Abstract
Background
Traditional educational methods often fail to adequately impart practical skills or foster initiative, highlighting the need for innovative teaching approaches. Ebbinghaus’ memory curve demonstrates a pattern of rapid forgetting, suggesting that incorporating this principle into education may improve outcomes. However, research on its application in medical training remains limited.
Method
This prospective study enrolled 43 fifth-year students from the eight-year medical program at Sun Yat-sen University’s School of Medicine. Following randomization, students were allocated to either a traditional Case-Based Learning (CBL) group or a CBL combined with Metronomic Online Classroom (CBL + MOC) group. Both groups completed courses on thoracic trauma and closed chest drainage. Baseline assessments were conducted to confirm group comparability. After the intervention, students’ exam performance and self-confidence were measured, and subjective course satisfaction was evaluated.
Results
Compared with the CBL group, students in the CBL + MOC group achieved significantly higher exam scores (102.50 ± 19.66 vs. 86.58 ± 24.95, p = 0.04), particularly in mastery of fundamental knowledge (39.38 ± 7.04 vs. 33.16 ± 8.37, p = 0.02). The CBL + MOC model did not significantly improve self-confidence. However, missing offline CBL sessions was associated with reduced self-confidence (p = 0.01), especially in communication, collaboration, and critical thinking. Course satisfaction was unaffected by the teaching model.
Conclusion
The CBL + MOC model enhances students’ academic outcomes more effectively than traditional CBL while maintaining course satisfaction. Nonetheless, offline CBL remains vital for sustaining self-confidence, particularly in skills central to medical practice.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12909-025-08427-6.
Keywords: Ebbinghaus’ memory curve, Case-Based learning, Online teaching
Background
In cardiothoracic surgery education, particularly for topics such as thoracic trauma and closed chest drainage, students must develop a strong foundation in anatomy, physiology, and clinical skills to meet the demands of managing emergencies. However, traditional educational methods may no longer fully meet these needs in the evolving landscape of medical training. This highlights the importance of adopting more innovative and flexible teaching approaches to help students master and apply critical knowledge effectively.
Multiple teaching models have been applied in medical education, including traditional Lecture-Based Learning (LBL) and Problem-Based Learning (PBL) [1, 2], as well as derivative approaches such as Case-Based Learning (CBL), Team-Based Learning (TBL), and Inquiry-Based Learning (IBL) [3–5]. At the School of Medicine, Sun Yat-sen University, CBL is widely implemented. This method employs clinical cases to contextualize learning, and its alignment with real-world patient assessment allows early-career clinicians to approach cases with greater confidence [3]. However, a central challenge in CBL is the demand for instructors to carefully design cases and guide students through structured analysis [6]. Over time, the long-term adoption of CBL has led to increasingly standardized and refined case development.
Advances in information technology have also reshaped medical education. Online modalities now include video-based instruction, interactive platforms, and social media–driven teacher-student communication. The global adoption of online teaching was further accelerated by the COVID-19 pandemic [7, 8].
Given the trade-offs across teaching models—offline classrooms being limited by time, space, and resource efficiency, and online instruction facing challenges such as reduced interaction and lower satisfaction—blended online-offline approaches have attracted growing interest. Therefore, investigating the integration of online and offline teaching is a critical next step in advancing medical education [9, 10].
Ebbinghaus’ memory curve, developed by German psychologist Hermann Ebbinghaus in the late 19th century, arose from his experiments on memory processes, particularly the rate of forgetting. His work revealed a fundamental characteristic of human memory: the rapid decay of information [11, 12]. Spaced repetition, a well-established learning strategy rooted in cognitive psychology, aims to optimize long-term memory retention by scheduling reviews of content at progressively longer intervals. This theoretical basis aligns directly with Ebbinghaus’ memory curve. Although spaced repetition has been applied in medical education, most implementations take the form of flashcard resources, which provide limited student–teacher interaction [13, 14].
