Abstract
Objective
To address the challenges of spatial understanding and knowledge fragmentation in Histology and Embryology, this study aimed to develop and evaluate a 3D model–driven, clinically oriented, three-stage progressive teaching program and examine its association with students' academic performance and learning outcomes.
Methods
The teaching reform consisted of three components. First, the curriculum was restructured, namely teaching hours were reduced from 80 to 76. Second, a three-stage progressive teaching program was implemented, including a knowledge verification stage, namely concept mapping combined with slide observation; a preliminary exploration stage, namely 3D-printed models, AI-generated animations, and clay modeling; and a practical application stage, namely clinical cases and abnormal anatomical models. Third, a diversified assessment system was adopted, including formative assessment (25%), theoretical examination (55%), and practical laboratory examination (20%). The program was implemented among clinical medicine students from 2017 to 2023, with a total of 6,415 participants.
Results
From the Class of 2017 to the Class of 2023, mean examination scores showed a gradual upward trend: 65.54 (Class of 2017), 66.59 (Class of 2018), 67.84 (Class of 2020), 71.72 (Class of 2021), 72.66 (Class of 2022), and 75.53 (Class of 2023). The Class of 2019 (mean 83.17) was assessed under different instructional conditions during the COVID-19 pandemic and was therefore excluded from the analysis. In addition to examination scores, students also demonstrated improved spatial reasoning and clinical problem-solving abilities.
Conclusion
The 3D model–driven, clinically oriented, three-stage progressive teaching program may serve as a feasible framework for basic medical education reform by promoting the integration of theoretical knowledge, spatial understanding, and clinical application.
Keywords: Histology and Embryology, Three-stage progressive program, 3D model, 3D printing in education, Competency-based education, Clinical orientation, Formative assessment
Introduction
Histology and Embryology is a core component of the basic medical curriculum, focusing on the microscopic structure of the human body and its developmental processes. It provides essential foundational knowledge for subsequent courses such as anatomy, pathology, and clinical medicine [1]. However, this subject still faces several challenges. On the one hand, the reliance on two-dimensional (2D) representations makes it difficult for students to develop adequate spatial understanding. On the other hand, the content is often fragmented, which hinders the effective integration of basic knowledge with clinical application.
In recent years, a number of studies have explored the use of three-dimensional (3D) models, digital visualization tools, and innovative teaching strategies in medical education. These approaches have shown potential in improving student engagement and understanding, particularly in enhancing spatial cognition and clinical thinking. To address these two major problems, the teaching team developed a 3D model–driven, clinically oriented, three-stage progressive teaching program. This model integrates knowledge verification, spatial exploration, and clinical application into a structured learning process. It is designed to promote students’ abilities in knowledge integration, spatial reasoning, critical thinking, clinical reasoning, and scientific literacy [2].
Therefore, this study aimed to evaluate whether the implementation of a three-stage progressive teaching program was associated with improvements in students’ academic performance and learning outcomes.
Materials and methods
Analysis of teaching problems and strategy development
Based on our teaching experience and a review of student performance and feedback over multiple academic years, several challenges in Histology and Embryology teaching were identified. These challenges mainly relate to knowledge organization, spatial understanding, and clinical application.
To better align teaching strategies with these observed difficulties, the instructional team summarized the main problems and corresponding instructional adjustments. The results of this analysis are presented in Table 1.
Table 1.
Matrix of instructional problems and innovative strategies
| Main Problems | Adjustments |
|---|---|
| Fragmented knowledge and lack of systematic integration. | In the Knowledge Verification Stage, we reorganized fragmented concepts into a coherent framework. |
| Weak spatial imagination, dominated by 2D observation. | In the Preliminary Exploration Stage, we used 3D models, clay modeling, and AI-based animations to help students visualize structures and their functional relationships in space. |
| Insufficient clinical reasoning. | In the Practical Application Stage, we introduced clinical cases and abnormal anatomical models to strengthen clinical reasoning and bridge theory with practice. |
Teaching design and implementation
Curriculum reconstruction
The course structure was revised prior to implementation of the teaching program. The total number of teaching hours was adjusted from 80 to 76. In terms of content organization, the traditional tissue-based sequence was reorganized into a function and organ-oriented modular structure. This restructuring aimed to improve the integration of related topics and strengthen the linkage between structure and function.
Three-stage progressive teaching program
This program was implemented among clinical medicine students from 2017 to 2023, with a total of 6,415 participants. Across all cohorts, the proportion of male and female students was approximately 53% and 47%, respectively. The mean age of students at enrollment was from 18 to 19 years. All students enrolled in the course during this period were included in the analysis; no exclusion criteria were applied.
