Code vs. Context: STEM Students' Resistance to Non-STEM Coursework

TL;DR

This study investigates why engineering students resist mandatory non-STEM coursework by testing a regression-based model that includes Cognitive Switching Cost, Work Overload, and Role Ambiguity as antecedents to Affective Resistance, Willingness to Engage, and Long-Term Adoption of soft skills. Using a cross-sectional survey of 212 CS/Engineering undergraduates in Bangladesh, the authors find that Role Ambiguity is the strongest driver of affective resistance, which in turn reduces willingness to engage and ultimately long-term adoption. The results reveal a clear sequential mechanism and offer practical curricular guidance to reduce ambiguity, align non-STEM content with engineering identity, and foster early engagement to boost long-term skill uptake. Overall, the work highlights identity alignment as a central factor in interdisciplinary education and provides a concrete pathway for improving the integration of soft skills into engineering curricula.

Abstract

Many STEM programs now require students to take non-technical courses to develop the soft skills necessary for professional practice, yet engineering students frequently resist this requirement. While prior research often attributes this resistance to heavy workloads, little is known about its cognitive and identity-related mechanisms. This study fills this knowledge gap by examining the effects of Cognitive Switching Costs, Work Overload, and Role Ambiguity on students' Affective Resistance to non-STEM coursework, as well as the subsequent impact on their Willingness to Engage and Long-Term Adoption of skills. We collected survey data from 212 undergraduate Computer Science and Engineering students and tested directional relationships using sequential OLS regression. Role Ambiguity emerged as the strongest predictor of Affective Resistance (beta of 0.47, p less than 0.001), exceeding the effects of Work Overload (beta of 0.20, p equals 0.007) and Cognitive Switching Cost (beta of 0.14, p equals 0.038). In turn, Affective Resistance significantly reduced Willingness to Engage (beta of -0.25, p less than 0.001), while Willingness to Engage served as a strong predictor of Long-Term Adoption (beta of 0.55, p less than 0.001). These results indicate that student resistance is driven primarily by the incongruence between non-technical content and students' emergent professional identities, rather than by cognitive effort or workload alone. To improve outcomes, curricula should focus on reducing role ambiguity by placing humanities and social science material in clear engineering contexts.