Domain Diversity, Motivation, Inclusion, and Feedback in Software Modelling Education
For educators in software modelling, this paper identifies specific disconnects between educator assumptions and student preferences regarding domain selection and feedback, offering actionable recommendations to improve student motivation and inclusivity.
This study surveyed 90 students and 22 educators to examine how problem domain diversity and teaching methods affect motivation, engagement, and inclusivity in software modelling education. It found that students are most motivated by socially relevant domains and prefer having a choice, while educators overestimate interest in study-related domains, and that feedback is perceived as meaningful when visibly acted upon.
Student engagement is critical for effective learning in software modelling, yet fostering motivation and inclusivity remains a challenge. While existing research has focused on modelling tools, notations, and assessment, little attention has been given to how the choice of problem domains and the diversity, relatability, and cultural perspectives they bring shape students' learning experiences. This study explores how problem domains and teaching methods influence motivation, engagement, inclusiveness, and feedback in modelling education. To investigate these dimensions, we conducted parallel surveys with 90 students and 22 educators. Our findings reveal disconnects between educator assumptions and student preferences: Students show greatest motivation for socially relevant domains and prefer choice in selection, while educators overestimate interest in study-related domains. The study identifies how minor design choices can exclude students. Students perceive feedback as meaningful when visibly acted upon. These findings suggest inclusive domain selection is central to student motivation; thus, we recommend student-centred domain selection.