The program consisted of three sequential stages: (1) Knowledge Verification Stage: Students reviewed theoretical content through guided instruction, combined with microscopic slide observation and concept mapping, to strengthen knowledge integration. (2) Preliminary Exploration Stage: Students worked with 3D models to explore structural features and spatial relationships, fostering an understanding of structure and function correlations. Briefly, the model was constructed using 3ds Max 2025 software (Fig. 1A). Key optimization steps included: cutting the vascular plane to expose all internal structures, smoothing edges to enhance natural appearance, and strengthening the protrusions on the raised blood vessels. After modeling, print feasibility was assessed using Ultimaker Cura 5.7.0. The software's auto-detection function was used to verify model integrity and confirm that the model was suitable for printing (Fig. 1B). Due to printer build volume limitations and the irregular shape of the model, it was divided into multiple components for separate printing using Anycubic Slicer (the Anycubic Slicer Installer) (Fig. 1C). All components were printed using PLA filament (Anycubic). After printing, the parts were assembled and finished (Fig. 1D).
Fig. 1.
Development workflow of the 3D-printed glomerular filtration barrier model. A 3D modeling in 3ds Max 2025. B Print feasibility analysis in Ultimaker Cura 5.7.0. C Segmented model preparation in Anycubic Slicer. D Completed 3D-printed model (PLA filament, Anycubic). The model shows the spatial relationship among endothelial cells, basement membrane, and podocyte foot processes
In addition to the glomerular filtration barrier model, the instructional team developed a 3D-printed model of the liver lobule to illustrate hepatic microarchitecture and blood flow dynamics. The development workflow is shown in Fig. 2. The liver lobule model was constructed using 3ds Max 2025 software, with careful delineation of the central vein, hepatocyte plates, and the portal triad area (branches of the portal vein, hepatic artery, and bile duct) (Fig. 2A). The model was printed using PLA filament (Anycubic) on an FDM printer (Fig. 2B). After printing, supports were removed and the surface was smoothed to enhance clarity (Fig. 2C). To further facilitate understanding of hepatic blood flow, an LED strip light was embedded along the vascular pathways of the model. The LED strip was programmed to illuminate sequentially—starting from the portal triad (representing inflow of blood via the portal vein and hepatic artery) and progressing toward the central vein. This dynamic visualization (Fig. 2D) allows students to observe the direction of blood flow within the liver lobule in real time, reinforcing the concept that blood flows from the periphery of the lobule toward the central vein.
Fig. 2.
Development and functional demonstration of the 3D-printed liver lobule model for histology teaching. A 3D modeling in 3ds Max 2025. B 3D printing process. C Completed 3D-printed model. D Dynamic blood flow demonstration using LED strip lighting
Optimization of the teaching evaluation system
Student performance was assessed using a combination of formative and summative evaluation methods. The final grade consisted of formative assessment (25%), theoretical examination (55%), and practical (laboratory) examination (20%).
Formative assessment included chapter quizzes (8%), laboratory assignments (8%), model presentations (5%), drawing assignments (2%), and attendance and learning attitude (2%). These components were used to monitor students’ learning progress and participation throughout the course.
The theoretical examination evaluated students’ understanding of fundamental knowledge and their ability to analyze case-based questions. The practical examination focused on laboratory skills and spatial reasoning. This integrated approach combined knowledge-based, process-oriented, and competency-based assessments to support self-directed learning and continuous improvement.
In addition to assessment, formative evaluation was accompanied by structured feedback to support student learning. Feedback was provided through multiple channels, including instructor comments on assignments and model presentations, in-class discussions, and follow-up explanations after quizzes and laboratory sessions. This process enabled students to identify knowledge gaps, reflect on their performance, and adjust their learning strategies accordingly.
Results
Academic performance and learning behavior
From 2017 to 2023, all cohorts of clinical medicine students (classified by year of entry) were included in the analysis. Students’ academic performance data were obtained from the university’s official academic administration system.
Across these cohorts, the mean examination scores showed a gradual increase over time. The mean scores of clinical medicine students were 65.54 for the Class of 2017, 66.59 for the Class of 2018 and 67.84 for the Class of 2020, rising to 71.72 for the Class of 2021, 72.66 for the Class of 2022, and 75.53 for the Class of 2023. The Class of 2019 had a higher mean score (83.17), which may be related to the transition to online teaching during the COVID-19 pandemic (Fig. 3). This cohort was assessed under different instructional and examination conditions and was therefore excluded from the main descriptive analysis to avoid confounding. The results reported below are based on the remaining cohorts (2017, 2018, 2020, 2021, 2022, 2023) unless otherwise specified.
