At-Risk Trajectories In Online Higher Education: Technopedagogical SupportWith Generative Ai

Authors

Author Biographies

  • Mariángeles Castro-Sánchez, Austral University

    Doctora en Comunicación Social (Universidad Austral, Facultad de Comunicación). Magister y especialista en Dirección de Instituciones Educativas (Universidad Austral, Escuela de Educación). Especialista en Educación y Nuevas Tecnologías (FLACSO Costa Rica). Profesora asociada y miembro del Consejo de Dirección del Instituto de Ciencias para la Familia de la Universidad Austral. Integrante del Steering Committee de la Artificial Intelligence Global Education Network (AIGEN). Líder del proyecto Estrategia de Educación a Distancia de la Universidad Austral.
    ORCID: https://orcid.org/0000-0001-6874-6683
    Correo electrónico: Mcastrosanchez@austral.edu.ar

  • Romina Silvetti, Austral University

    Magíster en Tecnología Educativa (Universidad Abierta Interamericana). Licenciada en Orientación Familiar (Universidad Austral). Licenciada en Administración (Universidad de San Andrés). Profesora adjunta, asesora tecnopedagógica y profesora encargada de cohorte del Instituto de Ciencias para la Familia de la Universidad Austral.
    ORCID: https:// orcid.org/0009-0000-5762-7267
    Correo electrónico: Rsilvetti-ext@austral.edu.ar

  • Sonia Calamante, Austral University

    Magister en Tecnología Educativa (Universidad Abierta Interamericana). Diplomada superior en Ciencias Sociales y Gestión Educativa (FLACSO). Licenciada en Ciencias para la Familia (Universidad Austral). Profesora de enseñanza primaria. Profesora adjunta, asesora tecnopedagógica y profesora encargada de cohorte del Instituto de Ciencias para la Familia de la Universidad Austral.
    ORCID:  https://orcid.org/0009-0001-2183-7980 
    Correo electrónico: Scalamante-ext@austral.edu.ar

  • Daniela Bertuni, Austral University

    Especialista en Educación y Nuevas Tecnologías (FLACSO Costa Rica). Diploma Superior en Ciencias Sociales (FLACSO Argentina). Licenciada en Orientación Familiar (Universidad Austral). Asesora tecnopedagógica y profesora encargada de cohorte del Instituto de Ciencias para la Familia de la Universidad Austral.
    ORCID: https://orcid.org/0009-0000-5772-6943
    Correo electrónico: Dbertuni-ext@austral.edu.ar

DOI:

https://doi.org/10.18800/educacion.202602.M004

Keywords:

Generative artificial intelligence, Online higher education, Student dropout, Academic advising

Abstract

In online higher education, discontinuities in student performance and socialization function as early signs of academic delay or dropout. This article presents an institutional pilot that integrated generative AI (TECgpt/Skill Studio) as technopedagogical support for an academic status assessment tool (VEA), used to detect at-risk trajectories in an online degree program. An ecosystem of five configurable assistants was designed to generate reports at the student, cohort, and program levels. It was evaluated using a qualitatively dominant methodology with the academic management team across four cohorts (N = 198 active students). Results indicate that the tool systematized the process and improved traceability, although output variability was observed and recommendations lacked sufficient differentiation. The tool provides value by standardizing and scaling academic support without replacing human mediation.

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References

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Published

2026-10-21

Issue

Vol. 35 No. 69 (2026)

Section

Monográfico

License

Copyright (c) 2026 Educacion

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Castro-Sánchez, M., Silvetti, R., Calamante, S., & Bertuni, D. (2026). At-Risk Trajectories In Online Higher Education: Technopedagogical SupportWith Generative Ai. Educacion, 35(69), 54-76. https://doi.org/10.18800/educacion.202602.M004