Understanding resilience in programming: A scale adaptation and analysis of individual differences

Abstract

Resilience is a critical personality trait that allows one to deal with difficulties, learn from failures, and maintain a positive attitude during task performance. However, it has not been understudied in a complex and challenging educational domain. The current research intends to address this gap by analyzing the specific characteristics of resilient university students in programming education with two studies. The first study aimed to adapt the programming resilience (PR) scale into the Turkish context to measure this construct in a different setting. The internal structure of the scale with four dimensions (persistence, perceived value, difficulty cognition, incremental belief), was validated using a sample of 311 undergraduate students. The Cronbach's alpha of this scale (0.937) indicated high internal consistency. The second study sought to determine the effect of several learner characteristics on PR based on a larger sample (n = 657). The results revealed that PR did not differ significantly by gender. However, it was higher when the students were majoring in computer science, had more than three years of programming experience, and engaged with programming activities every day. Upon controlling the effect of demographics and programming experience and frequency, the multiple regression analysis showed that less avoidant problem-solving style, higher problem-solving confidence, and deep learning approach resulted in higher PR. Overall, this study enriches our understanding of PR by highlighting the impact of individual differences on PR. This study further offers valuable suggestions for researchers and practitioners to build more resilient classes in programming courses.