Bayesian analysis and digital transformation to optimize internal communication at the Huaquillas Higher Institute

Authors

DOI:

https://doi.org/10.53591/scmu.v4i2.2409

Keywords:

Digital transformation, internal communication, Bayesian analysis, higher education, ISTH

Abstract

The objective of this study was to identify effective digital tools for internal communication at the Huaquillas Higher Institute within the framework of institutional digital transformation. A mixed-method approach was employed, with a quantitative emphasis on data collection through a structured survey targeting students, teachers, and administrative staff. The Bayesian model was used to estimate the posterior probabilities of the effectiveness of five platforms: WhatsApp, Moodle, institutional email, social media, and Google Meet. The results revealed that the most effective tool was WhatsApp, followed by Moodle, and that internal communication has been functional but mainly sustained through unofficial channels. Conducting interviews to answer the research question in environments known for their scarcity demonstrated the suitability of the Bayesian approach, which integrates empirical data and prior knowledge to guide decision-making. This made it a highly appropriate approach for educational contexts facing technological and organizational constraints. Based on the results, the study proposes institutionalizing the use of hybrid channels, merging formal and informal tools, strengthening staff digital training, and carrying out periodic evaluations of the communication ecosystem. It is also suggested that this model be extended to other technical higher education institutions in order to compare the effectiveness of this study’s model with other statistical methods, such as logistic regression or AHP. Ultimately, the combination of Bayesian analysis with strategic digital communication design can significantly contribute to information management in educational institutions undergoing transformation.

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Author Biographies

  • Silvia Lorena Bravo Barrezueta, Universidad Técnica de Manabí

    Professor and researcher, PhD candidate in educational sciences from the National University of Rosario, Argentina. She holds a Master's degree in educational management and leadership from the Universidad Técnica Particular de Loja. Her areas of interest include designing teaching resources in pedagogical methodologies and developing digital skills focused on online teaching.

  • Ronny Enrique Santana Estrella, University of Guayaquil

    Systems Analyst (ESPOL), Bachelor's Degree in Web Design and Multimedia Applications (ESPOL), Master's Degree in Management Information Systems (ESPOL), PhD in Computer Science - National University of La Plata, Argentina (UNLP), university professor in the area of ​​Information and Communication Technologies at the Faculty of Social Communication of the University of Guayaquil, research professor, I have carried out studies using Augmented Reality with Smart Glasses in STEM educational environments, part of the research internship was carried out at the Advanced Computing Research and Training Laboratory (LIFIA) of the National University of La Plata, Argentina. Author and co-author of scientific articles published and registered in high-impact indexed journals, speaker at national and international events.

  • Cristian Stalin Sancho López, , Instituto Superior Tecnológico Huaquillas

    Ecuadorian. Research professor at the Huaquillas Higher Technological Institute. He holds a Master's degree in Telecommunications from the Escuela Politécnica del Litoral and a Master's degree in Cybersecurity from the Catholic University of Cuenca. His areas of interest include the Internet of Things, Telecommunications, and Cybersecurity.

References

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Published

2025-07-31

Issue

Vol. 4 No. 2 (2025): Comunicación y Marketing en la era de la inteligencia artificial

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How to Cite

Bayesian analysis and digital transformation to optimize internal communication at the Huaquillas Higher Institute. (2025). Scripta Mundi, 4(2), 50-63. https://doi.org/10.53591/scmu.v4i2.2409