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Research Study – Published: May 26, 2026
Digital Pedagogical Skills, Self-Efficacy, and Teaching Effectiveness among Pre-Service Teachers: A Structural Equation Modeling Approach
Dr. P. Subramanian
ABSTRACT
The increasing integration of digital technologies in education has made digital pedagogical skills a fundamental competency for teachers. This study examines the influence of digital pedagogical skills on teaching effectiveness among pre-service teachers, incorporating digital self-efficacy as a mediating variable. A quantitative research design using Structural Equation Modeling (SEM) was employed. Data were collected from 250 pre-service teachers through validated instruments. The findings revealed that digital pedagogical skills significantly predict teaching effectiveness (β = 0.52, p < 0.001) and also influence self-efficacy (β = 0.60, p < 0.001), which in turn affects teaching effectiveness (β = 0.41, p < 0.001). The model demonstrated a good fit (CFI = 0.94, RMSEA = 0.05). The study highlights the importance of integrating digital pedagogy into teacher education programs and provides implications for curriculum design and policy development.
Keywords:
Digital Pedagogy, Teaching Effectiveness, Pre-Service Teachers, Self-Efficacy, SEM, Teacher Education
This is an Open Access Research distributed under the terms of the Creative Commons Attribution License (www.creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any Medium, provided the original work is properly cited.
How to cite this article: Subramanian, P. (2026).
Digital pedagogical skills, self-efficacy, and teaching effectiveness among pre-service teachers: A structural equation modeling approach.
Indian Educational Researcher, 19
(1), 44–54.
https://doi.org/10.34293/0974-2123.v19n1.005
Received: April 10, 2026;
Revision Received: May 20, 2026;
Accepted: May 26, 2026.
Responding Author: Dr. P. Subramanian |
ORCID:
https://orc-id.org/0000-0001-5586-6299
Article Overview:
ISSN: 0974-2123 |
DOI
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Published in Volume 19, Issue 1, January - June, 2026