Readiness for self-directed learning among basic sciences medical students.

BACKGROUND

Self-directed learning is a required skill for medical students for remaining lifelong learners. This study focuses on measuring the readiness for self-directed learning of basic sciences medical students.

MATERIALS AND METHOD

In the second half of 2022, a descriptive cross-sectional study was conducted on 288 basic sciences medical students at Tabriz University of Medical Sciences in Iran. The students were selected using convenience sampling. The instrument used was Fisher's self-directed learning readiness (SDLR) scale consisting of "self-management", "desire for learning", and "self-control" domains. The data were analyzed by SPSS-25 and also by using descriptive statistics [mean, standard deviation (SD), median, frequency, and percentage] and inferential statistics techniques (Chi-square test and -test, ANOVA, and MANOVA). Statistical significance was set at < 0.05.

RESULT

The results revealed that the scores of 63.9% students were more than 150. Also, the mean total score of self-directed learning readiness was 152.98 (SD = 16.76), suggesting that the self-directed learning readiness of the students was high level. The highest score was for "self-control" (59.99 ± 6.95), followed by "desire for learning" (46.99 ± 5.64) and "self-management" (46.01 ± 7.07). The total SDLR score and its three sub-scales did not show any notable interdependence with student contextual factors (age, gender, marital and residential status). However, a higher cumulative grade point average (>17) showed a significant higher mean in the "self-management" domain of SDLR among medical students (F = 3.730; = 0.025).

CONCLUSION

To become life-long learners, self-directed learning is crucial for medical students. The basic sciences medical students participating in this study showed a high level of SDL readiness. Even though the students obtained the highest score for the self-control sub-scale, the desire for learning and self-management skills needs further improvement, which can be achieved through multi-disciplinary approaches.