Reformulation of the K Coefficient for Expert Judgment Applied to Digital Teaching Competencies

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DOI: https://doi.org/10.6018/rie.679191
Keywords: evaluation, information and communication technologies, expert judgmentexpert judgment, expert competence coefficient

Supporting Agencies

  • Agencia Nacional de Investigación y Desarrollo (ANID)

Abstract

Expert judgment is a widely used technique to validate assessment, self-assessment, and self-perception instruments through informed item evaluation. The expert competence coefficient (K) combines self-assessment of knowledge and objective argumentation. It has been widely adopted in education and healthcare; however, its application as a simple, equally weighted average presents epistemological and statistical limitations due to its vulnerability to self-perception bias. A generalization of the K coefficient is proposed that incorporates a third component, referring to the expert's thematic proximity with differentiated weights for each dimension. An inferential model based on the beta distribution and the asymptotic normal approximation is integrated, allowing for the estimation of confidence intervals and significance tests on expert competence. It was applied in two contexts: a simulated case and a real-life validation study of an instrument on digital competencies in early childhood education. The analyses show that the traditional K coefficient overestimates competence compared to the generalized version. In the real-world case, the sample initially classified as valid under the fixed threshold of 0.8 is reduced by applying the proposed inferential criteria, increasing the accuracy of expert identification. A test for paired samples confirms significant differences between the two methodologies. The reformulation of the K coefficient improves the rigor, transparency, and validity of expert judgment by considering both objective and contextual criteria and by supporting decisions through statistical inference. The proposal offers a robust and adaptable framework for future validation processes in various disciplines.

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Published
06-05-2026
How to Cite
González Campos, J., Aspee, J. E., Silva Quiroz, J. E., & Matar-Khalil, S. (2026). Reformulation of the K Coefficient for Expert Judgment Applied to Digital Teaching Competencies. Revista De Investigación Educativa, (44). https://doi.org/10.6018/rie.679191
Issue
No. 44 (2026):
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