A structured blended learning approach for medical imaging technology interns: a prospective randomized comparative study

Abstract

Background

To address radiation safety constraints and equipment shortages in Computed Tomography (CT) training, this study introduces a Structured Blended Learning (SBL) framework integrating Small Private Online Courses (SPOCs), Flipped Classroom (FC), Virtual Simulation (VS), and remote supervision enabled by 5G communication infrastructure. This approach bridges the theory-practice gap by providing a structured progression from knowledge acquisition to simulated and clinical practice.

Methods

In a prospective randomized comparative study, 60 medical imaging interns undergoing CT clinical rotations were randomly assigned to either the SBL group (n = 30) or the traditional lecture-based learning (LBL) group (n = 30). Training effectiveness was evaluated using continuous theoretical examination scores (t-tests), ordinal Mini-Clinical Evaluation Exercise (Mini-CEX) practical assessments (Mann-Whitney U tests), and frequency distribution data from Likert-scale surveys (χ² tests) assessing student satisfaction and perceived learning outcomes.

Results

The SBL group consistently outperformed the LBL group across all theoretical assessments, yielding significantly higher mean scores in the pre-class, post-class, and final examinations (t = 2.391–2.779; all P < 0.05; Cohen’s d = 0.586–0.717). Mini-CEX assessments revealed superior performance by the SBL group across six domains, including patient positioning and handling, radiation protection and safety, equipment operation and image acquisition, image quality evaluation, organization and efficiency, and overall professional competence (Z = 4.855–5.110; all P < 0.001; r = 0.627–0.660). Furthermore, the SBL group reported significantly higher satisfaction with teaching methods, professional skills development, and overall evaluation (χ² =12.76–37.49; all P < 0.01; Cramér’s V=0.231–0.395) and perceived greater effectiveness in professional theoretical knowledge, practical and operational skills, self-directed learning, and overall teaching effectiveness (χ² = 18.27–27.04; all P < 0.01; Cramér’s V = 0.276–0.336).

Conclusions

The SBL approach provides an effective, safe, and engaging pedagogical framework for training medical imaging interns in complex CT workflows. By leveraging digital technologies to address physical access and radiation safety constraints, this approach demonstrates potential for broader application in medical imaging technology education, although further multicenter studies are needed to confirm its generalizability.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12909-026-09527-7.

Introduction

Medical imaging technology education aims to cultivate application-oriented professionals equipped with comprehensive competencies to meet the practical demands of frontline clinical practice. Globally, while hands-on practice is generally accessible, directly training novices on real patients poses universal challenges regarding patient safety, clinical workflow efficiency, and adherence to the as low as reasonably achievable (ALARA) principle [1–3]. Consequently, simulation-based training has become essential worldwide to ensure zero-harm learning before actual patient contact. Regionally, in high-volume healthcare systems like China, these challenges are exacerbated: heavy patient throughput and strict equipment management further restrict early hands-on opportunities [4, 5]. Under these dual global and regional constraints, conventional didactic and apprenticeship models clearly fall short [6–8]. This underscores an urgent need for innovative instructional models that effectively bridge abstract knowledge and clinical practice, highlighting the practical significance of our study.

Since their inception in 2012, Massive Open Online Courses (MOOCs) have been widely recognized for facilitating large-scale knowledge dissemination. Nevertheless, persistent challenges inherent in online learning—most notably a heavy reliance on learner autonomy, generally low completion rates, and limited depth of interaction—have been well documented [9, 10]. To address these shortcomings while leveraging the strengths of digital pedagogy, high-quality MOOC resources are increasingly being repurposed into Small Private Online Courses (SPOCs) for specialized clinical training [11]. Unlike the purely remote delivery typical of MOOCs, SPOCs are designed to be integrated with face-to-face instruction, laying the groundwork for the Flipped Classroom (FC) approach.