By leveraging online educational tools, virtual classrooms can be designed to align interventions with key time points along the memory curve, guiding students to consolidate knowledge through a structured “metronomic” trajectory. This approach supports stronger long-term retention while overcoming the scheduling and location constraints of traditional offline classrooms. However, given the characteristics of the memory curve, excessive online content should be avoided, as it may increase students’ cognitive burden. Protecting medical students’ rest time is crucial: this not only prevents fatigue-related inefficiency and learning aversion but also promotes consolidation of long-term memory and sustainable learning outcomes [15].
Currently, there is limited research evaluating the effectiveness of this combined teaching model. Therefore, this study investigates whether integrating CBL with a metronomic online classroom enhances the effectiveness of teaching thoracic trauma and closed chest drainage in cardiothoracic surgery education. By merging CBL with this innovative online approach, we aim to provide a more engaging and efficient learning experience while extending students’ retention of key knowledge.
Methods
Teaching topic
The teaching content focused on thoracic trauma and closed chest drainage.
Main teaching model in our research
The offline CBL class is a widely used medical education model at the School of Medicine, Sun Yat-sen University. Its implementation followed these steps: instructors prepared clinical cases related to thoracic trauma and closed chest drainage, then notified students to preview the relevant material in textbooks. During class sessions, instructors and students jointly analyzed the cases, discussed diagnoses, and formulated treatment plans. At the conclusion of the case analysis, the instructor summarized the core teaching content to reinforce students’ retention of key knowledge.
The Metronomic Online Classroom (MOC) is an online platform created for students, using WeChat groups as the foundation for knowledge sharing and real-time discussion. It includes sharing clinical cases, providing lecture recordings, and supporting a paced teaching approach. In this metronomic model, after each offline CBL class, teachers pushed course-related tweets, videos, and case analyses to students via the online platform, timed according to Ebbinghaus’ memory curve to encourage review at critical intervals. Both students and teachers accessed the MOC platform. Teachers uploaded resources, shared review materials, and answered questions, while students used the platform to access content, participate in discussions, and post academic queries.
Sample enrollment
The sample size was estimated for a fully randomized, two-group design using the following formula:
 |
Where:
n = total required sample size (for both groups).
Zα/2 = critical value of the standard normal distribution corresponding to the Type I error rate (α).
Z1−β = critical value of the standard normal distribution corresponding to the statistical power (1 − β).
σ = estimated standard deviation of the primary outcome (exam scores).
δ = meaningful mean difference in the primary outcome (exam scores) between groups.
The Type I error rate (α) was set at 0.05, and statistical power (1 − β) at 0.8. The standard deviation (σ) of exam scores was set at 10, based on historical data from previous identical course exams at our institution. The meaningful mean difference (δ) was also set at 10. This calculation indicated a minimum of 16 students per group (rounding 15.68 up to the nearest integer), for a total required sample size of at least 32 students.
This study ultimately included 43 medical students from the School of Medicine, Sun Yat-sen University. Participants were in the fifth year of an eight-year medical education program and remained in the pre-clinical phase, having not yet begun clinical training.
Inclusion criteria
Chinese nationality with Mandarin as a native language.
Proficiency in smartphone use and the ability to engage in online learning and testing.
No visual, auditory, or language impairments.
Exclusion criteria
Prior professional training in thoracic trauma and closed chest drainage.
Repeating a year.
As these students were still in the pre-clinical stage and had not received systematic training in thoracic trauma or closed chest drainage, their baseline knowledge levels were expected to be consistent. The course also provided supplementary knowledge in this field, serving a dual purpose.
All students volunteered to participate and signed written informed consent forms. During tests and questionnaire assessments, participants remained anonymous to ensure that involvement did not affect semester evaluations or grades. Ethical approval was obtained from Gulf Medical University, UAE (Number: IRB-COM-MHPE-STD-69-APRIL-2023).
