Evidence-based decision-making in Chilean higher education: the MITEDEC framework.
DOI:
https://doi.org/10.53382/issn.2810-7977.60Keywords:
decision-making, competency-based education, Chile, artificial intelligence, higher educationAbstract
Preparing professionals capable of acting in complex contexts requires moving beyond educational models focused exclusively on the acquisition of disciplinary knowledge. Evidence-based decision-making is an integrative competence through which students select, interpret, and contrast scientific information, disciplinary knowledge, contextual factors, ethical considerations, and professional experience to justify appropriate courses of action. However, research on competency-based education, critical thinking, authentic assessment, professional judgment, and artificial intelligence has addressed these components predominantly in isolation. This article develops the Integrative Framework for the Development of Evidence-Based Decision-Making Competence (MITEDEC) through an integrative review and a conceptual synthesis process. The framework comprises five interdependent levels: institutional conditions, pedagogical processes, cognitive-professional processes, decision-making competence, and professional performance impact. Artificial intelligence is incorporated as a transversal cognitive mediation whose educational value depends on information verification, metacognitive reflection, human judgment, and ethical responsibility. MITEDEC proposes that this competence does not emerge from an isolated course or teaching method, but from a longitudinal trajectory of increasingly complex curricular, assessment, and professional experiences. Within the Chilean context, the framework provides guidance for articulating graduate profiles, learning outcomes, authentic assessment, internal quality assurance, and institutional artificial intelligence policies. Finally, it establishes foundations for future conceptual validation, operationalization, and empirical evaluation.
Downloads
References
Andreucci-Annunziata, P., Riedemann, A., Cortés, S., Mellado, A., del Río, M. T., & Vega-Muñoz, A. (2023). Conceptualizations and instructional strategies on critical thinking in higher education: A systematic review of systematic reviews. Frontiers in Education, 8, Article 1141686. https://doi.org/10.3389/feduc.2023.1141686
Biggs, J., Tang, C., & Kennedy, G. (2022). Teaching for quality learning at university (5th ed.). Open University Press.
Brauer, S. (2021). Towards competence-oriented higher education: A systematic literature review of the different perspectives on successful exit profiles. Education + Training, 63(9), 1376–1390. https://doi.org/10.1108/ET-07-2020-0216
Chong, S. W., Lin, T. J., & Chen, Y. (2022). A methodological review of systematic literature reviews in higher education: Heterogeneity and homogeneity. Educational Research Review, 35, Article 100426. https://doi.org/10.1016/j.edurev.2021.100426
Comisión Nacional de Acreditación. (2021). Criterios y estándares de calidad para la acreditación institucional del subsistema universitario. https://www.cnachile.cl/noticias/Paginas/nuevos_cye.aspx
Decreto N.º 12 de 2024. (2025, 28 de enero). Aprueba actualización de la Política Nacional de Inteligencia Artificial. Diario Oficial de la República de Chile. https://www.bcn.cl/leychile/navegar?idNorma=1210664
Dennis, J. L., & Somerville, M. P. (2023). Supporting thinking about thinking: Examining the metacognition theory-practice gap in higher education. Higher Education, 86, 99–117. https://doi.org/10.1007/s10734-022-00904-x
DeVellis, R. F., & Thorpe, C. T. (2021). Scale development: Theory and applications (5th ed.). SAGE.
