Competencia digital docente en Panamá : diagnóstico DigCompEdu y claves sistémicas para transformar el aprendizaje

Raúl Coronado Aguirre; Kiria I. Lam Valdés; Dalys Graell; Dayse D. Pérez

doi:10.48204/j.guacamaya.v10n2.a9799

Submitted April 23, 2026

Published 2026-04-24

Artículos

Vol. 10 No. 2 (2026): Revista Científica Guacamaya

Digital teaching competence in Panama : DigCompEdu diagnostic and systemic keys to transform learning

Raúl Coronado Aguirre⁺⁻
Kiria I. Lam Valdés⁺⁻
Dalys Graell⁺⁻
Dayse D. Pérez⁺⁻

DOI https://doi.org/10.48204/j.guacamaya.v10n2.a9799

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DOI: 10.48204/j.guacamaya.v10n2.a9799

Published: 2026-04-24

How to Cite

Coronado Aguirre, R., Lam Valdés, K. I., Graell, D., & Pérez, D. D. (2026). Digital teaching competence in Panama : DigCompEdu diagnostic and systemic keys to transform learning. Revista Científica Guacamaya, 10(2), 114–125. https://doi.org/10.48204/j.guacamaya.v10n2.a9799

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

Abstract

This article reports the results of an initial digital teaching competence diagnostic administered to participants of the workshop Didáctica Digital e Innovación en la Educación Superior: Competencias docentes para transformar el aprendizaje. A sample of N = 120 completed a 36-item instrument on a 1-5 scale (1 = Never; 5 = Always) organized into six sections aligned with DigCompEdu: (1) professional engagement, (2) digital resources, (3) teaching and learning, (4) assessment, (5) empowering learners, and (6) facilitating learners’ digital competence (Redecker, 2017). Overall performance was high (M = 3.98; SD = 0.68; Median = 4.06; 95% CI [3.86, 4.10]), with a predominance of level B2 (Advanced). Assessment showed the highest mean (M = 4.28), while comparatively lower scores were observed in professional engagement (M = 3.78) and learners’ digital competence (M = 3.80). The paper discusses pedagogical and systemic implications and proposes a phased institutional action plan aligned with UNESCO’s ICT-CFT (UNESCO, 2018).

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References

Barrett, H. (2007). Researching electronic portfolios and learner engagement. The REFLECT Initiative.
Bates, T. (2019). Teaching in a digital age: Guidelines for designing teaching and learning. BCcampus.
Biggs, J. (1996). Enhancing teaching through constructive alignment. Higher Education, 32(3), 347–364.
Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7–74.
Boyer, E. L. (1990). Scholarship reconsidered: Priorities of the professoriate. Carnegie Foundation.
Brookhart, S. M. (2018). How to create and use rubrics for formative assessment and grading. ASCD.
CAST. (2018). Universal Design for Learning Guidelines (version 2.2). https://udlguidelines.cast.org/
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112.
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274.
Kotter, J. P. (1996). Leading change. Harvard Business School Press.
Mayer, R. E. (2009). Multimedia learning (2nd ed.). Cambridge University Press.
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.
NIST. (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). National Institute of Standards and Technology.
Redecker, C. (2017). European Framework for the Digital Competence of Educators: DigCompEdu. Publications Office of the European Union.
Sadler, D. R. (1989). Formative assessment and the design of instructional systems. Instructional Science, 18(2), 119–144.
Serrano Hidalgo, M., & Llorente Cejudo, M. del C. (2023). El modelo DIGCOMPEDU como base de la competencia digital docente en el contexto de una universidad latinoamericana. EDMETIC, Revista de Educación Mediática y TIC, 12(2). https://doi.org/10.21071/edmetic.v12i2.16011
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285.
UNESCO. (2018). UNESCO ICT Competency Framework for Teachers (ICT-CFT). United Nations Educational, Scientific and Cultural Organization.
UNESCO. (2019). Recommendation on Open Educational Resources (OER). UNESCO.
UNESCO. (2023). Guidance for generative AI in education and research. UNESCO.
Wiliam, D. (2011). Embedded formative assessment. Solution Tree Press.
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70.

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[1] Barrett, H. (2007). Researching electronic portfolios and learner engagement. The REFLECT Initiative.

[2] Bates, T. (2019). Teaching in a digital age: Guidelines for designing teaching and learning. BCcampus.

[3] Biggs, J. (1996). Enhancing teaching through constructive alignment. Higher Education, 32(3), 347–364.

[4] Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7–74.

[5] Boyer, E. L. (1990). Scholarship reconsidered: Priorities of the professoriate. Carnegie Foundation.

[6] Brookhart, S. M. (2018). How to create and use rubrics for formative assessment and grading. ASCD.

[7] CAST. (2018). Universal Design for Learning Guidelines (version 2.2). https://udlguidelines.cast.org/

[8] Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112.

[9] Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274.

[10] Kotter, J. P. (1996). Leading change. Harvard Business School Press.

[11] Mayer, R. E. (2009). Multimedia learning (2nd ed.). Cambridge University Press.

[12] Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.

[13] NIST. (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). National Institute of Standards and Technology.

[14] Redecker, C. (2017). European Framework for the Digital Competence of Educators: DigCompEdu. Publications Office of the European Union.

[15] Sadler, D. R. (1989). Formative assessment and the design of instructional systems. Instructional Science, 18(2), 119–144.

[16] Serrano Hidalgo, M., & Llorente Cejudo, M. del C. (2023). El modelo DIGCOMPEDU como base de la competencia digital docente en el contexto de una universidad latinoamericana. EDMETIC, Revista de Educación Mediática y TIC, 12(2). https://doi.org/10.21071/edmetic.v12i2.16011

[17] Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285.

[18] UNESCO. (2018). UNESCO ICT Competency Framework for Teachers (ICT-CFT). United Nations Educational, Scientific and Cultural Organization.

[19] UNESCO. (2019). Recommendation on Open Educational Resources (OER). UNESCO.

[20] UNESCO. (2023). Guidance for generative AI in education and research. UNESCO.

[21] Wiliam, D. (2011). Embedded formative assessment. Solution Tree Press.

[22] Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70.

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