MACHINE LEARNING TO PREDICT STUDENT ACADEMIC RISK IN ENGINEERING

Autores/as

  • Lizeth Stephany Roldán Jiménez Pontificia Universidad Javeriana

DOI:

https://doi.org/10.26507/ponencia.1579

Resumen

Identifying academic risk in an engineering program is very important since it allows to stablish policies that can be applied to prevent it and to guarantee student success. At Pontificia Universidad Javeriana in Bogotá – Colombia, we have developed s

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Referencias bibliográficas

Al-Atabi, M. (2013). Grand Challenges for Engineering and Development of CDIO Skills. Proceedings of the 9th International CDIO Conference, Cambridge, MA, USA.

Crawley, E., F. Malmqvist, J., Östlund, S., Brodeur, D., & Edström, K. (2014). Rethinking Engineering Education: The CDIO Approach, 2nd edition. New York: Springer-Verlag.

Géron, A. (2017). Hands-On Machine Learning with Scikit-Learn & TensorFlow,O’Reilly.

González, A., Barrera, D.,León, M., Curiel,M., & Prieto,L.(2018). Student Success: On The Need for A New Standard, Proceedings of the 14th International CDIO Conference, Kanazawa Institute of Technology, Kanazawa, Japan.

González, A., Patino, D., Roldán, L., Pena, J., Barrera, D. (2019). Toward Early Intervention: Model Of Academic Performance In A CDIO Curriculum, Proceedings of the 15th International CDIO Conference, Aarhus University, Denmark.

Jaramillo, C., Ordóñez, C., González, A., León, M., Curiel, M., Palacios, J., & Barrera, D. Formulación Del Programa De Prevención De La Deserción: Articulación De Acciones En Un Programa Transversal De Acompañamiento Para La Pontificia Universidad Javeriana. (2018). Congreso CLABES VIII, Ciudad de Panamá, Panamá.

Jayaprakash, Sandeep & Moody, E.W. & Lauria, Eitel & J., Regan & Baron, J.D.. (2014). Early Alert of Academically At-Risk Students: An Open Source Analytics Initiative. Journal of Learning Analytics. 1. 6-47..

Torres, L.(2012). Retención estudiantil en la educación superior: revisión de la literatura y elementos de un modelo para el contexto colombiano. Bogotá: Editorial Pontificia Universidad Javeriana.

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Publicado

2021-09-07

Cómo citar

[1]
L. S. Roldán Jiménez, «MACHINE LEARNING TO PREDICT STUDENT ACADEMIC RISK IN ENGINEERING», EIEI ACOFI, sep. 2021.