The self-rating scale of self-directed learning tool: findings from a confirmatory factor analysis
KeywordsConﬁrmatory factor analysis, Construct validity, Healthcare students, Healthcare professionals, Instrument, Tool, Self-Directed Learning, Self-Rating Scale of Self-Directed Learning
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AbstractIntroduction: Healthcare students and professionals possess self-directed learning abilities at different levels of development. For educators, measuring these abilities allow to tailor teaching and mentoring interventions. The aim of this study was to validate the structure of the Self-Rating Scale of Self-Directed Learning, Italian version (SRSSDL-Ita). Methods: A cross-sectional study design was adopted involving a convenience sample of 593 healthcare students and professionals. A Confirmatory Factor Analysis was performed to confirm the validity of the measurement model of the original structure of the SRSSDL-Ita. Results: The Maximum Likelihood Meand-and-Variance (MLMV) to confirmatory factor analysis was used to examine the underlying latent variable structure of the SRSSDL-Ita, which was composed of 40 items. All standardized factor loadings were &gt; 0.42. Latent dimensions were all positively correlated, ranging in magnitude between 0.28 and 0.78. The Chi-square value for the overall model was χ2 (712) = 1,104.273 with p &lt; .001, Root Mean Square Error of Approximation (RMSEA) (90% confidence interval (CI)) = 0.031 (lower bound 0.027; upper bound 0.054) with p = 1.00, and Standardized Root Mean Square Residual (SRMR) = 0.055. The overall interpretation of the fit indices suggests a more than acceptable fit between the hypothesized model and the data. The emerged structure confirms the original structure of the instrument composed of eight factors: “Awareness”, “Attitudes”, “Motivation”, “Learning Strategies”, “Learning Methods”, “Learning Activities”, “Interpersonal Skills” and “Constructing Knowledge”. Conclusions: The SRSSDL-Ita structure was confirmed. Therefore, SRSSDL-Ita is a valid and practical tool that may contribute to determining learning needs among students and healthcare professionals; helping educators in identifying and implementing strategies to enhance SDL abilities in both groups.