, relativism and attitude on individuals’ digital piracy behaviour in a developing country. Marketing Intelligence & Planning, 33(3), 348–365. https://doi.org/10.1108/MIP-09-2013-0149 DOI: https://doi.org/10.1108/MIP-09-2013-0149

Baghramian, M., & Carter, J. A. (2025). Relativism. In E. N. Zalta & U. Nodelman (Eds.), The Stanford Encyclopedia of Philosophy (Spring 2025 Edition).

Barbosa, J. (2024). Higher education in ethics and deontology: Student’s perspective survey. WSEAS Transactions on Advances in Engineering Education, 21, 128–138. DOI: https://doi.org/10.37394/232010.2024.21.16

Basch, C. H., Hillyer, G. C., Gold, B., & Yousaf, H. (2025). Understanding artificial intelligence knowledge and usage among college students: Insights from a survey on classroom, coursework, and personal applications. Review of Artificial Intelligence in Education, 6(i), e037. https://doi.org/10.37497/rev.artif.intell.educ.v6ii.37 DOI: https://doi.org/10.37497/rev.artif.intell.educ.v6ii.37

Biloš, A., & Budimir, B. (2024). Understanding the Adoption Dynamics of ChatGPT among Generation Z: Insights from a Modified UTAUT2 Model. J. Theor. Appl. Electron. Commer. Res., 19(2), 863–879. https://doi.org/10.3390/jtaer19020045 DOI: https://doi.org/10.3390/jtaer19020045

Birkland, J. L. H. (2019). Understanding the ICT User Typology and the User Types. In Gerontechnology (pp. 95–106). Emerald Publishing Limited. https://doi.org/10.1108/978-1-78743-291-820191009 DOI: https://doi.org/10.1108/978-1-78743-291-820191009

Camilleri, M. A. (2024). Factors affecting performance expectancy and intentions to use ChatGPT: Using SmartPLS to advance an information technology acceptance framework. Technological Forecasting and Social Change, 201, 123247. https://doi.org/10.1016/j.techfore.2024.123247 DOI: https://doi.org/10.1016/j.techfore.2024.123247

Campo, L., Delgado, N., Etxabe-Urbieta, J. M., Kanso, H., & Gueye, M. L. (2025). Relationship Between the Use of ChatGPT and Plagiarism in Higher Education: The Influence of Gender, Age and Previous Academic Results. Innovative Higher Education. https://doi.org/10.1007/s10755-025-09830-z DOI: https://doi.org/10.1007/s10755-025-09830-z

Cebrián Cifuentes, S., Guerrero Valverde, E., & Checa Caballero, S. (2024). The Vision of University Students from the Educational Field in the Integration of ChatGPT. Digital, 4(3), 648–659. https://doi.org/10.3390/digital4030032 DOI: https://doi.org/10.3390/digital4030032

Cheung, G. W., Cooper-Thomas, H. D., Lau, R. S., & Wang, L. C. (2024). Reporting reliability, convergent and discriminant validity with structural equation modeling: A review and best-practice recommendations. Asia Pacific Journal of Management, 41(2), 745–783. https://doi.org/10.1007/s10490-023-09871-y DOI: https://doi.org/10.1007/s10490-023-09871-y

Dahl, B. M., Vasset, F., & Frilund, M. (2023). Students’ approaches to scientific essay writing as an educational method in higher education: A mixed methods study. Social Sciences & Humanities Open, 7(1), 100389. DOI: https://doi.org/10.1016/j.ssaho.2022.100389

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., & Wright, R. (2023). Opinion paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642 DOI: https://doi.org/10.1016/j.ijinfomgt.2023.102642

Fiss, P. C. (2011). Building better causal theories: A fuzzy set approach to typologies in organization research. Academy of Management Journal, 54(2), 393–420. https://doi.org/10.5465/amj.2011.60263120 DOI: https://doi.org/10.5465/amj.2011.60263120

Gauttier, S. (2019). ‘I’ve got you under my skin’–The role of ethical consideration in the (non-) acceptance of insideables in the workplace. Technology in Society, 56, 93–108. https://doi.org/10.1016/j.techsoc.2018.09.008 DOI: https://doi.org/10.1016/j.techsoc.2018.09.008

Gorrieri, L. (2025). Should I use ChatGPT as an academic aid? A response to Aylsworth and Castro. Philosophy & Technology, 38(1), 8. https://doi.org/10.1007/s13347-024-00831-y DOI: https://doi.org/10.1007/s13347-024-00831-y

