Exploring the Influence of Emotions on the Code Quality of Novice Programmers
Primary Investigator (PI) Name
Luisa Valentina Nino de Valladares
Department
SPCEET - Industrial and Systems Engineering
Abstract
Code quality is an important metric for the evaluation of software. Besides technical factors that affect the quality of code, such as clarity, maintainability, reliability, and security, behavioral factors such as motivation, communication, time management, and emotions can also impact the quality of code. Emotions can have a significant impact on an individual’s performance while performing a task such as writing code. This research investigates how novice programmers' emotions impact the quality of their code during Python development in an experimental setting. A relaxation technique was introduced to examine its potential influence on emotions and programmer performance. The study uses non-invasive EEG to measure activity in the left and right prefrontal cortex, often associated with emotions. Code quality is evaluated using the Code-based Deep Knowledge Tracing method. Surprisingly, initial findings suggest that positive emotions may lead to lower-quality code among novice programmers. Expanding upon this study may help establish this connection more firmly, as well as shed light on how negative emotions affect code quality and provide recommendations for placing programmers in different emotional states.
Disciplines
Industrial Engineering | Management Information Systems | Other Operations Research, Systems Engineering and Industrial Engineering | Systems Engineering
Exploring the Influence of Emotions on the Code Quality of Novice Programmers
Code quality is an important metric for the evaluation of software. Besides technical factors that affect the quality of code, such as clarity, maintainability, reliability, and security, behavioral factors such as motivation, communication, time management, and emotions can also impact the quality of code. Emotions can have a significant impact on an individual’s performance while performing a task such as writing code. This research investigates how novice programmers' emotions impact the quality of their code during Python development in an experimental setting. A relaxation technique was introduced to examine its potential influence on emotions and programmer performance. The study uses non-invasive EEG to measure activity in the left and right prefrontal cortex, often associated with emotions. Code quality is evaluated using the Code-based Deep Knowledge Tracing method. Surprisingly, initial findings suggest that positive emotions may lead to lower-quality code among novice programmers. Expanding upon this study may help establish this connection more firmly, as well as shed light on how negative emotions affect code quality and provide recommendations for placing programmers in different emotional states.