Understanding Student Evaluation of Teaching in Computer Science Courses

Abstract

Understanding student perceptions in higher education is vital for optimizing teaching and learning practices. This research explores the relationship between course characteristics, Student Evaluation of Teaching, and disciplinary differences, with a particular focus on Computer Science courses. Analyzing data from the second half of the 2022 semester at one university, the study investigates the impact of course level, type, and size on student evaluation scores. Additionally, it compares Computer Science courses to other disciplines, revealing key differences in student satisfaction and perceptions. Findings indicate that second-year courses received lower ratings, and theoretical courses in online formats received higher satisfaction than programming courses. Smaller course sizes correlated with higher scores across multiple aspects. However, Computer Science courses scored lower overall and in crucial areas compared to other disciplines, highlighting the need for tailored teaching strategies. This research underscores the importance of continuous assessment and adaptation in higher education to foster positive learning environments and improve student experiences.