Howard, B., Diug, B., & Ilic, D. (2022). Methods of teaching evidence-based practice: A systematic review. BMC Medical Education, 22, Article 742. https://doi.org/10.1186/s12909-022-03812-x
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., . . . Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, Article 102274. https://doi.org/10.1016/j.lindif.2023.102274
Kumah, E. A., McSherry, R., Bettany-Saltikov, J., van Schaik, P., Hamilton, S., Hogg, J., & Whittaker, V. (2022). Evidence-informed versus evidence-based practice educational interventions for improving knowledge, attitudes, understanding, and behaviour towards the application of evidence into practice: A comprehensive systematic review of undergraduate students. Campbell Systematic Reviews, 18(2), Article e1233. https://doi.org/10.1002/cl2.1233
Kutcher, A. M., & LeBaron, V. T. (2022). A simple guide for completing an integrative review using an example article. Journal of Professional Nursing, 40, 13–19. https://doi.org/10.1016/j.profnurs.2022.02.004
Laupichler, M. C., Aster, A., Schirch, J., & Raupach, T. (2022). Artificial intelligence literacy in higher and adult education: A scoping literature review. Computers and Education: Artificial Intelligence, 3, Article 100101. https://doi.org/10.1016/j.caeai.2022.100101
Ley N.º 21.091. (2018, 29 de mayo). Sobre Educación Superior. Diario Oficial de la República de Chile. https://www.bcn.cl/leychile/navegar?idNorma=1118991
Lintner, T. (2024). A systematic review of AI literacy scales. npj Science of Learning, 9, Article 50. https://doi.org/10.1038/s41539-024-00264-4
McArthur, J. (2023). Rethinking authentic assessment: Work, well-being, and society. Higher Education, 85(1), 85–101. https://doi.org/10.1007/s10734-022-00822-y
Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://doi.org/10.54675/EWZM9535
Nasa, P., Jain, R., & Juneja, D. (2021). Delphi methodology in healthcare research: How to decide its appropriateness. World Journal of Methodology, 11(4), 116–129. https://doi.org/10.5662/wjm.v11.i4.116
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, Article 100041. https://doi.org/10.1016/j.caeai.2021.100041
Niederberger, M., Spranger, J., Homberg, A., Sonnberger, M., & Members of DeWiss. (2022). Reporting guidelines for Delphi techniques in health sciences: A methodological review. Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen, 172, 1–11. https://doi.org/10.1016/j.zefq.2022.04.025
OECD. (2023). OECD skills outlook 2023: Skills for a resilient green and digital transition. OECD Publishing. https://doi.org/10.1787/27452f29-en
Ossa, C. J., Rivas, S. F., & Saiz, C. (2023). Relation between metacognitive strategies, motivation to think, and critical thinking skills. Frontiers in Psychology, 14, Article 1272958. https://doi.org/10.3389/fpsyg.2023.1272958
Rivas, S. F., Saiz, C., & Ossa, C. (2022). Metacognitive strategies and development of critical thinking in higher education. Frontiers in Psychology, 13, Article 913219. https://doi.org/10.3389/fpsyg.2022.913219
Schreiber, F., & Cramer, C. (2024). Towards a conceptual systematic review: Proposing a methodological framework. Educational Review, 76(6), 1458–1479. https://doi.org/10.1080/00131911.2022.2116561
Sokhanvar, Z., Salehi, K., & Sokhanvar, F. (2021). Advantages of authentic assessment for improving the learning experience and employability skills of higher education students: A systematic literature review. Studies in Educational Evaluation, 70, Article 101030. https://doi.org/10.1016/j.stueduc.2021.101030
Soyka, C., & Schaper, N. (2024). Analyzing student response processes to refine and validate a competency model and competency-based assessment task types. Frontiers in Education, 9, Article 1397027. https://doi.org/10.3389/feduc.2024.1397027
Tertiary Education Quality and Standards Agency. (2023). Assessment reform for the age of artificial intelligence. https://www.teqsa.gov.au/guides-resources/resources/corporate-publications/assessment-reform-age-artificial-intelligence
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10, Article 15. https://doi.org/10.1186/s40561-023-00237-x
Tsiotsou, R. H., Koles, B., Paul, J., & Loureiro, S. M. C. (2022). Theory generation from literature reviews: A methodological guidance. International Journal of Consumer Studies, 46(5), 1505–1516. https://doi.org/10.1111/ijcs.12861
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Revista TSup

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Authors who publish in this journal retain their copyright and, at the same time, grant the publication the right of first distribution of their work under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. This license allows third parties to share, copy, redistribute, adapt, and reuse the content in any medium or format, even for commercial purposes, provided that the original authorship is properly acknowledged, the source of publication is indicated, and any modifications made are noted.
