Validation and Evaluation of the Digital Competency Model of Teachers: A Structural Equation-Based Analysis

Document Type : Original Article

Authors

1 PhD student in Educational Management, Shahid Beheshti University, Tehran, Iran.

2 Assistant Professor, Department of Educational Sciences, Faculty of Psychology and Educational Sciences, Shahid Beheshti University, Tehran, Iran.

3 Associate Professor, Department of Educational Sciences, Faculty of Educational Sciences and Psychology, Shahid Beheshti University, Tehran, Iran.

Abstract

This study purposed to examine teachers’ digital competence and its impact on professional competence, pedagogical skills, and learners’ capabilities. The statistical population consisted of all teachers in Kurdistan Province who participated in the “Digital Literacy Project” in the year 1403-1404. Based on the list obtained from the Provincial Department of Education and using proportional stratified random sampling, a total of 400 teachers were selected as the sample. Data were collected using the European Framework for the Digital Competence of Educators (DigCompEdu) standardized questionnaire, whose validity and reliability have been confirmed in previous studies; in this research, Cronbach’s alpha coefficients exceeded 0.85. Data were analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). The results showed that the mean score of teachers’ digital competence was 3.84 out of 5, indicating a relatively high level. Among the dimensions, the highest mean was for “use and creation of digital resources” (4.02), and the lowest was for “assessment with digital tools” (3.65). The structural model indicated that digital competence had a positive and significant effect on professional competence (β = 0.47, p < 0.001), pedagogical competence (β = 0.42, p < 0.001), and learners’ capabilities (β = 0.39, p < 0.001). Moreover, ANOVA results revealed a significant difference in digital competence levels across age groups (F = 6.21, p < 0.01), with younger teachers scoring higher on average. These findings highlight the importance of investing in technological infrastructure, targeted training programs, and the development of teachers’ digital skills to enhance the quality of teaching and learning processes.

Keywords

References

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History

  • Receive Date: 03 April 2025
  • Revise Date: 11 August 2025
  • Accept Date: 21 September 2025
  • First Publish Date: 21 September 2025
  • Publish Date: 23 September 2025

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