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203 DOI: https://doi.org/10.1108/EBR-11-2018-0203

Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274 DOI: https://doi.org/10.1016/j.lindif.2023.102274

Killen, M. (2018). The origins of morality: Social equality, fairness, and justice. Philosophical Psychology, 31(5), 767–803. https://doi.org/10.1080/09515089.2018.1486612 DOI: https://doi.org/10.1080/09515089.2018.1486612

Leonard, L. N., Riemenschneider, C. K., & Manly, T. S. (2017). Ethical behavioral intention in an academic setting: Models and predictors. Journal of Academic Ethics, 15(2), 141–166. https://doi.org/10.1007/s10805-017-9273-2 DOI: https://doi.org/10.1007/s10805-017-9273-2

Licht, K. de F. (2024). Generative artificial intelligence in higher education: Why the “banning approach” to student use is sometimes morally justified. Philosophy & Technology, 37(3), 113. https://doi.org/10.1007/s13347-024-00799-9 DOI: https://doi.org/10.1007/s13347-024-00799-9

Livian, Y.-F. (2026). The role of generative AI for academic writing: A risk of disappearance of students skills? A reflection in the French context. Review of Artificial Intelligence in Education, 7(i), e059. https://doi.org/10.37497/rev.artif.intell.educ.v7ii.59 DOI: https://doi.org/10.37497/rev.artif.intell.educ.v7ii.59

Menon, D., & Shilpa, K. (2023). “Chatting with ChatGPT”: Analyzing the factors influencing users’ intention to use the OpenAI’s ChatGPT using the UTAUT model. Heliyon, 9(11), e20142. https://doi.org/10.1016/j.heliyon.2023.e20962 DOI: https://doi.org/10.1016/j.heliyon.2023.e20962

Naznin, K., Al Mahmud, A., Nguyen, M. T., & Chua, C. (2025). ChatGPT Integration in Higher Education for Personalized Learning, Academic Writing, and Coding Tasks: A Systematic Review. Computers, 14(2). https://doi.org/10.3390/computers14020053 DOI: https://doi.org/10.3390/computers14020053

Nguyen, N. T., Basuray, M. T., Smith, W. P., Kopka, D., & McCulloh, D. (2008). Moral issues and gender differences in ethical judgment using Reidenbach and Robin’s (1990) multidimensional ethics scale: Implications in teaching of business ethics. Journal of Business Ethics, 77, 417–430. https://doi.org/10.1007/s10551-007-9357-9 DOI: https://doi.org/10.1007/s10551-007-9357-9

Pappas, I. O., & Woodside, A. G. (2021). Fuzzy-set Qualitative Comparative Analysis (fsQCA): Guidelines for research practice in Information Systems and marketing. International Journal of Information Management, 58. https://doi.org/10.1016/j.ijinfomgt.2021.102310 DOI: https://doi.org/10.1016/j.ijinfomgt.2021.102310

Pelegrín-Borondo, J. P., Pascual, C. O., Pascual, L. B., & Milon, A. G. (2024). Impact of ethical judgment on university professors encouraging students to use AI in academic tasks. In The leading role of smart ethics in the digital world (pp. 53–61). Universidad de La Rioja.

Pérez-Portabella, A., Arias-Oliva, M., Padilla-Castillo, G., & de Andrés-Sánchez, J. (2025). Passing with ChatGPT? Ethical Evaluations of Generative AI Use in Higher Education. Digital, 5(3). https://doi.org/10.3390/digital5030033 DOI: https://doi.org/10.3390/digital5030033

Pérez-Portabella, A., Arias-Oliva, M., Padilla-Castillo, G., & de Andrés-Sánchez, J. (2026). Ethical conditions for university students’ adoption of large language models in exam preparation contexts. Computers and Education Open, 10, 100323. https://doi.org/10.1016/j.caeo.2025.100323 DOI: https://doi.org/10.1016/j.caeo.2025.100323

Pérez-Portabella, A., de Andrés-Sánchez, J., Arias-Oliva, M., & Padilla-Castillo, G. (2026). Ethical Judgments and Weakness of Will in the Misuse of Generative AI: The Case of Academic Essay Production among Higher Education Students. Innovative Higher Education, 51(2), 453–479. https://doi.org/10.1007/s10755-026-09885-6 DOI: https://doi.org/10.1007/s10755-026-09885-6

Pérez-Portabella, A., de Andrés-Sánchez, J., Arias-Oliva, M., & Souto-Romero, M. (2026). Explaining higher education social sciences students’ misuse of generative artificial intelligence: evidence from a multidimensional ethics scale. SN Social Sciences, 6(1), 18. https://doi.org/10.1007/s43545-025-01294-4 DOI: https://doi.org/10.1007/s43545-025-01294-4

