Does Digital Pedagogical Competence Strengthen Teachers' Professional Competence in Deep Learning? Evidence from SEM Analysis

Abstract

Digital transformation in education requires teachers to combine professional competence with digital pedagogical competence to support meaningful learning. Deep learning, characterized by conceptual understanding, critical thinking, and knowledge transfer, has become a key goal of contemporary education, yet empirical evidence on the relationship among these competencies remains limited. This study examines the influence of digital pedagogical competence on teachers' professional competence, the effect of professional competence on students' deep learning, and the moderating role of digital pedagogical competence in this relationship. A quantitative approach using Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied. Data were collected through questionnaires from 30 teachers in two senior high schools in Sintang Regency, Indonesia, selected through purposive sampling. Data analysis included measurement model evaluation (validity and reliability) and structural model testing using path coefficients, coefficient of determination (R²), and bootstrapping. Digital pedagogical competence which nce significantly influences teachers' professional competence (β = 0.58, p < 0.001). Professional competence also has a significant positive effect on students' deep learning (β = 0.46, p < 0.001). Furthermore, digital pedagogical competence significantly moderates the relationship between professional competence and deep learning (β = 0.31, p = 0.008). The model explains 34% of the variance in professional competence and 49% of the variance in deep learning. The findings highlight the importance of strengthening digital pedagogical competence to enhance teachers' professional competence and support deeper student learning.