Fig. 3.
Trends in mean examination scores among clinical medicine students from 2017 to 2023. The line chart shows the mean examination scores of clinical medicine students across different cohorts (Class of 2017 to Class of 2023). A gradual upward trend in academic performance is observed over time. The Class of 2019 was excluded from the main analysis due to differences in teaching and assessment conditions during the COVID-19 pandemic
In terms of score distribution, the proportion of high-achieving students (≥ 80 points) increased in the later cohorts, reaching 37.61% in the Class of 2023, compared with 22.79% in the Class of 2021 and 21.66% in the Class of 2022. At the same time, the proportion of students scoring below 60 decreased to 6.42% in the Class of 2023, representing the lowest level observed among the cohorts. The proportion of students scoring between 70 and 79 remained relatively stable at around 35% across cohorts.
In addition, the completion rate of pre-class learning tasks exceeded 90% in recent cohorts. Practical examination performance also showed a gradual improvement over time, suggesting a possible enhancement in students’ hands-on skills and spatial understanding.
Development of higher-order competencies and practical skills
Students completed model-making, drawing tasks, and laboratory training. Practical assessment scores were higher among cohorts that participated in these activities. Cohorts using 3D models and digital visualization tools demonstrated improved performance in tasks requiring interpretation of microscopic structures and spatial relationships.
Discussion
Factors contributing to the improvement in student performance
The results of this study show an overall improvement in student performance from 2017 to 2023, with a gradual increase in mean scores, a higher proportion of high-achieving students, and a reduction in failure rates. These changes suggest that the teaching reform may have contributed to improved learning outcomes.
One possible explanation lies in the adjustment of course structure and learning approaches. In the knowledge verification stage, the use of mind maps together with histological slide observation helped students organize fragmented information into a more coherent framework. This structured approach may have supported a better understanding of fundamental concepts.
In the preliminary exploration stage, the introduction of three-dimensional models and hands-on activities provided students with opportunities to move from two-dimensional observation to spatial understanding. Previous studies have shown that three-dimensional visualization tools can improve learners’ comprehension of complex structures [3]. In the present study, the improvement observed in practical assessments may reflect the development of spatial cognition during this stage. In addition, the use of hands-on activities and model reconstruction in the preliminary exploration stage may support the development of stable spatial representations through repeated practice and feedback [4].
In the practical application stage, clinical cases were incorporated to encourage students to apply their knowledge in specific contexts. Compared with learning based mainly on memorization, this approach requires students to interpret and use knowledge when solving problems. Case-based learning has been reported to support the development of clinical reasoning skills [5]. The incorporation of authentic clinical scenarios in the practical application stage further encourages knowledge transfer to real-world contexts [6]. Therefore, this teaching system not only contributes to improved knowledge retention [7], but also effectively fosters the development of clinical reasoning and problem-solving abilities [8].
Taken together, the three-stage teaching program appears to provide a gradual transition from basic knowledge acquisition to application. This progression is consistent with the development from lower- to higher-order cognitive processes described in Bloom’s taxonomy [9]. It also aligns with the constructivist view that knowledge is built through active engagement in meaningful contexts [10].
Role of 3D models and multimedia technologies in learning
In addition to the overall structure of the program, the use of 3D models and related technologies may have contributed to the observed improvements in students’ performance, particularly in practical and spatial tasks. Compared with traditional two-dimensional teaching materials, 3D models provide more direct spatial information, which may help students better understand the relationships between structures. In this study, the improvement in practical examination performance suggests that students may have developed stronger spatial awareness and hands-on skills.
During the learning process, students interacted with models through observation and manipulation. Students were able to interact with 3D models by rotating and observing structures from different angles, which provided more opportunities to examine spatial relationships in detail [11, 12]. This form of interaction may have encouraged more active engagement compared with traditional lecture-based learning. This allowed them to gradually translate abstract two-dimensional information into three-dimensional understanding. Model construction and related activities also encouraged more active participation, as students were involved in exploring and adjusting their understanding rather than passively receiving information. Previous studies have shown that 3D visualization tools can support spatial cognition and improve the understanding of complex structures in medical education [13–15].
In addition, multimedia tools such as AI-based animations may have supported students’ understanding of dynamic biological processes, particularly in embryological development. By presenting structural changes over time, these tools provide a perspective that is difficult to achieve with static images alone, and may help students connect structural changes with developmental processes [16].