Building upon the knowledge acquired online, the in-person FC sessions act as a pivotal link between theoretical concepts and practical application. This approach emphasizes the use of in-class time for problem-solving, discussion, and knowledge consolidation rather than direct content delivery, significantly enhancing students’ self-directed learning abilities, teacher–student interaction, and learning motivation [12, 13]. By compensating for the interactive limitations of digital resources and promoting frequent cognitive engagement, this approach ultimately strengthens their learning initiative and critical thinking skills.

To overcome the inherent challenges of medical imaging training—namely high risks, costs, and limited reproducibility—integrating Virtual Simulation (VS) and remote supervision facilitates the development of higher-order clinical competencies. VS provides a cost-effective, zero-risk environment where students can master complex console operations, patient positioning, parameter optimization, and artifact identification prior to actual patient encounters [14, 15]. This approach enhances clinical readiness despite limited access to physical Computed Tomography (CT) scanners and allows for deliberate, repetitive practice without radiation exposure [16, 17]. Complementing simulation-based training, real-time remote supervision can further bridge virtual training and real-world practice. In this context, 5G communication technology serves as the enabling infrastructure that makes high-fidelity remote supervision feasible: its high bandwidth and ultra-low latency ensure the real-time, lag-free transmission of high-definition images and bidirectional audiovisual communication [18]. Together, these components support the transition from virtual training to real-world practice. However, while both technologies demonstrate independent benefits in medical education, empirical studies integrating them into medical imaging internships remain scarce.

Addressing this gap, this study implements a structured blended learning (SBL) approach grounded in Bloom’s Taxonomy. Designed to overcome the clinical constraints of high risk, high cost, and limited reproducibility, the model aligns strictly with cognitive hierarchies to progressively build professional competence. First, SPOCs shift foundational theory online to target lower-order skills (remembering/understanding). Next, FC sessions advance students to intermediate levels (application/analysis), fostering critical thinking. Finally, the integration of VS and remote supervision cultivates higher-order competencies (evaluation/creation), equipping students for complex clinical realities.

Therefore, we hypothesize that the SBL model would be superior to traditional lecture-based learning (LBL) in enhancing the comprehensive professional competence of medical imaging technology interns. This study aims to evaluate this hypothesis by comparing the two instructional methods in terms of their effects on interns’ clinical performance, theoretical knowledge, and self-reported learning experiences.

Participants and study setting

Study design

This was a prospective randomized comparative study conducted at a single institution from March 2025 to January 2026. The study included three theoretical tests, one Mini-Clinical Evaluation Exercise (Mini-CEX) assessment, and two questionnaire surveys. The study protocol was approved by the hospital’s Ethics Committee (Approval No.: 2025-KLS-1007-02). To ensure educational equity and adhere to ethical pedagogical principles, all SBL resources, including the instructional videos within the SPOCs platform and access to the virtual simulation platform, were fully made available to the students in the LBL group immediately following the conclusion of the study and final assessments.

Inclusion and exclusion criteria

A total of 60 medical imaging technology interns were enrolled. The inclusion criteria were as follows: (1) recruited from the same institution; (2) no prior clinical training experience related to CT imaging; (3) completion of a standardized pre-internship test, ensuring comparable baseline theoretical knowledge; and (4) voluntary participation with signed written informed consent. The exclusion criteria were: (1) previous participation in similar CT clinical teaching or training programs; and (2) inability or unwillingness to commit to completing the entire training cycle.

All participants were informed that their participation was entirely voluntary and that they could withdraw from the study at any time without any consequences.

Randomization and blinding

An independent researcher not involved in the teaching or outcome assessment randomly assigned the interns to either the SBL group or the LBL group (n = 30 per group) using a random number table. Allocation concealment was ensured using sealed, opaque envelopes, and the group assignments were disclosed to the students by teaching administrators prior to the start of the internship. Additionally, the teaching administrators used a random number table to assign a teaching team, which consisted of two experienced medical imaging technology instructors and one teaching assistant. All theoretical tests were graded using standardized answer keys. The Mini-CEX practical skills assessments were conducted by clinical instructors who were not involved in this teaching intervention and remained blinded to the participants’ group allocations.