Randomization
Randomization was conducted using computer-generated random numbers assigned to each student. Students were then sorted by the magnitude of these numbers. The first 22 students were allocated to the traditional CBL group, and the remaining 21 students to the CBL + MIC group.
Evaluation indicators
The primary outcome was exam score, a widely used and intuitive measure of students’ learning outcomes. Secondary outcomes included self-confidence scores and subjective satisfaction. Self-confidence scores assessed students’ confidence levels across multiple dimensions. Subjective satisfaction was also treated as a key indicator of the effectiveness of the educational model, as higher satisfaction generally reflects stronger course design and greater student engagement.
Pre-course baseline assessment and End-of-Course evaluation method
Both the pre-course baseline assessment and the end-of-course evaluation were administered as online quizzes to ensure convenience and accessibility. The questionnaires used for student assessments were in Chinese, while English versions of all items were provided in the supplementary materials.
The pre-course baseline assessment included two components: a knowledge test and a confidence evaluation. The confidence questionnaire was adapted from Bray et al.’s study and measured students’ confidence in six domains: collaboration, communication, creativity and innovation, self-direction, critical thinking, and use of technology [16].
The end-of-course assessment consisted of 30 single-choice questions: 10 tested basic knowledge and 20 tested case analysis, all relating to thoracic trauma and closed chest drainage. The questions were developed by senior thoracic surgeons at the First Affiliated Hospital of Sun Yat-sen University. They were aligned with course content and formed part of the evaluation for residents’ clinical competency. The end-of-course confidence assessment used the same scale as the pre-course evaluation.
Subjective satisfaction ratings were scored on a 5-point scale: 1 = “very dissatisfied,” 2 = “dissatisfied,” 3 = “neutral,” 4 = “satisfied,” and 5 = “very satisfied.” Higher scores indicated greater student satisfaction with the course. All online assessments were administered via the Chinese version of the Questionnaire Star mobile application. The entire questionnaire content is provided in the supplementary materials.
Procedure
Students in the traditional CBL group were notified one week in advance to prepare relevant knowledge on thoracic trauma and closed chest drainage. Before attending the class, they completed a knowledge assessment and a self-confidence questionnaire. One week later, they participated in the offline CBL class, where instructors presented clinical cases for group discussion. One month after the course, students completed a post-course knowledge assessment and a follow-up self-confidence evaluation.
Students in the CBL + MOC group also self-studied the assigned content one week before the course and completed the same baseline knowledge test and self-confidence questionnaire as the CBL group. They then attended the offline CBL class together with students from the traditional CBL group, as both groups were mixed during the in-person session. Afterward, a teaching secretary created a dedicated WeChat group for CBL + MOC participants. At key time points corresponding to Ebbinghaus’ memory curve (days 1, 2, 4, 7, and 15 after class), the secretary shared course slides, knowledge summaries, lecture recordings, and real clinical case analyses to prompt scheduled review. Students were able to engage in online discussions, provide feedback, and communicate with peers and instructors through the WeChat group at any time. One month after the course, these students completed the same post-course assessment and self-confidence evaluation as the traditional CBL group (Fig. 1).
Fig. 1.
The flow chart of this study
Statistical analysis
Student’s t-test was used to compare differences in indicators between the two groups. Pearson correlation analysis was applied to examine the association between students’ confidence scores and their final exam scores. Statistical significance was defined as p < 0.05.
The reliability of the questionnaire was assessed using Cronbach’s alpha, with values greater than 0.7 considered acceptable. The Bootstrap method was applied to calculate the 95% confidence interval (CI) for Cronbach’s alpha.
All statistical analyses were conducted using R version 4.3.1, and selected visualizations were generated with the SangerBox 3.0 platform.
Results
Baseline assessment
This study ultimately included 43 medical students from the School of Medicine, Sun Yat-sen University. All students met the inclusion criteria and completed the baseline assessment. Of these, 22 students were assigned to the traditional CBL group and 21 to the CBL + MOC group. The demographic characteristics of participants are presented in Table S1.
