Encouraging Growth in Programming Education: Does Growth Mindset Feedback Influence Learning?

Abstract

Tutoring systems enable individualized support for diverse learners. Feedback is one of the most influential factors shaping learning, yet the optimal form of feedback remains an open question. Growth mindset feedback emphasizes effort and the value of errors. It has shown promise in fostering growth mindset beliefs, academic performance, and persistence in classroom settings, though results for tutoring systems in mathematics remain mixed. Computer science may represent a particularly relevant domain for this type of feedback, given frequent errors, compiler messages, and iterative debugging, which demand both persistence and frustration tolerance. This study examined whether growth mindset feedback is effective in a tutoring system for computer science. In a controlled between-subjects experiment, 79 German secondary school students (aged 14 to 17 years) received either performance-based feedback (indicating the proportion of correct responses) or growth mindset feedback while learning code tracing. Performance, mindset beliefs, and self-efficacy were assessed pre- and post-intervention, with intrinsic motivation and coding experience included as covariates in robust regression models. No main effects of feedback type emerged on any outcome, and gender did not moderate these results. Exploratory moderation analyses, however, revealed a gender-specific pattern. Among female students with high coding experience and low intrinsic motivation, performance-based feedback was associated with positive effects on both performance and mindset beliefs, with no comparable effects for male students. These preliminary findings suggest that feedback effectiveness may depend on the interplay of gender, prior experience, and motivation, highlighting the need for future research into the underlying mechanisms.