Abstract
BACKGROUND: Student evaluations of teaching (SET) are widely used in medical education as a tool to improve teaching quality. However, biases in SET can undermine their effectiveness. While numerous studies have explored bias factors in SET within higher education, few have specifically investigated these factors among medical students in China. This study aims to systematically explore the multidimensional causes of bias in Chinese undergraduate medical students' teaching evaluations. METHODS: A qualitative study was conducted using semi-structured interviews with medical students from a medical university in northern China. Participants were selected through purposive sampling to ensure diversity in gender, academic year, and major. Interviews were transcribed verbatim and analyzed using thematic analysis to identify themes and subthemes related to biases in teaching evaluations. RESULTS: The analysis revealed several key themes contributing to biases in SET among medical students: (1) Teacher-Student Interaction: High personal affinity of teachers led to positive bias, while strict classroom management and poor teacher-student relationships resulted in negative bias. (2) Aspects Related to Medical Students: Course attributes and personal interest influenced evaluations, with elective courses and low-interest subjects leading to arbitrary bias. Group influences, such as peer effects and conformity, also contributed to bias. (3) Evaluation System Factors: Doubts about the anonymity of the evaluation system and lack of timely feedback led to self-protective scoring behaviors and arbitrary bias. The presence of informal agreements between teachers and students introduced moral hazards that further skewed evaluations. CONCLUSIONS: Biases in medical students' teaching evaluations are multifaceted and can primarily be attributed to teacher-student interpersonal relationships, student perceptions, and systemic issues within the evaluation process. To enhance the objectivity and effectiveness of SET, it is essential to address these biases by reshaping students' understanding of evaluations, improving teacher-student communication, and establishing a digital evaluation system that ensures anonymity and timely feedback.