Self-directed learning readiness: re-examining dimensions in an online degree program in computer science

Background and context Online courses have become an integral part of higher education, requiring students to adapt to this evolving learning environment. However, completing an entire degree online demands specific competencies and a certain level of preparedness. One important aspect of this preparedness is self-directed learning readiness (SDLR).Objective This study identifies dimensions that reflect the manifestation of SDLR among computer science students enrolled in an online master’s program. Identifying dimensions can provide additional information about the construct and reveal context-specific characteristics.Method The methods contain confirmatory factor analysis (CFA) to validate the existing SDLR model and exploratory factor analysis (EFA) to extract new dimensions (factors). Descriptive analysis was performed for the new dimensions.Findings CFA showed that the original SDLR model’s factor structure did not fit this group of online computer science master’s students. EFA identified five factors. Two of these,self-managementanddesire for learning, were retained from the original model, while new factors self-efficacy, self-demandingness, and self-imposed learning emerged. The distributions of these factors revealed very high score levels, especially on the desire for learning and self-efficacy dimensions.Implications The identification of new dimensions suggests that self-directed learning readiness among online computer science students is more multifaceted than previously recognized. The study indicates that a high level of SDLR is required in the online computer science program, due both to the nature of the field and the responsibility placed on students for managing their own learning.