Female Student Participation in Software Engineering Projects: Opportunities to Model Project Evaluation and to Improve Early Prediction of Teamwork Failure

Abstract

Software engineering project is the preferred mean to measure competency and practical skills among learners in IT-fields. This study investigates the opportunities to model software engineering project final evaluation and improve early prediction of academic software engineering project failure by considering female student participation as a teamwork member, regardless of being a teamwork leader or a teamwork regular member. Four distinct arrangements of software engineering development teamwork are advised and studied. Those arrangements range from female-less participation teamwork to female-dominated participation teamwork. Machine learning techniques are leveraged to build prediction models. Teams are evaluated from two distinct perspectives. First, software products submitted at the end of each project life cycle milestone, namely product perspective. Second, the degree of obeying the good practices of software engineering project development, namely process perspective. Results reveal significant differences due to female student participation. Arrangement of female-less participation attains the worst modeling and prediction performance compared to the other arrangements of female student participation.

Keywords: Gender diversity, E-learning, Software engineering, Project failure, Machine learning

DOI: 10.7176/JEP/11-35-06

Publication date: December 31^st 2020