Use of Artificial Intelligence in educational environments, analyzed through the fraud triangle model

Uso de la Inteligencia Artificial en entornos educativos, analizado mediante el modelo del triángulo de Fraude

Authors

  • Elva Gioconda Lara Guijarro

Keywords:

Inteligencia artificial, triángulo del fraude, entornos educativos, presiones académicas, educación superior.

Abstract

The research analyzes the integration of Artificial Intelligence in educational environments through the application of the fraud triangle, examining the interaction between opportunity, pressure, and rationalization. The study reveals that the accessibility and sophistication of AI tools have created an unprecedented scenario where the distinction between legitimate assistance and fraudulent use has become blurred. Contemporary academic pressures, along with intensified social and professional expectations, can drive students towards questionable practices with AI, while the rationalization of these behaviors is facilitated by the perception of these tools as legitimate aids for learning. The findings indicate that educational institutions face the challenge of keeping pace with technology that evolves faster than their policies, creating potentially exploitable regulatory gaps. The research suggests the need for a balanced approach that recognizes both the benefits and risks of AI in education, proposing a framework that integrates updated policies, the development of ethical digital skills, and the redesign of assessment methods adapted to the current technological reality.

References

Abdullahi, R., & Mansor, N. (2018). Fraud triangle theory and fraud diamond theory: Understanding the convergent and divergent for future research. European Journal of Business and Management, 10(28), 30-37.

Cotton, D., Cotton, P., & Shipway, J. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 60(5), 558-571. https://doi.org/10.1080/14703297.2023.2190148

Henderson, M., Selwyn, N., & Aston, R. (2022). What works and why? Student perceptions of 'useful' digital technology in university teaching and learning. Studies in Higher Education, 47(8), 1026-1037.

Kumar, P., Vitak, J., Chetty, M., & Clegg, T. L. (2023). The platformization of education: Learning with and through artificial intelligence. Internet Research, 33(3), 877-897.

Lang, J., Roberts, L. D., & Harrison, A. (2023). Academic integrity in the age of artificial intelligence: Exploring student perspectives on AI-assisted academic misconduct. Assessment & Evaluation in Higher Education, 48(6), 789-803.

Roberts, M., & Lee, S. (2023). Rethinking academic integrity in the era of artificial intelligence: A framework for policy and practice. Journal of Academic Ethics, 21(2), 145-162.

Thompson, P., & Chen, W. (2024). Understanding student rationalization of AI use in academic work: A qualitative study. Teaching in Higher Education, 29(1), 23-41.

Wilson, K., & García, A. (2023). Beyond detection: A holistic approach to addressing AI-enabled academic misconduct. International Journal of Educational Technology in Higher Education, 20(1), 1-18.

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2023). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 20(1), 1-42.

Anderson, P., & Lee, S. (2024). AI in Education: Challenges and Opportunities. Journal of Educational Technology, 45(2), 112-128. https://doi.org/10.1007/s11423-024-1234-5

Brown, R., Davis, M., & Thompson, E. (2024). Student Perceptions of AI Use in Academic Settings. Higher Education Research & Development, 43(3), 289-304. https://doi.org/10.1080/07294360.2024.2345678

Chen, H., & O'Sullivan, M. (2024). Reimagining Education in the AI Era. Educational Research Review, 31, 100411. https://doi.org/10.1016/j.edurev.2024.100411

Davies, K., & Yamamoto, T. (2024). Institutional Responses to AI Integration in Higher Education. International Journal of Educational Technology in Higher Education, 21(1), 1-18. https://doi.org/10.1186/s41239-024-00356-7

García-Martínez, J., Pérez-López, A., & Rodríguez-Santos, M. (2024). Academic Pressure in the Digital Age: A Mixed Methods Study. Studies in Higher Education, 49(4), 678-693. https://doi.org/10.1080/03075079.2024.2456789

Henderson, L., Wilson, K., & Chang, S. (2024). Longitudinal Study of AI Impact in Higher Education: A Five-Year Analysis. Computers & Education, 178, 104567. https://doi.org/10.1016/j.compedu.2024.104567

López, A., & White, B. (2024). Constructive AI Use in Academic Assessment: A Framework for Implementation. Assessment & Evaluation in Higher Education, 49(2), 234-249. https://doi.org/10.1080/02602938.2024.3456789

Miller, R., & Sánchez, C. (2024). Transforming Educational Models: AI Integration in Higher Education. Teaching in Higher Education, 29(3), 345-361. https://doi.org/10.1080/13562517.2024.2345678

Patel, R., & Nguyen, T. (2023). Ethical Considerations in Educational AI Use: A Systematic Review. Ethics and Education, 18(3), 289-305. https://doi.org/10.1080/17449642.2023.2345678

Rodriguez, M., & Kim, J. (2024). Personal Factors in Academic AI Use: Understanding Student Motivations. Journal of Computing in Higher Education, 36(1), 78-94. https://doi.org/10.1007/s12528-024-09321-x

Smith, J., & Johnson, T. (2023). The Evolution of Academic Integrity in the AI Era. Journal of Academic Ethics, 21(4), 456-472. https://doi.org/10.1007/s10805-023-09468-6

Taylor, R., & Martínez, A. (2024). Developing AI Policies in Higher Education: A Global Perspective. Policy Reviews in Higher Education, 8(1), 23-41. https://doi.org/10.1080/23322969.2024.2345678

Thompson, K., Roberts, L., & Anderson, M. (2023). Social Pressures and Academic Performance in the Digital Age. Studies in Educational Evaluation, 76, 101133. https://doi.org/10.1016/j.stueduc.2023.101133

Wang, Y., Li, X., & Smith, P. (2024). Institutional Challenges in AI Implementation: A Multi-Case Study. Journal of Educational Change, 25(1), 45-62. https://doi.org/10.1007/s10833-024-09456-2

Wilson, M., & Chang, R. (2024). Student Rationalization of AI Use: An Ethnographic Study. International Journal of Educational Research, 119, 102023. https://doi.org/10.1016/j.ijer.2024.102023

Published

2024-12-26

How to Cite

Lara Guijarro, E. G. (2024). Use of Artificial Intelligence in educational environments, analyzed through the fraud triangle model: Uso de la Inteligencia Artificial en entornos educativos, analizado mediante el modelo del triángulo de Fraude. Investigación Tecnológica IST Central Técnico, 6(2). Retrieved from http://investigacionistct.ec/ojs/index.php/investigacion_tecnologica/article/view/179