The results showed no significant differences between the two groups in theoretical knowledge of thoracic trauma and closed chest drainage (p = 0.75). Similarly, no statistically significant differences were observed in confidence scores, either across the six individual categories or in the total confidence score (Fig. 2). Cronbach’s alpha for the confidence questionnaire was 0.9, exceeding the acceptable threshold of 0.7 and demonstrating high reliability.
Fig. 2.
The results of the pre-assessment baseline for two groups of students after randomization. The numerical values above the image indicate the p-values from the t-tests between the two groups. A Comparison of the mastery of basic thoracic surgery knowledge between the two groups. B Comparison of the overall confidence scores of students in the two groups. C Comparison of the confidence scores in collaboration, communication, Creativity, and Innovation among students in the two groups. D Comparison of the confidence scores in self-direction, critical thinking, and the use of technology among students in the two groups
Examination performance assessment
Of the 43 enrolled students, four did not complete the online test on the scheduled day: one in the traditional CBL group and three in the CBL + MOC group. Among the 39 students who completed the test, 21 were in the traditional CBL group and 18 in the CBL + MOC group.
The total average score for the CBL + MOC group (101.11 ± 24.41) was higher than that of the traditional CBL group (87.14 ± 29.90), although the difference was not statistically significant (p = 0.12). However, when extreme values were removed, the difference reached statistical significance, with the CBL + MOC group (102.50 ± 19.66) outperforming the traditional CBL group (86.58 ± 24.95; p = 0.04).
Further analysis showed that this improvement was particularly evident in basic knowledge mastery (p = 0.02), whereas no significant difference was observed for case analysis performance (p = 0.14) (Fig. 3).
Fig. 3.
The comparison of exam scores between the two groups. The x-axis represents different types of sections in the exam paper. The p-values are annotated above the image. A Primary results. B Excluding the highest and lowest scores from each group’s exams
Confidence scores
Comparisons of self-confidence scores between the CBL + MOC group and the traditional CBL group revealed no significant differences, either in total scores or across the subcategories of self-confidence. Correlation analysis between students’ self-confidence scores and exam performance showed a positive correlation (r = 0.15), although this was not statistically significant (p = 0.37).
Pre- and post-course comparisons of self-confidence scores within both groups indicated that participation in either CBL or CBL + MOC led to modest increases in average self-confidence. However, these improvements did not reach statistical significance (Table S2 and Table S3).
The reliability of the self-confidence questionnaire was high, with Cronbach’s alpha of 0.971 and a 95% CI of 0.949–0.984, confirming excellent internal consistency (Fig. 4).
Fig. 4.
Comparisons of self-confidence scores between the two groups after the conclusion of the course, with the x-axis representing different types of self-confidence assessments. The p-values are annotated above the image. A Comparisons of self-confidence scores in Collaboration, Communication, Creativity, and Innovation between the two groups. B Comparisons of self-confidence scores in Self-direction, Critical Thinking, and Use of Technology between the two student groups. C A comparison of the overall self-confidence scores between the two student groups. D Correlation analysis between students’ overall self-confidence scores and exam performance
Impact of offline course participation
Seven students were unable to attend the offline course: two from the traditional CBL group and five from the CBL + MOC group. To evaluate the impact of offline participation on learning outcomes, we compared these seven students with the 36 students who attended.
The results showed no significant difference in exam scores between attendees and non-attendees (p = 0.84), including in basic knowledge mastery (p = 0.65) and case analysis performance (p = 0.76). However, the average scores of students who participated in offline classes were higher overall (Fig. 5A).
Fig. 5.
