Integrating Data Science into Undergraduate Science and Engineering Courses through Discipline-specific Modules: The Students’ Perspective

Data science literacy is increasingly vital for undergraduate engineering and science students,yet questions remain about effective integration approaches across established curricula. Thisstudy investigates the impact of integrating discipline-specific data science modules into existingundergraduate STEM courses through a multi-university research-practice partnership fromstudent perspectives. Using mixed methods analysis of survey responses from 877 students andinstructors' grades and interviews across six courses and three universities, we examinedchanges in students' perceptions of data science and compared student and instructorperspectives. Results show significant increases in students' self-reported confidence, skills,interest, and motivation in data science after completing modules, with initial perception being thestrongest predictor of final perception. Analysis revealed general alignment between student self-assessments and instructor evaluations. Students highlighted benefits including real-worldapplications and career relevance, while identifying challenges with data science tools andvarying experience levels. These findings provide insights for engineering educators seeking tointegrate data science into their curricula.