Improvement of flipped classroom teaching in colleges and universities based on virtual reality assisted by deep learning
Abstract In order to solve the limitations of flipped classroom in personalized teaching and interactive effect improvement, this paper designs a new model of flipped classroom in colleges and universities based on Virtual Reality (VR) by combining the algorithm of Contrastive Language-Image Pre-Tra...
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-87450-5 |
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| author | Wenxia Dai Qinqing Kang |
| author_facet | Wenxia Dai Qinqing Kang |
| author_sort | Wenxia Dai |
| collection | DOAJ |
| description | Abstract In order to solve the limitations of flipped classroom in personalized teaching and interactive effect improvement, this paper designs a new model of flipped classroom in colleges and universities based on Virtual Reality (VR) by combining the algorithm of Contrastive Language-Image Pre-Training (CLIP). Through cross-modal data fusion, the model deeply combines students’ operation behavior with teaching content, and improves teaching effect through intelligent feedback mechanism. The test data shows that the similarity between video and image modes reaches 0.89, which indicates that different modal information can be effectively integrated to ensure the semantic consistency and intuitive understanding of teaching content. The minimum Kullback–Leibler (KL) divergence is 0.12, which ensures the stability of data distribution and avoids information loss. The accuracy of automatically generating feedback reaches 93.72%, which significantly improves the efficiency of personalized learning guidance. In the adaptability test of virtual scene, the frequency of scene adjustment is 2.5 times/minute, and the consistency score is stable above 8.6, ensuring the consistency of teaching goals under complex interaction. This paper aims to enhance personalized learning experience, improve teaching efficiency and autonomous learning effect through VR technology and intelligent feedback, and promote the innovation of interactive teaching mode. |
| format | Article |
| id | doaj-art-fe30ee85a6a140b8939f78d578a6931c |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-fe30ee85a6a140b8939f78d578a6931c2025-01-26T12:24:31ZengNature PortfolioScientific Reports2045-23222025-01-0115111410.1038/s41598-025-87450-5Improvement of flipped classroom teaching in colleges and universities based on virtual reality assisted by deep learningWenxia Dai0Qinqing Kang1School of Humanities and Arts, Hunan International Economics UniversitySchool of Electronic and Information Engineering, Changsha Institute of TechnologyAbstract In order to solve the limitations of flipped classroom in personalized teaching and interactive effect improvement, this paper designs a new model of flipped classroom in colleges and universities based on Virtual Reality (VR) by combining the algorithm of Contrastive Language-Image Pre-Training (CLIP). Through cross-modal data fusion, the model deeply combines students’ operation behavior with teaching content, and improves teaching effect through intelligent feedback mechanism. The test data shows that the similarity between video and image modes reaches 0.89, which indicates that different modal information can be effectively integrated to ensure the semantic consistency and intuitive understanding of teaching content. The minimum Kullback–Leibler (KL) divergence is 0.12, which ensures the stability of data distribution and avoids information loss. The accuracy of automatically generating feedback reaches 93.72%, which significantly improves the efficiency of personalized learning guidance. In the adaptability test of virtual scene, the frequency of scene adjustment is 2.5 times/minute, and the consistency score is stable above 8.6, ensuring the consistency of teaching goals under complex interaction. This paper aims to enhance personalized learning experience, improve teaching efficiency and autonomous learning effect through VR technology and intelligent feedback, and promote the innovation of interactive teaching mode.https://doi.org/10.1038/s41598-025-87450-5Flipped classroomCLIPCross-modal data fusionVRDeep learning |
| spellingShingle | Wenxia Dai Qinqing Kang Improvement of flipped classroom teaching in colleges and universities based on virtual reality assisted by deep learning Scientific Reports Flipped classroom CLIP Cross-modal data fusion VR Deep learning |
| title | Improvement of flipped classroom teaching in colleges and universities based on virtual reality assisted by deep learning |
| title_full | Improvement of flipped classroom teaching in colleges and universities based on virtual reality assisted by deep learning |
| title_fullStr | Improvement of flipped classroom teaching in colleges and universities based on virtual reality assisted by deep learning |
| title_full_unstemmed | Improvement of flipped classroom teaching in colleges and universities based on virtual reality assisted by deep learning |
| title_short | Improvement of flipped classroom teaching in colleges and universities based on virtual reality assisted by deep learning |
| title_sort | improvement of flipped classroom teaching in colleges and universities based on virtual reality assisted by deep learning |
| topic | Flipped classroom CLIP Cross-modal data fusion VR Deep learning |
| url | https://doi.org/10.1038/s41598-025-87450-5 |
| work_keys_str_mv | AT wenxiadai improvementofflippedclassroomteachingincollegesanduniversitiesbasedonvirtualrealityassistedbydeeplearning AT qinqingkang improvementofflippedclassroomteachingincollegesanduniversitiesbasedonvirtualrealityassistedbydeeplearning |