Similar approaches have also been widely applied in clinical education and physician training, including orthopedics [17], urology [18], cardiology [19], dentistry [20], ultrasonography [21], gynecology [22], ophthalmology [23], and emergency medicine [24]. These studies suggest that model-based and visualization-supported teaching may facilitate the understanding of complex anatomical structures and support the transition from theoretical knowledge to clinical application. Taken together, the findings of the present study indicate that the use of 3D models and multimedia tools may play a supportive role in improving learning outcomes in histology and embryology.
Overall, these findings suggest that the use of 3D models and multimedia tools may have contributed to the observed improvements in learning outcomes.
Clinical-oriented learning and the development of problem-solving processes
In the practical application stage, clinical cases and abnormal structural models were introduced to place students in more concrete learning contexts [25]. Compared with traditional approaches that rely mainly on memorization, this stage required students to apply their knowledge to specific situations.
When working with these cases, students were expected to draw on their understanding of tissue structure, function, and related basic knowledge to analyze the problem and propose possible explanations. This approach is consistent with the principles of case-based learning (CBL) and situated learning [26–28]. Some studies have suggested that such approaches may increase student engagement and support the development of clinical thinking [29, 30].
During implementation, students typically worked in groups, discussing different perspectives and gradually refining their understanding of the problem. In this process, they were required to interpret structural changes, relate them to functional outcomes, and explain possible mechanisms. This type of task may help deepen understanding and support the application of knowledge across contexts [31]. In this stage, instructors mainly acted as facilitators by posing guiding questions and providing feedback to support students’ reasoning processes. Moreover, during the course implementation, instructors gradually shifted from being knowledge transmitters to facilitators of learning. By adjusting the complexity of cases and guiding discussions, they supported students in developing their understanding through reflection and interaction. Through repeated engagement with problem-solving tasks, students were encouraged to interpret information, evaluate possible explanations, and refine their reasoning. Previous studies have suggested that such processes may support the development of clinical reasoning, critical thinking, and reflective learning abilities [32, 33].
It should be clarified that clinical reasoning was not assessed using a standardized or independent measurement tool in this study. However, students’ responses in case-based discussions may reflect their ability to integrate and apply knowledge. For example, students were asked to explain pathological changes based on histological structures and to propose possible interpretations, which can be considered an initial form of clinical reasoning.
This study included all clinical medicine students from Class of 2017 to 2023 and did not include a parallel control group, reflecting the implementation of teaching reform in a real educational setting. While this design limits the strength of causal inference, the multi-year data provide an indication of changes over time.
Taken together, these observations suggest that the practical application stage may offer opportunities for students to engage in knowledge application and structured problem analysis, although further studies with more direct assessment methods are needed.
Educational effectiveness of a diversified assessment system
In addition to changes in teaching strategies, the assessment system may also have contributed to the observed improvements in student performance. The course adopts a diversified assessment system that combines formative and summative evaluations, focusing not only on final outcomes but also on the learning process.
Formative assessment provides continuous feedback and may help sustain student engagement throughout the course [34]. The formative assessment was implemented across different stages of teaching [35], including chapter quizzes, classroom participation, model production, drawing assignments, and group presentations. These activities allowed both students and instructors to identify areas of difficulty and adjust learning or teaching strategies accordingly [36]. Compared with traditional approaches that rely mainly on final examinations, this process-oriented evaluation places greater emphasis on learning behaviors and ongoing development [37].
Summative assessment, including theoretical and practical examinations, focused on students’ ability to integrate and apply knowledge [38]. In particular, case-based questions required students to relate structural knowledge to functional interpretation, which is consistent with the objectives of this course. This combination of formative and summative components may support both knowledge acquisition and its application.
In addition, the use of multiple assessment methods, including peer and self-evaluation, provided opportunities for reflection and feedback. Such processes may encourage students to take a more active role in their learning and gradually develop self-regulated learning behaviors [39].
Moreover, the assessment system was designed to balance fairness with a developmental perspective. By incorporating multiple forms of evaluation, including instructor assessment, peer feedback, and self-reflection, it created a more interactive evaluation process. In this context, students were encouraged to reflect on their learning and adjust their strategies over time, which may have supported the development of learning autonomy. Previous studies have also suggested that diversified assessment approaches are associated with improved student engagement and participation, as well as broader competence development [40].
However, the present study implemented a comprehensive teaching reform that involved simultaneous changes in instructional design, use of 3D models, and assessment strategies. As a result, the improvements observed in student performance are likely to reflect the combined effects of these elements, rather than the impact of the assessment system alone. Therefore, the specific contribution of the assessment component cannot be determined in isolation. Nevertheless, within this integrated framework, the assessment system appears to have played a supportive role in promoting students’ engagement and learning outcomes. Further studies with more controlled designs are needed to clarify the individual effects of each component.