Pilcher, J. J., & Smith, P. D. (2024). Social context during moral decision-making impacts males more than females. Frontiers in Psychology, 15, 1397069. https://doi.org/10.3389/fpsyg.2024.1397069 DOI: https://doi.org/10.3389/fpsyg.2024.1397069

Prashar, P., Gupta, Y., & Dwivedi, Y. K. (2023). Plagiarism awareness efforts, students’ ethical judgment and behaviors: A longitudinal experiment study on ethical nuances of plagiarism in higher education. Studies in Higher Education, 49(6), 929–955. https://doi.org/10.1080/03075079.2023.2253835 DOI: https://doi.org/10.1080/03075079.2023.2253835

Ragin, C. C. (2018). User’s Guide to Fuzzy-Set/Qualitative Comparative Analysis 3.0. https://sites.socsci.uci.edu/~cragin/fsQCA/software.shtml

Ramberg, J., & Modin, B. (2019). School effectiveness and student cheating: Do students’ grades and moral standards matter for this relationship? Social Psychology of Education, 22, 1313–1337. https://doi.org/10.1007/s11218-019-09486-6 DOI: https://doi.org/10.1007/s11218-019-09486-6

Reidenbach, R. E., & Robin, D. P. (1990). Toward the development of a multidimensional scale for improving evaluations of business ethics. Journal of Business Ethics, 9(8), 639–653. https://doi.org/10.1007/BF00383391 DOI: https://doi.org/10.1007/BF00383391

Rua, T., Lawter, L., & Andreassi, J. (2024). The ethical student scale: development of a new measure. Organization Management Journal, 21(3), 117–128. https://doi.org/10.1108/OMJ-03-2023-1831 DOI: https://doi.org/10.1108/OMJ-03-2023-1831

Rutten, R., & Rubinson, C. (2022). A vocabulary for QCA.

Shawver, T. J., & Sennetti, J. T. (2009). Measuring ethical sensitivity and evaluation. Journal of Business Ethics, 88(4), 663–678. https://doi.org/10.1007/s10551-008-9973-z DOI: https://doi.org/10.1007/s10551-008-9973-z

Silva, A. de O., & Janes, D. (2025). Editorial perspective on the 2025 edition (V6) of the Review of Artificial Intelligence in Education: Advances, challenges, and theoretical convergences in global AI-in-education research. Review of Artificial Intelligence in Education, 6(i), e065. https://doi.org/10.37497/rev.artif.intell.educ.v6ii.65 DOI: https://doi.org/10.37497/rev.artif.intell.educ.v6ii.65

Sinnott-Armstrong, W. (2023). Consequentialism. In E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy.

Strzelecki, A. (2024). To use or not to use ChatGPT in higher education? A study of students’ acceptance and use of technology. Interactive Learning Environments, 32(9), 5142–5155. https://doi.org/10.1080/10494820.2023.2209881 DOI: https://doi.org/10.1080/10494820.2023.2209881

Tsaousis, I., & Alghamdi, M. H. (2022). Examining academic performance across gender differently: Measurement invariance and latent mean differences using bias-corrected bootstrap confidence intervals. Frontiers in Psychology, Volume 13-2022. https://doi.org/10.3389/fpsyg.2022.896638 DOI: https://doi.org/10.3389/fpsyg.2022.896638

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540 DOI: https://doi.org/10.2307/30036540

Woodside, A. G. (2014). Embrace perform model: Complexity theory, contrarian case analysis, and multiple realities. Journal of Business Research, 67(12), 2495–2503. https://doi.org/10.1016/j.jbusres.2014.07.006 DOI: https://doi.org/10.1016/j.jbusres.2014.07.006

Yang, S. C. (2012). Ethical academic judgments and behaviors: Applying a multidimensional ethics scale to measure the ethical academic behavior of graduate students. Ethics & Behavior, 22(4), 281–296. https://doi.org/10.1080/10508422.2012.672907 DOI: https://doi.org/10.1080/10508422.2012.672907

Yudhistyra, W. I., & Srinuan, C. (2024). Exploring the Acceptance of Technological Innovation Among Employees in the Mining Industry: A Study on Generative Artificial Intelligence. IEEE Access, 12, 165797–165809. https://doi.org/10.1109/ACCESS.2024.3493242 DOI: https://doi.org/10.1109/ACCESS.2024.3493242