Integrated instructional design of the SBL model

Participants in the SBL group were organized into collaborative learning groups consisting of 4 to 5 students. The instructional design of the SBL model was grounded in Bloom’s Taxonomy of Educational Objectives [19]. Within this framework, SPOCs primarily targeted lower-order cognitive domains, including knowledge acquisition and comprehension. The FC approach was employed to promote the application and analysis of knowledge, while the integration of VS training and remote supervision facilitated the development of higher-order cognitive skills.

The overall process and structure of the integrated SBL instructional design are illustrated in Fig. 1.

Fig. 1.

Comparison of the Instructional Frameworks for the SBL (Experimental) and LBL (Control) Groups. The SBL model integrates SPOCs for foundational knowledge, the FC for application and analysis, and VS with remote supervision enabled by 5G communication infrastructure for higher-order skill development. The LBL model follows a traditional, lecture-based approach

Asynchronous pre-class learning via SPOCs

During the pre-class learning phase, instructors integrated relevant professional knowledge in alignment with standard reference textbooks and developed teaching materials, including PowerPoint presentations and instructional videos. The videos were designed with a student-centered approach, closely integrating theoretical content with clinical application requirements. Each video lasted approximately 8 to 10 min and was structured into four components: concept introduction, concept explanation, classic clinical cases, and knowledge summary. Students were required to watch the instructional videos, review key theoretical concepts (e.g., imaging principles and positioning), and complete brief formative quizzes or guiding questions prior to class to ensure a baseline understanding.

Rather than using a fully open MOOCs environment, all video-based learning resources and supplementary materials were deployed within a restricted-access SPOCs framework, accompanied by targeted practice exercises. Operating in this asynchronous, self-paced learning environment, interns were required to independently complete these modules and successfully pass the corresponding quizzes prior to attending the face-to-face sessions.

In-class learning

The in-class phase was structured around a dual-component approach: it began with FC sessions designed to deepen theoretical understanding and promote knowledge application, followed by immersive, hands-on training supported by the integration of VS with remote supervision enabled by 5G communication infrastructure.

FC instruction: problem-based case analysis

The FC teaching component was structured around a Guided Problem-Based Learning (Guided PBL). Unlike classic open-ended PBL where students independently derive all learning objectives from scratch, Guided PBL was selected to maximize efficiency within the time-constrained flipped classroom environment.

Using the CT triple-rule-out examination for acute chest pain as an example, the teaching process centered on an authentic, ill-structured clinical scenario. Crucially, rather than receiving predefined prompts upfront, students initially engaged in brief independent brainstorming to identify key clinical issues and formulate preliminary imaging needs. Only after this self-directed exploration were six scaffolded prompts introduced to guide their collaborative analysis. This sequenced approach preserved independent inquiry before advancing to structured clinical reasoning.

The six scaffolded inquiry prompts included:

1. Fundamentals: Defining the CT triple-rule-out examination and comparing its diagnostic advantages over conventional radiography.

2. Advanced Technology: Exploring the unique technical features and clinical applications of spectral CT.

3. Safety and Optimization: Calculating and optimizing radiation dose and contrast media protocols for diverse patient profiles (e.g., varying body weight).

4. Technical Execution: Adjusting scan parameters to ensure diagnostic image quality and determining optimal scan time.

5. Team Collaboration: Outlining standardized protocols for interprofessional collaboration (physicians, technologists, nurses) in managing contrast-related adverse events.

6. Image Interpretation: Identifying the key imaging features of target pathologies such as coronary artery disease, pulmonary embolism, and aortic dissection.

This problem-based framework followed a logical progression from imaging theory and equipment to radiation dose, examination techniques, and clinical diagnosis. The primary objective was to cultivate systematic thinking and clinical problem-solving skills from the perspective of medical imaging technologists, thereby facilitating the effective transformation of theoretical knowledge into practical competence.

