Exploring the link between emotional states and coding task quality: a pilot study

Emotions play a crucial role in shaping cognitive performance, yet their influence on programing remains understudied. This pilot study investigates the relationship between emotional states and coding task quality. Ten participants completed a programing task while their brain activity was recorded using electroencephalography (EEG), with frontal alpha asymmetry (FAI) applied as a neural marker of emotional valence. Emotional self-reports were collected using the Scale of Positive and Negative Experience (SPANE), and coding quality was evaluated through a structured rubric. Preliminary findings indicate a potential association between FAI and coding performance, whereas self-reported affect showed weaker or inconsistent patterns. Given the small sample size (n = 10), these results should be interpreted as exploratory. Nevertheless, the study demonstrates the feasibility of integrating EEG-based emotional measures into software engineering research and lays the groundwork for larger-scale investigations into how emotions influence coding task quality.