Fraud, Plagiarism, or Lack of Professional Ethics
DOI:
https://doi.org/10.37843/rted.v19i1.781
Main Article Content
Abstract
The emergence of generative artificial intelligence in higher education is redefining the boundaries between technological support, plagiarism, and academic fraud, particularly in the capstone projects undertaken within teacher education programs. This essay aimed to analyze a case involving the potential misuse of artificial intelligence in a professional report and, based on this analysis, to propose an instrument for assessing authenticity, methodological rigor, and ethical integrity in academic production. The study was grounded in the inductive method, employing an interpretive qualitative approach and a topical narrative design centered on case analysis. The analysis sought to identify textual cues associated with writing generated by language models and to cross-reference them against established criteria for academic integrity. The findings revealed the presence of non-existent references, recurring linguistic patterns, low auditability of the writing process, and a lack of triangulation, factors that triggered the warning indicators within the proposed assessment instrument. It was concluded that the undeclared use of artificial intelligence compromises professional ethics; consequently, there is a need to strengthen formative guidance and methodological supervision, as well as to establish institutional codes of conduct that regulate the use of AI from a preventive pedagogical perspective.
Downloads
Metrics
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Those authors who have publications in our journal accept the following terms:
- When a work is accepted for publication, the author retains rights of reproduction, distribution of his/her article for exploitation in all countries of the world in the format provided by our magazine and any other magnetic medium, optical, and digital.
- Authors will retain their copyright and guarantee the journal the right first to publish their work, which will be simultaneously subject to the Creative Commons Acknowledgment License (Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)). That allows third parties to copy and redistribute the material in any medium or format, under the following conditions: Acknowledgment - You must properly acknowledge authorship, provide a link to the license, and indicate if any changes have been made. You may do so in any reasonable way, but not in a way that suggests you have the licensor's endorsement or receive it for your use. NonCommercial - You may not use the material for a commercial purpose. NoDerivatives - If you remix, transform, or build from the material, you cannot broadcast the modified material. There are no additional restrictions - You cannot apply legal terms or technological measures that legally restrict you from doing what the license allows.
- Authors may adopt other non-exclusive license agreements to distribute the published version of the work (e.g., deposit it in an institutional archive or publish it in a monographic volume) provided that the initial publication in this journal is indicated.
- Authors are allowed and recommended to disseminate their work through the Internet (e.g., in institutional telematic archives, repositories, libraries, or their website), producing exciting exchanges and increasing the published work's citations.
- Request of withdrawal an article has to be done in writing by the author to the Editor, becoming effective after a written response from the Editor. For this purpose, the author or authors will send correspondence via e-mail: [email protected].
- The author will not receive financial compensation for the publication of his work.
- All Docentes 2.0 Journal publications are under the Open Journal System (OJS) platform at: https://ojs.docentes20.com/.
Citaciones del Artículo
References
Alfaro-Salas, H., & Díaz Porras, J. A. (2024). Percepciones y Aplicaciones de la IA entre Estudiantes de Secundaria. Revista Docentes 2.0, 17(1), 200–215. https://doi.org/10.37843/rted.v17i1.458
Barr, R. (2025). Neuroscientist explains why AI detection tools don’t work. En el canal de Instagram Rachel Barr, The Neuroscientist. https://go.docentes20.com/r3ayy
Bisi, T., Risser, A., Clavert, P., Migaud, H., & Dartus, J. (2023). What is the rate of text generated by artificial intelligence over a year of publication in Orthopedics y Traumatology: Surgery y Research? Analysis of 425 articles before versus after the launch of ChatGPT in November 2022. Orthop Traumatol Surg Res. 109(8) http://www.doi.org/10.1016/j.otsr.2023.103694
Bravo, X. R., & Osorio, B. (2017). Criterios de calidad y rigor en la metodología cualitativa. Gac pedagóg, 36, 62-74. https://doi.org/10.56219/rgp.vi36.566
Cadenas, D. M. R. (2016). El rigor en la investigación cualitativa: técnicas de análisis, credibilidad, transferibilidad y confirmabilidad. Sinopsis Educativa. Revista venezolana de investigación, 7(1), 17-26. https://go.docentes20.com/r62s
Castillo, E., & Vásquez, M. L. (2003). El rigor metodológico en la investigación cualitativa. Colombia médica, 34(3), 164-167. https://go.docentes20.com/rvq3
Corral, Y. (2016). Validez y fiabilidad en investigaciones cualitativas. Revista Arjé, 11(21), 196-209. https://go.docentes20.com/rjzes
Dien, J., & Ritz, T. (2023). Editorial: Generative artificial intelligence as a plagiarism problem, Biological Psychology, 181 (July). https://doi.org/10.1016/j.biopsycho.2023.108595
Elliot, J. (1991). Action research for educational change. Open University Press.
Fátima. (2025). Documento recepcional. Inédito.
