Proposal for Improving and Enriching the Student Experience at the Faculty of Computer Science of Fidélitas University

Authors

DOI:

https://doi.org/10.46450/revistafidelitas.v6i2.126

Keywords:

Student experience (SX), learning analytics, educational satisfaction, personalized education, higher education improvement

Abstract

This study aims to enhance the student experience at the Faculty of Computer Science, Universidad Fidélitas, by aligning educational strategies with best practices and trends centered around client-oriented design principles. Building on previous research, student experience (SX) is viewed because of continuous interaction with institutional services. Recognizing students as service consumers, this research identifies the specific needs, frustrations, and preferences of students to create a more personalized educational environment. Key dimensions—academic, emotional, and professional development—were selected for analysis through surveys assessing satisfaction levels in teaching quality, curriculum, and emotional well-being. Data from 157 students were analyzed using descriptive and inferential statistics, as well as clustering methods, to develop student archetypes based on shared characteristics. Findings suggest that students enrolled in virtual modalities report higher satisfaction than those in hybrid or in-person settings.

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References

Castillo-Jiménez, A., & Gallardo-Echenique, E. (2020). El rol de la experiencia del cliente en la estrategia omnicanal durante el proceso de compra. Revista Ibérica de Sistemas e Tecnologías de Información, (E34), 119-132.

Fernández, P., Álvarez, J., & Cornejo, L. (2022). Satisfacción estudiantil y percepción de calidad en programas de ingeniería: Un análisis desde la experiencia del usuario. Revista Educación y Tecnología, 33(2), 45-60. https://doi.org/10.35622/j.rent.2022.02.003

Ganesan, K., & Lawrance, R. (2017). Educational Data Mining and Learning Analytics – Educational Assistance for Teaching and Learning. International Journal of Computer & Organization Trends, 41(1), 21-25.

Godoy, E. (2021, 16 de febrero). Challenge de Clustering. Medium. https://egodoyl.medium.com/challenge-de-clustering-7f774f21d298

Matus, N., Rusu, C., & Cano, S. (2021). Student eXperience: A Systematic Literature Review. Applied Sciences, 11(20), 9543. https://doi.org/10.3390/app11209543

Méndez, C., & Londoño, S. (2021). Análisis de datos para la mejora de la retención estudiantil en carreras STEM: Aplicaciones de learning analytics. Revista Colombiana de Educación, 82(1), 120–143. https://epsir.net/index.php/epsir/article/download/440/223/3912

Microsoft Learn. (2023, 31 de octubre). Algoritmos de minería de datos. Microsoft Learn: Power BI. https://learn.microsoft.com/es-es/analysis-services/data-mining/data-mining-algorithms-analysis-services-data-mining?view=asallproducts-allversions

Published

2025-07-14 — Updated on 2025-07-16

How to Cite

Proposal for Improving and Enriching the Student Experience at the Faculty of Computer Science of Fidélitas University. (2025). Revista Fidélitas, 6(2), 2-14. https://doi.org/10.46450/revistafidelitas.v6i2.126