The FC session was executed in three distinct stages:

First, the session began with the presentation of the authentic, unstructured clinical scenario. After a brief period of initial brainstorming where students identified their own learning needs, the instructors introduced the scaffolded prompts. Students worked in groups of 4 to 5, with each group randomly assigned a core problem for in-depth discussion. Two experienced instructors provided continuous supervision and timely guidance to encourage active participation and to address key challenges. After group discussions, one representative from each group presented the discussion outcomes, with each presentation strictly limited to 5 min.

Second, following each presentation, students from other groups were encouraged to raise questions and provide feedback, further enhancing learner engagement and critical thinking.

Third, instructors delivered a comprehensive summary and commentary based on the group presentations, clarifying common misunderstandings and key points. Targeted in-class quizzes were subsequently developed to address both shared and individual learning issues, thereby reinforcing learning outcomes and sustainability.

Practical training integrating VS

Following the theoretical sessions, the SBL model transitioned to practical skills training by integrating VS with remote supervision enabled by 5G communication infrastructure. This integrated structure supported a problem-oriented training environment where interns could apply their knowledge from the FC sessions.

The VS training utilized a browser-based, high-fidelity CT simulation system developed with Jiamaohong Medical. Accessible via standard workstations (1920 × 1080 resolution) without specialized hardware, this WebGL-rendered platform ensured excellent institutional scalability and delivered seamless 60-FPS visual feedback. It realistically replicated an authentic clinical console, integrating interactive parameter adjustments (e.g., kV, mAs), landmark-based 3D patient positioning, real-time image output, and programmed branching logic.

Within this zero-risk environment, interns engaged in the deliberate practice of integrated clinical workflows. Compared to traditional observation or phantom training, the VS platform provided distinct advantages: (1) safe trial-and-error for exposure settings with immediate feedback; (2) simulation of time-critical, high-risk scenarios (e.g., emergency imaging); and (3) precise 3D visualization for patient positioning. For example, in a contrast-enhanced chest CT scenario, interns were tasked with executing the entire procedural sequence:

1. Performing equipment and image quality control.

2. Conducting patient communication and ensuring radiation safety during patient positioning.

3. Selecting the optimal imaging protocol based on the patient’s clinical presentation.

4. Optimizing scanning parameters to balance diagnostic image quality with radiation dose.

5. Performing image post-processing and reconstruction.

This “one-stop” workflow practice generated quantitative performance reports, providing objective feedback for skill refinement. Each integrated simulation training module on the VS platform was designed to be completed within a 45-minute timeframe.

Real-time remote clinical guidance supported by 5G communication infrastructure

Following the VS, the training transitioned to real-world application through remote supervision enabled by 5G communication infrastructure. Instructors conducted real-time remote demonstrations of both routine and contrast-enhanced CT examinations, covering key procedures such as patient positioning, parameter adjustment, contrast media administration, and image post-processing.

Subsequently, interns remotely participated in live clinical CT examinations with actual patients. While having an instructor in the room remains the gold standard for clinical teaching, strict radiation safety protocols, the limited physical space within the CT scanning room, and the high volume of daily patients heavily restrict the number of interns who can be physically present alongside a senior instructor. To overcome these practical barriers, remote supervision was utilized as a complementary strategy. Under the continuous, high-definition audiovisual monitoring of a remote senior instructor, interns in the control room were responsible for tasks like setting exposure parameters and image post-processing. This approach allowed that multiple interns could simultaneously receive expert, real-time guidance and timely intervention—ensuring both procedural accuracy and patient safety—without violating radiation safety regulations or disrupting clinical throughput. The complete training workflow is depicted in Fig. 2.

Fig. 2.

