Design and Validation of an In-Service Training Model for Teachers in the Iranian Education System
Keywords:
Validation, Smart Management, Comprehensive Model, Professional Development, Iran’s Education System, Digital Learning, In-Service Teacher TrainingAbstract
The present study aimed to design and validate a comprehensive, indigenous, and smart model for in-service teacher training in Iran’s education system with an emphasis on digital learning, sustainable professional development, and smart educational management. This study employed an exploratory mixed-methods design of the instrument-development type. In the qualitative phase, Strauss and Corbin’s grounded theory approach was applied, and data were collected through 21 semi-structured interviews with teachers, school administrators, and educational experts selected via purposive sampling. Data analysis was conducted through open, axial, and selective coding procedures. In the quantitative phase, the statistical population consisted of teachers, administrators, and faculty members related to the education system, from whom 384 participants were selected using multi-stage sampling based on the Krejcie and Morgan table. The data collection instrument was a researcher-made 30-item questionnaire measured on a five-point Likert scale. Data were analyzed using SPSS, AMOS, and SmartPLS through confirmatory factor analysis and structural equation modeling. The qualitative findings led to the extraction of ten major categories, including smart professional needs assessment, advanced pedagogical design, digital-smart learning, smart innovative methods, sustainable professional development, smart educational evaluation, learning-oriented organizational support, networked professional participation, educational digital inclusion, and educational artificial intelligence literacy. “Smart management of in-service training” emerged as the core category. Confirmatory factor analysis demonstrated that all factor loadings were within acceptable ranges, confirming the adequacy of the measurement structure. The KMO value was 0.959 and Bartlett’s test was significant (p<0.001), indicating sample adequacy and suitability of the correlation matrix. Model fit indices also confirmed excellent model fit, including RMSEA=0.038, CFI=0.948, and TLI=0.960. Cronbach’s alpha, composite reliability, and average variance extracted values exceeded standard thresholds for all constructs, confirming the validity and reliability of the proposed model. The proposed model provides a comprehensive, indigenous, and digitally oriented framework for redesigning in-service teacher training programs in Iran. By emphasizing smart learning, professional collaboration, digital inclusion, and sustainable professional development, the model has the potential to enhance teachers’ professional growth and improve educational quality within the Iranian education system.
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