Exploring the role of moxibustion robots in teaching: a cross-sectional study.

Background: Artificial intelligence has gradually been used into various fields of medical education at present. Under the background of moxibustion robot teaching assistance, the study aims to explore the relationship and the internal mechanism between learning engagement and evaluation in three stages, preparation before class, participation in class, and consolidation after class.

Methods: Based on the data investigated in 250 youths in university via multistage cluster sampling following the self-administered questionnaire, structural equation model was built to discussing factors of study process about moxibustion robots.

Results: It was found after moxibustion robot teaching assistance that preparation before class, participation in class and consolidation after class positively predicted learning engagement. Learning engagement, preparation before class, participation in class, consolidation after class positively predicted effect evaluation. Learning engagement played a mediating role in the effect of preparation before class and consolidation after class on evaluation.

Conclusion: Employing artificial intelligence in three stages of class can improve the quality and efficiency of medicine education and promote its innovation and development. Serviceable and valuable reference and inspiration for future teaching improvement and industrial development can be provided via the systematic research and analysis of the practical application of moxibustion robot in teaching.