Visualization of the integrated practical training platform. A Immersive VS environment. This module facilitates risk-free practice of pre-scan preparations, including patient positioning and radiation protection (e.g., thyroid shielding). B High-fidelity CT console simulation. The interface replicates clinical operating systems, allowing students to define scan ranges and optimize parameters (kV, mAs, pitch) for chest CT protocols. C Schematic of the 5G-enabled remote teaching architecture. The system supports real-time demonstrations of routine and contrast-enhanced workflows via bidirectional audiovisual streams. It enables remote student participation in live examinations with synchronous mentor monitoring and intervention to ensure patient safety

Collaborative learning and personalized feedback

To strengthen collaborative learning, one student from each group was designated to raise questions arising during the operational process. Instructors provided concise feedback on group-specific queries, addressed common challenges collectively, and reserved complex individual issues for subsequent face-to-face discussions. This tiered feedback mechanism reinforced the instructor’s role as a facilitator while allowing for personalized guidance.

Post-class consolidation and extension

During the post-class consolidation phase, two open-ended questions with relatively high cognitive demands were carefully designed to extend and deepen in-class learning outcomes and foster self-directed learning abilities among imaging interns. Students were encouraged to formulate their responses through the review of clinical guidelines and independent literature searches. After submission, instructors provided individualized feedback and detailed explanations via an online teaching platform.

Control group: LBL protocol

Participants in the LBL group received traditional didactic instruction. To ensure comparability between groups, the LBL and SBL groups were matched in terms of instructors, teaching content, teaching schedule, and assessment criteria, with differences limited to instructional organization and teaching media.

Before class, students in the LBL group followed the same teaching schedule as the SBL group and used identical reference textbooks and PowerPoint materials; however, they did not participate in asynchronous video-based learning modules. Students were also required to complete pre-class quizzes based on the identical assigned exercises used in the SBL group. During in-class sessions, instructors adopted a traditional didactic teaching approach, systematically explaining theoretical knowledge, key technical points, and the exact same representative clinical cases (e.g., the CT triple-rule-out examination) using PowerPoint presentations. Limited interaction occurred in the form of questions and answers, without structured group discussions or FC presentations.

Practical training was conducted using a conventional clinical observation model. Students participated in small groups and accompanied supervising instructors into examination rooms to observe equipment operation and examination workflows in real clinical cases. When feasible, and without interfering with routine clinical practice, students were allowed to perform limited hands-on operations. However, no VS tools or remote guidance systems were utilized, and students primarily acquired practical skills through observation of instructors’ equipment operation.

To minimize potential confounding bias regarding the instructional workload, the total allocated learning time (including both online self-study and offline face-to-face sessions) was kept strictly equivalent between the SBL and LBL groups. The SBL model did not simply add more teaching hours, but structurally reallocated the traditional lecture time into pre-class online learning and in-class high-level interactive practices.

Comprehensive assessment and questionnaire survey

A multi-faceted approach was used to evaluate the effectiveness of the SBL framework.

Theoretical Knowledge: Interns’ theoretical knowledge was assessed at three time points: pre-class quizzes, post-class quizzes, and a comprehensive final examination. The content and structure of these assessments are detailed in Supplementary Tables S1-S3.

Clinical Skills: Practical clinical skills were evaluated using the Mini-CEX. Each item on the Mini-CEX was rated on a 9-point scale, with the detailed rubric provided in Supplementary Table S4.

Learning Experience and Perceptions: Two custom-designed questionnaires were administered to assess teaching satisfaction and perceived teaching effectiveness (Supplementary Tables S5-S6). These instruments were developed by our teaching research group based on a literature review and tailored to the course objectives [20]. Both questionnaires demonstrated good internal consistency, with Cronbach’s α coefficients exceeding 0.8. A 5-point Likert scale was used for all items (ranging from “very dissatisfied” to “very satisfied”).

The questionnaires were distributed to all participants at the conclusion of the internship program, strictly prior to the release of any assessment outcomes, including the final theoretical examination and Mini-CEX scores. This timing was intentionally designed to prevent grade-driven bias, ensuring that students’ self-reported satisfaction and perceived effectiveness were not unduly influenced by their actual performance results. To ensure candid responses, the surveys were completed and submitted anonymously within a specified timeframe.

