Insufficient interaction and communication in pharmacology instruction—particularly after the outbreak of coronavirus disease 2019 (COVID-19), which forced rapid transitions to online teaching in medical schools—have resulted in suboptimal educational outcomes. To enhance learner engagement and interaction in both distance learning and face-to-face settings, innovative and interactive teaching strategies are urgently needed. Bullet screens were incorporated into pharmacology classes. Subsequently, a questionnaire survey was administered to first-, second-, and third-year pre-clinical undergraduate medical and nursing students at Shanghai Jiao Tong University School of Medicine between November 2020 and March 2022. The core characteristics, pedagogical effectiveness, and entertainment aspects of bullet screens were assessed. Responses to both structured and open-ended items regarding perceived advantages, limitations, and overall impressions were coded and analyzed, with comparisons conducted between medical and nursing student groups. Regarding fundamental attributes, bullet screens showed strong student acceptance, and this innovative format effectively facilitated classroom interaction. From the perspective of teaching effectiveness, bullet screens appeared to encourage deeper cognitive engagement. At the same time, students more often used bullet-screen messages to show agreement or support rather than to contribute new ideas or express dissenting opinions. The entertainment component of bullet screens was prominent. Differences observed between medical and nursing students may have been related to variability in idea generation, suggesting that appropriate guidance on bullet-screen usage is necessary. Bullet screens have the potential to be widely adopted as a supplementary instructional method to strengthen teacher–student interaction in both in-person classes and remote learning environments. They represent an engaging and useful aid in pharmacology education; however, several aspects of this tool require refinement before large-scale implementation.
