Domain Diversity, Motivation, Inclusion, and Feedback in Software Modelling Education

2026-06-04

AI Summary

This study addresses the limited diversity and perceived relevance of problem domains in software modeling instruction, which often undermine student motivation and inclusivity. Through parallel surveys of 90 students and 22 instructors, combined with quantitative and qualitative analyses, it reveals a significant mismatch between instructor assumptions and student preferences: learners prioritize socially relevant problem contexts and value autonomy in topic selection. Furthermore, their sense of engagement markedly increases when they perceive their feedback has been explicitly incorporated. The work proposes a learner-centered strategy for selecting problem domains that foregrounds social relevance and autonomy as critical enablers of inclusive learning. It also highlights how seemingly minor instructional design choices can inadvertently foster exclusion, offering empirical insights and actionable guidance for improving pedagogical practice.

Abstract

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.

Problem

• Domain Diversity
• Motivation
• Inclusion
• Feedback
• Software Modelling Education

Innovation

• domain diversity
• student-centred design
• inclusive education
• motivation in modelling
• feedback perception