Statistical analysis

All statistical analyses were conducted using Statistical Package for the Social Sciences (SPSS, Version 23.0), GraphPad Prism (Version 9.5.1), and Python (Version 3.8). A P-value of < 0.05 was considered statistically significant for all tests.

Continuous data that followed a normal distribution, such as theoretical test scores, were presented as mean ± standard deviation (SD) and compared between the two groups using independent samples t-tests. Ordinal data, including Mini-CEX scores and Likert-scale questionnaire responses, were presented as median and interquartile range (IQR). Comparisons of these data between the experimental and control groups were performed using the Mann-Whitney U test.

Teaching satisfaction and teaching effectiveness questionnaire data based on the 5-point Likert scale were presented as frequencies and percentages, and group comparisons were performed using the chi-square (χ²) test.

Results

Baseline demographics and comparability

A total of 60 interns participated in the study, with 30 allocated to the SBL group and 30 to the LBL group. The SBL group consisted of 16 males and 14 females, with a mean age of 22.50 ± 0.86 years and a mean pre-internship examination score of 70.00 ± 11.74. The LBL group included 11 males and 19 females, with a mean age of 22.73 ± 0.75 years and a mean pre-internship examination score of 69.33 ± 11.43. There were no significant baseline differences between the SBL and LBL groups regarding age, gender, and pre-internship examination scores (all P > 0.05), indicating that the two groups were highly comparable.

Comparison of theoretical knowledge scores

As detailed in Table 1, the SBL group significantly outperformed the LBL group across all three assessments (t = 2.391, 2.779, and 2.271, respectively; all P < 0.05).

Table 1.

Comparison of Theoretical Knowledge Scores Between the SBL and LBL Groups

Score	SBL group	LBL group	t	P	Cohen’s d
Pre-class score	78.33 ± 6.99	73.67 ± 8.09	2.391	0.020	0.617
Post-class score	86.07 ± 2.60	83.63 ± 4.03	2.779	0.008	0.717
Final examination score	90.01 ± 5.74	87.53 ± 4.57	2.271	0.027	0.586

Note: For the SBL group, the pre-class test was conducted after SPOCs learning, where as for the LBL group, it was conducted after lecture-based instruction

Assessment of practical skills using the Mini-CEX

Both the SBL and LBL groups underwent the same practical skills Mini-CEX assessment. As shown in Fig. 3, no statistically significant differences were observed between the two groups in pre-procedure preparation and verification, or in communication and humanistic care (Z = 0.655 and 0.820, respectively; all P > 0.05; r = 0.085 and 0.106, respectively).

Fig. 3.

A Pre-procedure preparation and verification; B Communication and humanistic care; C Patient positioning and handling; D Radiation protection and safety; E Equipment operation and image acquisition; F Image quality evaluation; G Organization and efficiency; H Overall professional competence. The SBL group scored significantly higher in domains C through H

In contrast, the SBL group achieved significantly higher scores than the LBL group in patient positioning and handling, radiation protection and safety, equipment operation and image acquisition, image quality evaluation, organization and efficiency, and overall professional competence (Z = 4.920, 5.015, 5.110, 4.980, 4.855, and 4.950, respectively; all P < 0.001; r = 0.635, 0.647, 0.660, 0.643, 0.627, and 0.639, respectively).

Student satisfaction with the teaching model

Figure 4 compares teaching satisfaction between different instructional models across five dimensions. The results indicated that the distribution of satisfaction levels differed significantly between the SBL and LBL groups in terms of teaching method, professional skills, and overall evaluation (χ² = 37.49, 23.58, and 12.76, respectively; P < 0.01; Cramér’s V = 0.395, 0.313, and 0.231, respectively). This finding suggests that students in the SBL group reported significantly higher satisfaction in these aspects compared to their counterparts in the LBL group.

