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With the expansion of online education, particularly after the COVID-19 pandemic, self-directed learning (SDL) has been recognized as factors in success in digital learning environments. However, within the Persian-speaking community, there is no standardized and validated tool to assess this construct in online settings. To address this issue, this study culturally adapted the Self-Directed Online Learning Scale (SDOLS) into a Persian version (SDOLS-P) and psychometrically validated it for use among medical science students in the new context. This cross-sectional methodological study was conducted on 250 students of medicine, nursing, and midwifery from Tehran and Hamadan Universities of Medical Sciences in Iran. The sample was divided into two independent subsamples, with 125 participants for exploratory factor analysis (EFA) and 125 for confirmatory factor analysis (CFA). The scale adaptation and psychometric validation process included the following steps: translation and back-translation of the scale, assessment of face and content validity (qualitative and quantitative), identification of construct validity (exploratory and confirmatory factor analyses), and reliability testing (Cronbach’s alpha and intraclass correlation coefficient). Data were analyzed using SPSS Statistics (Version 24) and AMOS (Version 24). The scale demonstrated acceptable face and content validity (CVR > 0.62 and CVI = 0.94). The overall reliability of the scale was confirmed with Cronbach’s alpha of 0.857 and ICC of 0.794. Exploratory factor analysis revealed two factors: autonomous learning (8 items) and asynchronous learning (9 items), which together explained 59.24% of the variance. Confirmatory factor analysis further supported the good fit of the two-factor model (CFI = 0.997, RMSEA = 0.003). The findings provide preliminary evidence of the validity and reliability of the Persian version of the Self-Directed Online Learning Scale (SDOLS-P) among medical sciences students from two Iranian universities. Further studies involving broader and more diverse student populations are needed to examine its measurement invariance and criterion and predictive validity.
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Pakrad et al. (2026) studied this question.
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