Enhancing medical imaging teaching on scoliosis: Efficacy of learning method integrating 3D printing and artificial intelligence technologies.

BACKGROUND

In scoliosis imaging education, the traditional lecture-based learning model can lead to low student engagement and present challenges in developing clinical thinking abilities and diagnostic skills. This study aims to evaluate the effectiveness of integrating three-dimensional (3D) printing and artificial intelligence (AI) technologies with traditional teaching methods in scoliosis education through objective and subjective assessments, and explore the integrated teaching method for medical imaging to address the limitations of traditional lecture-based teaching, thereby providing insights for the development of medical imaging education.

METHODS

A total of 36 undergraduate medical imaging students from our institution were selected as participants and randomly assigned to a control group and an experimental group, with 18 students in each group. The control group received traditional multimedia instruction, while the experimental group supplemented traditional teaching methods with 3D-printed scoliosis models and AI software. Following the course, all participants underwent standardized assessments, which were evaluated by assessors blinded to group allocation. The final evaluation compared the two groups on theoretical knowledge test scores, imaging case analysis assessments, and questionnaire responses on comprehensive capabilities and teaching satisfaction.

RESULTS

Students in the experimental group achieved significantly higher scores than the control group in both theoretical knowledge (91.01 ± 4.48 vs. 82.49 ± 4.08) and imaging case analysis (90.24 ± 4.77 vs. 80.61 ± 6.33), with statistically significant differences (p < 0.001). Questionnaire results showed that the experimental group scored higher in spatial imagination ability, depth of knowledge mastery, learning interest, thinking inspiration, and overall comprehensive ability, with statistically significant differences (p < 0.001). Students in the experimental group reported higher teaching satisfaction than those in the control group, but the difference was not statistically significant (p = 0.60).

CONCLUSION

Integrating 3D printing and artificial intelligence technologies into scoliosis teaching not only enhances students' theoretical comprehension and practical skills but also improves overall teaching quality, thereby contributing to the optimization of comprehensive educational outcomes.

PLAIN LANGUAGE SUMMARY: Students learning medical imaging can find it hard to understand complex spine conditions. This study compared traditional teaching with lessons that also used 3D models and artificial intelligence tools. This study found that students using the new method had better test results, stronger case analysis skills, and more interest in learning. This matters because improved teaching methods can help students gain the skills needed for better patient care.