Fig. 4.

A Teaching Method; B Teaching Content; C Instructor Guidance; D Professional Skills; E Overall Evaluation. The outer ring represents the SBL group, and the inner ring represents the LBL group. Students in the SBL group reported significantly higher satisfaction in domains A, D, and E (P < 0.01)

In contrast, no statistically significant differences were observed between the two groups regarding teaching content or instructor guidance (χ² = 1.02 and 0.92, respectively; P > 0.05; Cramér’s V = 0.065 and 0.062, respectively), suggesting comparable satisfaction levels between the two teaching models in these dimensions.

Perceived teaching effectiveness

As shown in Fig. 5, interns’ evaluation of teaching effectiveness revealed a clear and significant advantage for the SBL model.

Fig. 5.

A Professional Literacy; B Professional Theoretical Knowledge; C Practical and Operational Skills; D Patient Communication Skills; E Self-directed Learning Ability; F Overall Teaching Effectiveness. The outer ring represents the SBL group, and the inner ring represents the LBL group. The SBL group received significantly higher ratings in domains B, C, E, and F (P < 0.01)

The SBL intervention was rated as significantly more effective in fostering the core competencies central to the curriculum. This included “professional theoretical knowledge,” “practical and operational skills,” and “self-directed learning ability,” which culminated in a significantly higher rating for “overall teaching effectiveness” (χ² = 21.63, 27.04, 18.27, and 22.11 respectively; all P < 0.01; Cramér’s V = 0.300, 0.336, 0.276, and 0.304, respectively).

In contrast, no statistically significant differences were identified between the two groups regarding professional literacy or patient communication skills (χ² = 0.79 and 0.68, respectively; P > 0.05; Cramér’s V = 0.057 and 0.053, respectively), suggesting that the teaching effectiveness of the two instructional models was comparable in these aspects.

Discussion

With the rapid advancement of modern medical education and the deep integration of information technology, educational paradigms have gradually shifted from a “teacher-centered” approach to a “learner-centered” approach, characterized by enhanced interactivity, intuitiveness, and instructional efficiency. Accordingly, this study constructed a SBL model grounded in Bloom’s Taxonomy, aiming to facilitate the progressive transformation of knowledge into professional competence through a hierarchically structured teaching strategy.

Our findings supported this staged approach. The superior pre-class test scores in the SBL group suggest that SPOC-based preparation is more effective than traditional textbook study for mastering foundational knowledge. This can be attributed to several factors. Medical imaging technology is an interdisciplinary field, integrating complex concepts from medicine, physics, and computer science. Traditional textbook learning can struggle to convey this abstract and multifaceted knowledge coherently. In contrast, the SPOCs used in our model deconstruct this complexity into digestible, modular units. By using visualization to explain abstract principles and allowing for self-paced, repeated viewing, SPOCs enhance both the comprehensibility and retention of core concepts. This advantage of multimedia-based pre-learning is consistent with findings from previous research [21, 22].

Our results further revealed that the integration of SPOCs with FC model significantly improved post-class test scores and final examination performance. Within Bloom’s theoretical framework, the FC model facilitates the transition of learning objectives from lower-order cognitive levels to higher-order processes such as application and analysis. By reallocating in-class time to problem-solving, case-based discussions, and interactive inquiry, interns are encouraged to actively apply pre-class knowledge to real-world scenarios under instructor guidance, thereby promoting knowledge internalization and transfer [23, 24]. This instructional strategy effectively overcomes the limitations of traditional LBL in fostering deep learning and higher-order cognitive development.