The impact of participation in offline Case-Based Learning (CBL) classes on students’ performance and self-confidence. The x-axis represents different types of exam question scores or various self-confidence assessments. The p-values are annotated above the image. A Comparisons of exam scores between the two groups. B A comparison of the overall self-confidence scores between the two groups. C Comparisons of self-confidence scores in Collaboration, Communication, Creativity, and Innovation between the two groups. D Comparisons of self-confidence scores in Self-direction, Critical Thinking, and Use of Technology between the two groups
In contrast, participation in offline CBL classes was associated with significantly higher self-confidence scores (65.63 ± 16.31) compared with non-participation (50.43 ± 11.50; p = 0.01). Subscale analysis further revealed that students attending offline classes scored significantly higher in collaboration (p = 0.02), communication (p = 9.40E − 03), and critical thinking (p = 2.50E − 03). No significant differences were observed in creativity and innovation (p = 0.13), self-direction (p = 0.11), or technology use (p = 0.10) between participants and non-participants (Fig. 5B–D).
Comparison after excluding students who did not participate in offline CBL classes
As students who did not attend offline CBL sessions were unevenly distributed between the traditional CBL and CBL + MOC groups, their inclusion risked introducing bias. To reduce the influence of offline participation on self-confidence outcomes, these students were excluded from analysis.
Comparisons between the traditional CBL group and the CBL + MOC group showed no significant differences in either overall self-confidence scores or individual subcategories. However, the CBL + MOC group had a higher mean self-confidence score (69.31 ± 12.36) compared with the traditional CBL group (63.11 ± 18.43), though the difference was not statistically significant (Fig. 6A–C).
Fig. 6.
Comparisons of self-confidence scores between the two groups after excluding students who did not participate in offline classes, along with an assessment of overall subjective satisfaction with the course for all students. The p-values are annotated above the image. A Comparisons of self-confidence scores in Collaboration, Communication, Creativity, and Innovation between the two student groups. B Comparison of self-confidence scores in Self-direction, Critical Thinking, and Use of Technology between the two groups. C A comparison of the overall self-confidence scores between the two student groups. D An assessment of subjective satisfaction with the course by students in both groups
Course satisfaction
Subjective satisfaction ratings were collected to assess student perceptions of the two teaching models. In the traditional CBL group, nine students reported being “very satisfied,” nine were “satisfied,” and three rated the course as “average.” In the CBL + MOC group, 11 students were “very satisfied,” five were “satisfied,” one rated the course as “average,” and one did not provide a rating.
Although a higher proportion of students in the CBL + MOC group reported being “very satisfied,” the difference in satisfaction ratings between groups was not statistically significant (p = 0.17) (Fig. 6D).
Discussion
Using a completely randomized design, this study compared the teaching effectiveness of the CBL + MOC model with the traditional CBL model. The results showed that the CBL + MOC model produced superior exam performance. Furthermore, students who attended offline courses demonstrated higher self-confidence scores.
In recent years, following the introduction of the PBL teaching model, several new instructional approaches—including CBL, TBL, and related models—have been applied in medical education. At Sun Yat-sen University, CBL has been widely implemented after years of practice. Compared with the traditional LBL model, CBL, which is grounded in real clinical cases, provides students with a more vivid and tangible understanding of knowledge and improves course effectiveness [17]. Nevertheless, several researchers have observed that CBL can further be strengthened when combined with other teaching methods. For example, some studies have reported enhanced outcomes when integrating CBL with PBL, or combining PBL with both CBL and TBL [6, 18, 19]. While such blended models promote learning, they also impose heavy demands on students, who must dedicate significant time to pre-class preparation and post-class review. In parallel, educators must adapt to shifting roles across multiple teaching modes, often leading to fatigue. Although the novelty of alternating teaching methods may temporarily improve student engagement, it does not necessarily foster the development of stable, long-term learning patterns. Given the already intensive medical curriculum, highly complex models may be impractical for daily teaching. Thus, while multi-model approaches offer certain benefits, more feasible, less burdensome innovations are needed to improve educational outcomes.