Fierro, C., Fortoul, B., & Rosas, L. (1999). Transformando la práctica docente: Una propuesta basada en la investigación-acción. Paidós.Dung, D. A., Toan, N. T., Minh, N. D., & Anh, N. Q. (2025). Reimagining Quality: Artificial Intelligence, Governance and the Politics of Data in Higher Education. Higher Education for the Future, 13(1), 50-73. https://doi.org/10.1177/23476311251386123
Francke, E., & Alexander, B. (2019). The Potencial Influence of Artificial Intelligence on Plagiarism: A Higher Education Perspective. En Griffiths, P. (Editor) ECIAIR European Conference on the Impact of Artificial Intelligence and Robotics http://www.doi.org/10.34190/ECLAIR.19.043
Gaylor, B. (2012) Rip! El manifiesto del remix. EyeSteelFilm y National Film Board of Canada. https://go.docentes20.com/r9c5
Gritsai, G., Voznyuk, A., Grabovoy, A., & Chekhovich, Y. (2024). Are ai detectors good enough? a survey on quality of datasets with machine-generated texts. arXiv preprint arXiv:2410.14677. https://go.docentes20.com/rxt3
Gutiérrez, J. D. (2023). Lineamientos para el uso de inteligencia artificial en contextos universitarios. GIGAPP Estudios Working Papers, 10(267-272), 416-434. https://go.docentes20.com/rvcg
Hernández, I. R., Mateus, J. C., Rogel, D. E. R., & Meléndez, L. R. Á. (2024). Percepciones de estudiantes latinoamericanos sobre el uso de la inteligencia artificial en la educación superior. Austral Comunicación, 13(1), 34-58. https://go.docentes20.com/r5gx
Huang, K., & Lee-Post, A. (2025). Enhancing online college students' self-regulated learning and performance through self-assessments and commitment strategies. The Internet and Higher Education, 67, 101033. https://doi.org/10.1016/j.iheduc.2025.101033
Hutson, J. (2024). Rethinking plagiarism in the era of generative AI. Journal of Intelligent Communication, 4(1). https://doi.org/10.54963/jic.v3i2.220
International Center for Academic Integrity (ICAI). (2021). The Fundamental Values of Academic Integrity, Third Edition. https://go.docentes20.com/rg6u5
JustDone (2025). Just Done: Plagiarism detector, Text Humanizer, AI Detector, Paraphraser, Grammar Checker, Image Generator, and more. https://go.docentes20.com/rhr2
Latorre, A. (2004). Investigación-acción: estrategias para mejorar la práctica educativa. Graó. https://go.docentes20.com/rb4pr
Moya, B.A., & Eaton, S. E. (2023). Examinando Recomendaciones para el Uso de la Inteligencia Artificial Generativa con Integridad desde una Lente de Enseñanza y Aprendizaje. En RELIEVE. Revista Electrónica de Investigación y Evaluación Educativa. 29 (2). https://doi.org/10.30827/relieve.v29i2.29295
Muñoz-Ortiz, A. Gómez-Rodríguez, C., & Vilares, D. (2024). Contrasting Linguistic Patterns in Human and LLM-Generated News Text. Artif Intell Rev, 57, 265 (2024). https://doi.org/10.1007/s10462-024-10903-2
Ocampo Martínez, F. A. (2024). Escritura en tiempos de la inteligencia artificial: desafíos para el docente de Educación Normal. DIDAC, (84 JUL-DIC), 21–29. https://doi.org/10.48102/didac.2024..84_JUL-DIC.209
Oluwagbenro, M. B. (2024). Generative AI: Definition, Concepts, Applications, and Future Prospects. Authorea Preprints. https://go.docentes20.com/rgxy
Raffaghelli, J. E., Rivera-Vargas, P., & Dussel, Ines. (2025). Repensar la ética en la era de la IA: más allá de una pedagogía de la crueldad. Izquierdas. 54. http://www.doi.org/10.4067/S0718-50492025000100245
Rincón Castillo, A., Rodríguez, C., Castañeda, L. y Mejía, D. (2024). La inteligencia artificial en la formación de profesores. Una revisión sistemática. En Ruiz-Velasco, E. y Bárcenas, J. (Coordinadores) Argumentos y usos tecnopedagógicos de la Inteligencia Artificial. Sociedad Mexicana de Computación en la Educación A. C. https://go.docentes20.com/ryu8
Salgado Lévano, A. C. (2007). Investigación cualitativa: diseños, evaluación del rigor metodológico y retos. Liberabit, 13(13), 71-78. https://go.docentes20.com/ra3bq
Sánchez, A. (2009). La enseñanza de idiomas en los últimos 100 años. Métodos y enfoques. España. SGEL.
Sánchez, A. (2005). El español en cifras. (PDF). Biblioteca Ele del Instituto Cervantes. https://go.docentes20.com/rpp2w
Soto Rodríguez, A. (2012). El plagio y su impacto a nivel académico y profesional. E-Ciencias De La Información, 2(1), 1–13. https://doi.org/10.15517/eci.v2i1.1213
Starman, A. B. (2013). The case study as a type of qualitative research. Journal of Contemporary Educational Studies, 64(1), 28–43. https://go.docentes20.com/rgga
Universidad Iberoamericana (UIA). (2024). Construyendo en conjunto: propuesta de políticas públicas desde la Universidad Iberoamericana para México. Universidad Iberoamericana A.C. https://go.docentes20.com/rrms
Vera, H. (2016). Introducción. El plagio nuestro de todos los días. Perfiles educativos, 38(154), 2-5. https://go.docentes20.com/rfht
Yang, S., Chen, S., Zhu, H., Lin, J., y Wang, X. (2024). A comparative study of thematic choices and thematic progression patterns in human-written and AI-generated texts. System, 126, 103494. https://doi.org/10.1016/j.system.2024.103494
Yankelevich, J. (2016). Mapas prestados para entender el plagio académico. Perfiles educativos, 38(154), 20-27. https://go.docentes20.com/rkcz6
Zhou, E. P. (2023). The Fallibility of AI Content Detectors. In 2023 IEEE MIT Undergraduate Research Technology Conference (URTC) (pp. 1-4). IEEE. http://doi.org/10.1109/URTC60662.2023.10534929