To further enhance practical competency development, this study incorporated VS technology and remote supervision to address constraints in clinical training opportunities. Assessment based on the Mini-CEX scale demonstrated significant improvements across multiple core domains, including patient positioning, radiation protection, equipment operation, image quality assessment, and organizational efficiency. From the perspective of Bloom’s taxonomy, VS technology provides an immersive simulated environment where learners can practice clinical skills repeatedly in a safe setting while engaging in self-reflection and performance evaluation. This approach directly facilitates the attainment of higher-order cognitive objectives, such as application and evaluation. Furthermore, by providing such a risk-free platform, the SBL model responds to urgent calls for enhanced radiation safety education, effectively bridging the current gaps in formal medical curricula where students often lack adequate preparation for real-world radiation risks [3]. Meanwhile, remote supervision enabled by 5G communication infrastructure supports real-time collaborative guidance from instructors, assisting interns in transferring skills acquired in virtual environments to authentic clinical contexts and further promoting cognitive integration at the synthesis level [25, 26]. However, no significant improvement was observed in “communication and humanistic care.” While the SBL model excels at standardizing technical training, its reliance on technology reduces the authentic face-to-face patient interactions needed to develop empathy and communication skills.

Compared to the traditional LBL model, the SBL approach demonstrated clear advantages in enhancing overall professional competence among interns. Questionnaire findings indicated significant improvements in mastery of professional theory, practical skills, and self-directed learning ability. Additionally, interns expressed positive evaluations regarding overall satisfaction, acceptance of the instructional approach, and achievement of clinical competencies. These results suggest that the SBL model not only supports progressive cognitive development but also effectively stimulates learning motivation and professional self-efficacy, consistent with findings reported by Sun et al. [27].

Nevertheless, several limitations of this study should be acknowledged. First, the single-center design, relatively small sample size, and one-year observation period limit the generalizability of our findings and preclude the assessment of long-term educational outcomes. Second, relying solely on quantitative questionnaires restricts deeper insights into learners’ experiences, which could be addressed through qualitative methods like focus group interviews. Third, as SBL is a multi-component intervention, isolating the specific effect of each element (SPOC, FC, VS) is challenging; furthermore, the overall improvements may be partially driven by a novelty effect rather than the instructional design alone. Fourth, the technology-centric nature of the model may inadvertently constrain the cultivation of humanistic competencies, raising concerns about students’ readiness for independent, real-world patient interactions. Finally, the lack of a formal cost-effectiveness analysis—given variable institutional costs for platform licensing and content development—leaves the model’s economic viability unverified. Consequently, future multicenter longitudinal studies incorporating qualitative feedback, cost analyses, and clinical performance tracking are warranted to fully validate the model’s long-term effectiveness and scalability.

Conclusion

The SBL approach, grounded in Bloom’s Taxonomy, provides an effective pedagogical framework for medical imaging technology education. It may help address persistent challenges, including the abstract nature of theoretical content, limited hands-on training opportunities, and the inequitable distribution of educational resources. By creating a structured training continuum from foundational knowledge to applied clinical practice, this approach supports the integration of theory and skill. As a potentially feasible and scalable educational strategy, the SBL approach may contribute to optimizing clinical teaching resources and promoting the dissemination of high-quality medical education; however, broader implementation should be supported by further multicenter validation and contextual evaluation.

Authors’ contributions

HZ: Conceptualization, Methodology, Formal analysis, Writing – original draft.HJ: Methodology, Writing – Original Draft.HX: Investigation, Data Curation.LM: Investigation, Data Curation.JW: Investigation, Data Curation.SW: Supervision, Funding Acquisition, Writing – Review & Editing.

Funding

This work was supported by the Ministry of Education–Industry Collaboration and Cooperative Education Project (grant number 230901214131224) and the Undergraduate Education and Teaching Reform Project of Zhejiang Chinese Medical University (grant number ZB24002).

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

The study protocol and written informed consent form were approved by the Institutional Review Board and Ethics Committee of The First Affiliated Hospital of Zhejiang Chinese Medical University (Ref: 2025-KLS-1007-02). Prior to enrollment, all participants provided written informed consent and were advised of their right to withdraw from the study at any time without penalty. The study was conducted in accordance with relevant guidelines and regulations, including the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.