Traditional Chinese medicine has a rich theoretical system. However, in the modern educational environment, its complex and profound theoretical knowledge and object identification skills are often challenging to fully convey through traditional teaching methods. Given this, this study uses the combination of virtual and natural Mixed Reality (MR) characteristics to propose a design scheme for a traditional Chinese medicine teaching system based on MR technology. It establishes a corresponding teaching effect evaluation system. The system uses MR technology to superimpose the virtual Chinese medicine model on the natural environment. It enables students to observe and identify various Chinese medicinal materials and their growing environments in near-real scenes. At the same time, the system has built-in expert-level explanations and interactive question-and-answer modules to help students deeply understand the efficacy and compatibility principles of medicinal materials. The experimental results show that after using this system for teaching, the accuracy of students’ understanding of Chinese herbal medicines is improved by 27.5%, and the depth of their understanding of pharmacological effects is improved by 15%. In the subsequent actual drug discrimination test, the students who participated in the experiment scored more than 12% higher than that of the control group on average. In addition, students’ interest and initiative in learning traditional Chinese medicine have also been significantly improved. According to the questionnaire survey, 93% of the subjects expressed willingness to continue using such systems to assist learning.
HouseRJEapenJPShenH, et al.Ceas: an R package for seahorse data analysis and visualization. Bioinformatics2024; 40(8): btae503.
2.
PhamXLLuuMHvan WalsumT, et al.CMAN: cascaded multi-scale spatial channel Attention-guided network for large 3D deformable registration of liver CT images. Med Image Anal2024; 96: 103212.
3.
BalaKAOmarMRSooJYH, et al.CNUCTRAN: a program for computing final nuclide concentrations using a direct simulation approach. Comput Phys Commun2024; 302: 109258.
4.
ZhiSHWangYXiaoH, et al.Coarse-super-resolution-fine network (CoSF-Net): a unified end-to-end neural network for 4D-MRI with simultaneous motion estimation and super-resolution. IEEE Trans Med Imag2024; 43(1): 162–174.
5.
LiWYLuWZLiangXJ, et al.Collaborative dictionary learning for compressed sensing. IEEE Trans Ind Inf2024; 20(7): 9610–9620.
6.
DavoodiSThanhHVWoodDA, et al.Combined deep-learning optimization predictive models for determining carbon dioxide solubility in ionic liquids. Journal of Industrial Information Integration2024; 41: 100662.
7.
ZhaoYBollegalaDHiroseS, et al.Community knowledge graph abstraction for enhanced link prediction: a study on PubMed knowledge graph. J Biomed Inf2024; 158: 104725.
8.
ElawadyMSarhanAAlshewimyMAM. Toward a mixed reality domain model for time-sensitive applications using IoE infrastructure and edge computing (MRIoEF). J Supercomput2022; 78(8): 10656–10689.
9.
QiaoMYWangSQiuH, et al.CHeart: a conditional spatio-temporal generative model for cardiac anatomy. IEEE Trans Med Imag2024; 43(3): 1259–1269.
10.
LiXDHuY. Cooperative-net: an end-to-end multi-task interaction network for unified reconstruction and segmentation of MR image. Comput Methods Progr Biomed2024; 245: 108045.
11.
HolopainenJLahtevanojaALammassaariH, et al.Best of both worlds: a model combining online and mixed reality learning environments based on cognitive affordances. Educ Media Int2022; 59(1): 45–61.
12.
SunMXNiCZZhangFQ, et al.Chiral amino acid recognition in water: a BINOL-Based fluorescent probe. Chin Chem Lett2023; 34(12): 108345.
13.
KaraMAlpNC. Assessing the adoption of the Yavuz battleship application in the mixed reality environment using the technology acceptance model. Multimed Syst2024; 30(2): 76.
14.
Lugtu-PeaJAZhangXMirzaieS, et al.An emerging terpolymeric nanoparticle pore former as an internal recrystallization inhibitor of celecoxib in controlled release amorphous solid dispersion beads: experimental studies and molecular dynamics analysis. Acta Pharm Sin B2024; 14(6): 2669–2684.
15.
LiangXLiHLiX, et al.Highly sensitive H2O2-scavenging nano-bionic system for precise treatment of atherosclerosis. Acta Pharm Sin B2023; 13(1): 372–389.
16.
JenschkeTLde AmorimMDFdidaS. Nearby connections strategies: features, usage, and empirical performance evaluation. Internet of Things2023; 23: 100895.
