Improving Medical Education through Student Feedback: Key Factors Driving Response Rates in Online Student Evaluations of Teaching - An Extended Technology Acceptance Model

Introduction: Student evaluation of teaching (SET) provides medical faculties with an empirical foundation for evidence-based enhancement of teaching quality for both medical educators and coordinators. However, the transition from paper-based to online evaluation has led to a marked decline in response rates, undermining the reliability and validity of the data obtained. At Charité, a newly developed online tool was implemented, after which response rates increased substantially. This study aimed to identify technical, procedural, and motivational factors associated with higher response rates in SET by applying an extended version of the Technology Acceptance Model (TAM) that integrates Actual System Use (AU). Methods: A cross-sectional survey was conducted among medical students at Charité - Universitätsmedizin Berlin (n = 834). A custom questionnaire operationalized core TAM constructs (Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Behavioral Intention (BI)) alongside Intrinsic Motivation (IM), Extrinsic Motivation (EM), and Perceived Workload (PW). The instrument was first examined using exploratory factor analysis (EFA; n = 325) and subsequently validated through confirmatory factor analysis (CFA; n = 509). Structural equation modeling (SEM) was then performed on the CFA sample to test hypothesized relationships. AU was objectively measured via student response rates in SET. Results: The classical TAM structure was confirmed. IM influenced BI indirectly via PU, whereas EM had the strongest direct effect on BI and positively reinforced IM. PW negatively influenced PEOU. PW and IM did not directly significantly influence the students’ intention to participate in SET. Moreover, BI strongly influenced AU. Conclusion: Higher response rates in SET can be achieved through a user-friendly and useful evaluation system, strategically implemented incentives, and the avoidance of adverse processes such as excessive evaluation workload. Overall, the study provides practical guidance for designing inclusive and effective evaluation systems that support continuous improvement of teaching quality in medical education.