Implications for teaching practice
This study was conducted in a real educational setting and involved multiple cohorts of clinical medicine students. The findings suggest that a structured, stage-based teaching approach may help support the progression from basic knowledge acquisition to application.
In particular, the combination of curriculum restructuring, 3D model–assisted learning, and clinical case integration provided students with opportunities to engage with knowledge at different levels. Rather than focusing on a single intervention, this approach emphasized the alignment between teaching content, learning activities, and assessment methods.
From a practical perspective, the program can be adapted to other basic medical courses that involve complex structures and require the integration of knowledge and application. Previous research has shown that competency-oriented teaching approaches can support the development of higher-order skills in medical education [41]. Similarly, integrating three-dimensional models with clinical cases has been found to encourage active inquiry and innovative thinking [42].
Overall, the present study provides an example of how different teaching elements can be combined within a coherent framework in routine educational settings. The experience may be useful for educators seeking to reform similar courses, especially in disciplines where spatial understanding and clinical application are important.
Future directions
The findings of this study are based on a longitudinal observation of teaching practice across multiple cohorts within a real educational setting. Within this context, the results provide an initial basis for understanding how integrated teaching strategies may influence learning outcomes.
Future research may build on these observations by adopting more controlled study designs to further clarify the effects of specific components, such as 3D model–assisted learning or case-based activities. In addition, the use of more targeted assessment tools may help to better capture changes in higher-order abilities, including clinical reasoning and problem-solving. With the ongoing development of digital technologies, emerging approaches such as virtual simulation and data-informed learning analytics may offer additional opportunities to refine both teaching and evaluation processes in medical education [43].
Conclusion
This study examined the implementation of a three-stage progressive teaching program in histology and embryology across multiple cohorts of clinical medicine students. The results showed an overall improvement in academic performance, with an increase in the proportion of high-achieving students and a reduction in failure rates.
The findings suggest that a structured approach integrating staged learning activities may support the progression from knowledge acquisition to application. In particular, the combination of curriculum restructuring, model-assisted learning, and case-based activities provided opportunities for students to engage with knowledge at different levels.
Within the context of routine teaching practice, this program may offer a feasible approach for improving learning outcomes in courses that involve complex structures and require the integration of basic knowledge with application. Further studies are needed to examine its effects under more controlled conditions.
Acknowledgements
The authors would like to thank all the students and faculty members who participated in this study. Their engagement and feedback were invaluable for the design, implementation, and evaluation of the 3D model–driven, clinically oriented, three-stage progressive teaching program. The authors also acknowledge the support of the Department of Histology and Embryology, School of Preclinical Medicine, Zunyi Medical University. ChatGPT was used solely for language editing and improving readability. No AI tools were used for data analysis, result generation, or scientific interpretation. All content was critically reviewed, revised, and approved by the authors, who take full responsibility for the integrity and accuracy of the manuscript. The AI-generated animations described in the Methods section were used as instructional materials and are unrelated to the preparation or writing of this manuscript.
Authors’ contributions
Na Liang, Xiang Lu and Jun Tan contributed to the conception and design of the study. Qiongyou Liu, Lian Liu and Renlian Cai were involved in data collection and analysis. Xiaodong Yi and Ying Wu assisted with the preparation of teaching materials and implementation of the teaching model. Yanping Ren supervised the project and critically revised the manuscript. All authors read and approved the final manuscript.
Funding
This work was supported by the Teaching Master Training Program of Zunyi Medical University and the Teaching Content and Curriculum System Reform Project of Higher Education Institutions in Guizhou (grants SJJG-2023183). This study was supported by the Zunyi Medical University Graduate Education Teaching Reform Project (Grant No. YJSJG2025005). The authors also acknowledge the support of the Department of Histology and Embryology, School of Basic Medical Sciences, Zunyi Medical University. And the Project Funded under the Undergraduate Education and Teaching Reform Program of Zunyi Medical University (XJJG2025-02 and XJJG2023-34).
Data availability
The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
This study analyzed students’ academic performance and participation in routine teaching activities within the Histology and Embryology course. It did not involve human tissue, patient data, or any clinical interventions. According to educational research management guidelines, this type of study does not require formal ethics approval or informed consent. All procedures were conducted in accordance with the ethical principles of the Declaration of Helsinki. This study is not a clinical trial. Clinical trial number: not applicable.
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.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.