The Effectiveness of a Novel Android Application for Improving Deep Learning Approach among medical students: A Randomised Controlled Trial

Abstract

Background: Biggs defined learning approaches as the combination of motivation and strategy that students employ while studying, which might be "Surface" or "Deep". The Deep Learning technique entails the ability to connect new and old knowledge, the capacity to study thoroughly to get a "whole picture," and the skill to seek meaning and implications in what you have learned. The objective was to determine the effectiveness of an app-based intervention on improving Deep Learning approach among medical students. Methodology: A parallel-group, unblinded, Randomized Control Trial was conducted among the MBBS undergraduate students of a medical college in South India, using an android app based digital intervention. The Intervention Group was given the application for free that sends information and strategies for imparting Deep Learning approach daily for six weeks, followed by the assessment using the and assessed using R-SPQ-2F questionnaire in both groups. 

Result: Out of 140 participants, a highly significant (p<0.001) improvement of the mean Deep Motive score was observed in the Intervention group, after using the app, whereas the control group observed a significant reduction in their scores, which was statistically significant (p<0.001). The Deep Approach Score was also improved in the intervention group (p<0.001), whereas it declined over time in the control group. There was no significant association between sleep duration and learning approach. Overall, the use of the app reflected a statistically significant improvement in all three domains of Deep learning, such as Deep Motive, Deep Strategy, and Deep Approach in the Intervention group.

Conclusion: The intervention by the android application effectively imparted a Deep Learning Approach among medical students, with statistically significant improvements.

Keywords: Learning approaches, Surface learning approach, Deep learning approach, Deep strategy.