Our exploration of teaching model reform was driven by the practical challenge of students’ knowledge retention. By integrating interventions based on Ebbinghaus’ memory curve, we found that the CBL + MOC approach was effective. Students in the CBL + MOC group achieved significantly higher exam scores compared with the traditional CBL group. This improvement likely stemmed from stronger mastery of fundamental knowledge, as no significant differences were observed in case analysis. These findings suggest that case analysis—being a core element of CBL—may already be effectively reinforced in offline sessions, reducing the likelihood of forgetting diagnostic and treatment processes. In contrast, theoretical knowledge and abstract concepts are more vulnerable to forgetting in the absence of repeated exposure. From this perspective, the CBL + MOC model may be particularly effective for courses emphasizing theoretical knowledge. Spaced repetition aligned with the Ebbinghaus’ curve has gained growing attention in medical education. For instance, Zachary et al. developed a spaced repetition model to support plastic surgery education [20] and Femi et al. implemented flashcards to improve microbiology learning—both reporting positive outcomes [14]. Together, these findings support the unique value of spaced repetition, consistent with the Ebbinghaus’ curve, in strengthening long-term retention within medical education.
Notably, we did not observe a significant improvement in students’ self-confidence under the CBL + MOC model, despite higher average scores compared with the traditional CBL group. Because of the uneven distribution of students who missed offline CBL classes, we re-analyzed outcomes after excluding non-participants. However, the results remained non-significant. One explanation may be a ceiling effect: as shown in the baseline characteristics, self-confidence levels were already relatively high (mean ± SD: 57.45 ± 18.56 in the CBL group and 58.57 ± 16.30 in the CBL + MOC group). In addition, the short duration of the program (one month) may have limited observable changes. Building students’ self-confidence is a long-term process, and future studies with extended follow-up periods may provide more reliable evidence on the impact of this intervention.
We also found that participation in offline CBL classes did not appear to influence students’ knowledge mastery, which is consistent with findings from other studies. For example, Peter Nicklen et al. compared face-to-face and online CBL, reporting both formats to be equally effective [21]. Similarly, Aileen Wai-Kiu Chan conducted a controlled trial with Chinese nursing students and found comparable efficacy between online and traditional CBL methods [22]. These results may reflect students’ strong self-directed learning abilities, which help compensate for the absence of direct face-to-face interaction with instructors.
By contrast, offline participation was closely related to self-confidence outcomes, particularly in collaboration, communication, and critical thinking. This highlights the unique value of offline classes, where direct interaction among peers and between students and teachers fosters essential collaborative and communicative skills. In offline sessions, teachers can guide students toward efficient problem-solving strategies. However, students who do not attend offline classes may take more circuitous approaches without such guidance, resulting in additional time expenditure and a subsequent decline in self-confidence. In this study, self-confidence scores showed a positive—but non-significant—correlation with exam performance, possibly due to the limited sample size. While short-term experiments may not capture performance decline, reduced self-confidence could have negative long-term effects on academic achievement and competence. From our perspective, students who miss offline classes may also experience feelings of guilt, which could lower their willingness to seek help from teachers. This, in turn, may prolong learning time, heighten frustration, and further erode self-confidence. Artificial intelligence (AI) may offer a partial solution to this issue, given its accessibility and capacity for data storage. However, AI use in medical education faces challenges, including inaccurate responses, privacy risks, and ethical concerns [23–25]. At present, offline CBL remains indispensable, reinforcing the importance of a blended approach that integrates both offline and online components.
Electronic devices and the internet have become indispensable in daily life, providing access to abundant online educational resources. Therefore, the integration of information technology into teaching has become a prevailing trend. With the widespread use of communication tools such as WeChat and QQ, interpersonal connections have become more convenient, and group chat functions offer efficient platforms for online discussions. Compared with traditional email, which transmits information more slowly and limits timely communication, instant messaging tools enable real-time interaction, facilitating prompt problem-solving and immediate feedback. Group chat functions also promote collaboration, allowing students to exchange opinions collectively, thereby strengthening teamwork and improving learning outcomes. In addition, these tools foster stronger teacher-student interaction by providing opportunities for more personalized guidance. In our study, students appeared to prefer the CBL + MOC model, possibly because the MOC platform enhanced communication between teachers and students. The online system allowed for immediate inquiries and discussions, which proved highly beneficial for learning. Importantly, the use of MOC did not impose additional study burdens. Students were only required to review the materials pushed by the teaching secretary, and because these could be accessed without strict time constraints, the process was convenient for students already proficient in smartphones and other digital devices. As a result, the CBL + MOC model may be easily accepted and widely adopted in similar educational contexts.