17.
AmerAAAl-RazganMAbdallaHI, et al.Neighboring-aware hierarchical clustering: a new algorithm and extensive evaluation. Int J Semantic Web Inf Syst2024; 20(1): 1–24.
18.
YangYTLuYY. NICFS: a file system based on persistent memory and SmartNIC. Front Inform Technol Electron Eng2023; 24(5): 675–687.
19.
GuoRXJiangPXLiangRY, et al.A non-intrusive speech quality evaluation method based on the audiogram and weighted frequency information for hearing aid. IEICE Trans Fundamentals2023; E106A(1): 64–68.
20.
MalikALhachemiHShortenR. A cyber-physical system to design 3D models using mixed reality technologies and deep learning for additive manufacturing. PLoS One2023; 18(7): e0289207.
21.
RangelRLGimenezJMOñateE, et al.A continuum-discrete multiscale methodology using machine learning for thermal analysis of granular media. Comput Geotech2024; 168: 106118.
22.
XieYLiuXHObaidatMS, et al.Nondeterministic evaluation mechanism for user recruitment in Mobile crowd-sensing. ACM Trans Sens Netw2023; 19(2): 1–18.
23.
RadanovicMKhoshelhamKFraserC. Aligning the real and the virtual world: mixed reality localisation using learning-based 3D-3D model registration. Adv Eng Inform2023; 56: 101960.
24.
LiuMYangMWeiF, et al.A nonorthogonal uplink/downlink IoT solution for next-generation ISAC systems. IEEE Internet Things J2024; 11(5): 8224–8239.
25.
ChenZYLiangWZLuoSZ. A novel integrated picture fuzzy MACONT method and its application in teaching quality evaluation in higher education. IEEE Access2024; 12: 88345–88356.
26.
JalilibalZKaravighMHAMalekiMR, et al.Control charting methods for monitoring high dimensional data streams: a conceptual classification scheme. Comput Ind Eng2024; 191: 110141.
27.
BaryG. Analysis of chaos-coherence peculiarities within the chaotic phenomena of fluid at finite temperature. Chaos Solitons Fractals2022; 164: 112572.
28.
DawoodKAZaidanAASharifKY, et al.Novel multi-perspective usability evaluation framework for selection of open source software based on BWM and group VIKOR techniques. Int J Inf Technol Decis Making2023; 22(01): 187–277.
29.
YuCL. Computer interactive gesture recognition model based on improved YOLOv5 algorithm. Int J Comput Intell Syst2024; 17(1): 133.
30.
MendesAFSBlasHSSRobledoFP, et al.A novel multiagent system for cervical motor control evaluation and individualized therapy: integrating gamification and portable solutions. Multimed Syst2024; 30(3): 131.
31.
KhalilUUddinMMalikOA, et al.A novel NFT solution for assets digitization and authentication in cyber-physical systems: blueprint and evaluation. IEEE Open J Comput Soc2024; 5: 131–143.
32.
PandeyRJayanthGRKumarMSM. Comprehensive mathematical model for efficient and robust control of irrigation canals. Environ Model Software2024; 178: 106083.
33.
BaryGAhmedWAhmadR, et al.Novel techniques to analyze dynamical properties of quantum chaos with peculiar evidence of hybrid systems confinement. Sci Rep2024; 14(1): 11041.
34.
SumithraTVRaghaLVaishyaA, et al.Evolving usability heuristics for visualising augmented reality/mixed reality applications using cognitive model of information processing and fuzzy analytical hierarchy process. Cognitive Comp and Systems2024; 6(1-3): 26–35.
35.
YooJParkBYLeeWI, et al.A novel NLMS algorithm for system identification. Electronics2023; 12(14): 3159.
36.
XieYQHuangYL. A novel personalized recommendation model for computing advertising based on user acceptance evaluation. IEEE Access2023; 11: 140636–140645.
37.
LinKDLinBSSungHY, et al.Novel smart assistance system for arteriosclerosis evaluation. IEEE J Biomed Health Inform2023; 27(5): 2545–2552.
38.
MusunuriYRKimCKwonOS, et al.Object detection using ESRGAN with a sequential transfer learning on remote sensing embedded systems. IEEE Access2024; 12: 102313–102327.
39.
ShinMLeeH. Exploring the unique effects of virtual and mixed reality on students’ science learning intentions A serial mediation model of plausibility illusion and enjoyment. J Media Psychol2025; 37(2): 89–100.