Limitations
This study has some limitations. First, because it was conducted at a single center with a relatively small sample size, the generalizability of the findings to other institutions may be limited. Second, students in the two groups may be friends or acquaintances outside of the teaching setting, leading to casual, unplanned interactions after class. Such spontaneous communication—not structured sharing of learning materials between groups—may then have narrowed the differences between the two groups. Third, given the challenges of implementing new teaching methods and the complexity of resource allocation, the present comparison of teaching models relied on a limited sample size. Future studies with larger cohorts across multiple centers are needed to validate and extend these findings.
Conclusions
This study demonstrates the potential of the CBL + MOC model to enhance retention of fundamental knowledge, while underscoring the critical role of offline classes in developing collaboration, communication, and critical thinking skills. Our findings also highlight the growing importance of information technology in medical education. Platforms such as WeChat provide rapid feedback, promote collaboration, and offer personalized guidance, supporting more effective and engaging learning experiences. Looking forward, the continuous evolution of blended learning approaches and the integration of digital technologies will play an increasingly central role in shaping medical education in Chinese universities. Addressing the limitations of emerging models and strategically applying information technology will be essential for advancing educational reform and ensuring sustainable improvements in medical training.
Supplementary Information
Acknowledgements
The authors thank Professor David Taylor for his guidance and Professor Trevor Gibbs for his input. We are grateful to all the teachers at Gulf Medical University and the First Affiliated Hospital of Sun Yat-sen University for their suggestions and support, and to all student participants for their contributions. We also thank Editage (www.editage.cn) for professional English language editing.
Abbreviations
- LBL
Lecture-Based Learning
- AI
Artificial Intelligence
- CBL
Case-Based Learning
- CI
Confidence interval
- COVID-19
Coronavirus Disease 2019
- IBL
Inquiry-Based Learning
- MOC
Metronomic Online Classroom
- PBL
Problem-Based Learning
- TBL
Team-Based Learning
- VBL
Video-Based Learning
- WBL
Web-Based Learning
Authors’ contributions
**FHZ and WL: ** Conceptualization, data curation, methodology, software, investigation, visualization, writing-original draft, writing-review and editing.**XZ, TZ, YS, and RH: ** Data curation.**YFF and YYL: ** Conceptualization, writing-review and editing, and supervision.
Funding
This work was supported by grants from the “New Medicine” teaching reform project in Guangdong province, 2023.
Data availability
All data generated or analyzed during this study are included in this published article and its supplementary information files. Additional information required to reanalyze the findings of this study is available from the corresponding author ([leiyiyan@mail.sysu.edu.cn](mailto: leiyiyan@mail.sysu.edu.cn)) upon reasonable request.
Declarations
Ethics approval and consent to participate
The authors confirm that the study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments. This Study Received Ethical Approval from the Institutional Review Board of Gulf Medical University (IRB Number: IRB-COM-MHPE-STD-69-APRIL-2023). Written Informed Consent Was Obtained from All Participants.
Consent for publication
Not Applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Fei-Hang Zhi and Wei Liu contributed equally to this work.
Contributor Information
Yan-Fen Feng, Email: fengyf@sysucc.org.cn.
Yi-Yan Lei, Email: leiyiyan@mail.sysu.edu.cn.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All data generated or analyzed during this study are included in this published article and its supplementary information files. Additional information required to reanalyze the findings of this study is available from the corresponding author ([leiyiyan@mail.sysu.edu.cn](mailto: leiyiyan@mail.sysu.edu.cn)) upon reasonable request.