Welcome to Francis Academic Press

Frontiers in Educational Research, 2023, 6(14); doi: 10.25236/FER.2023.061415.

Classroom Model of DanceSport in Universities Based on Internet Layered Teaching Method


Yijin Wang1,2

Corresponding Author:
Yijin Wang

1School of Media and Arts Institute of International Education, Tianjin University of Sport, Tianjin, China

2Philippine Christian University Center for International Education, Manila, 1004, Philippines


The purpose of offering dancesport courses is to cultivate sports talents with strong professional and comprehensive qualities. Layered teaching methods have been applied in many disciplines and have achieved significant results, effectively solving the problem of imbalanced classroom teaching caused by individual differences. Therefore, the use of hierarchical teaching methods in university dancesport teaching is an innovative and developmental teaching method. The purpose of this article is to study the classroom mode of dancesport in universities based on the Internet layered teaching method. Combining with the current situation of dancesport teaching in universities, focus has been on the research of dancesport teaching models based on the Internet layered teaching method, in order to make up for the shortcomings of traditional teaching models. Taking M Sports University as a case study, a teaching model was constructed based on multiple factors and the scientific and effective nature of the model was verified through rigorous teaching experiments. Through a comprehensive analysis of a series of evaluation feedback information, it was found that 70% of students are very receptive to the application of internet layered teaching in university dancesport classes.


Internet Age, Layered Teaching Method, College Classroom, Dancesport

Cite This Paper

Yijin Wang. Classroom Model of DanceSport in Universities Based on Internet Layered Teaching Method. Frontiers in Educational Research (2023) Vol. 6, Issue 14: 87-93. https://doi.org/10.25236/FER.2023.061415.


[1] Katerina El Raheb, Michele Buccoli, Massimiliano Zanoni, Akrivi Katifori, Aristotelis Kasomoulis, Augusto Sarti, Yannis E. Ioannidis. Towards a general framework for the annotation of dance motion sequences. Multim. Tools Appl. 82(3). 3363-3395 (2023)

[2] Naoko Abe. Beyond anthropomorphising robot motion and towards robot-specific motion. consideration of the potential of artist - dancers in research on robotic motion. Artif. Life Robotics 27(4). 777-785 (2022)

[3] Fabrízia de Souza Conceição, Paula de Faria Fernandes Martins, Anna Carolina Souza Marques, Geovana S. Minikovski, Mariana Inocêncio Matos, Bárbara Pessali-Marques. The Effects of a Low Volume Physical Training Program on Functional Movement and Strength in Dancers. Int. J. Art Cult. Des. Technol. 11(2). 1-12 (2022)

[4] Clara Fischer, Andersen Gracio Fagundes, Roberto Poton. Analysis of Current Tests for Assessing Dance Aesthetic Performance. A Systematic Review. Int. J. Art Cult. Des. Technol. 11(2). 1-9 (2022)

[5] Ljubojevic A, Popovic B, Bijelic S, et al. Proprioceptive training in dance sport. effects of agility skills. J. Turkish Journal of Kinesiology. 6(3).109-117 (2020)

[6] Hasko J, Rivera M C, Erbacher M K, et al. Visual Analysis Plus Hierarchical Linear Model Regressions. Morphosyntax Intervention with Deaf-and-Hard-of-Hearing Students. J. Communication Disorders Quarterly. 43(3).195-205 (2022)

[7] Mariana Inocêncio Matos, Elirez Bezerra da Silva. New Notes on the Cardiorespiratory Capacity of Dancers. A Narrative Review. Int. J. Art Cult. Des. Technol. 11(2). 1-11 (2022)

[8] Paulo H. L. Rettore. The Implantation of a Dance Workshop on the Quality of Life in the Work Environment. The Paola Rettore Method. Int. J. Art Cult. Des. Technol. 11(2). 1-9 (2022)

[9] Guangle Yin, Lu Wang. Teaching Effect Analysis and Behavior Detection of an Online Dance Learning Platform in the Context of COVID-19. Int. J. Inf. Syst. Serv. Sect. 14(3). 1-17 (2022)

[10] Lu-Ho Hsia, Gwo-Jen Hwang, Chi-Jen Lin. A WSQ-based flipped learning approach to improving students’ dance performance through reflection and effort promotion. Interact. Learn. Environ. 30(2). 229-244 (2022)

[11] Deepjyoti Kalita, Dipen Deka. Ontology for preserving the knowledge base of traditional dances (OTD). Electron. Libr. 38(4). 785-803 (2020)

[12] Beibei Guo. Analysis on Influencing Factors of Dance Teaching Effect in Colleges Based on Data Analysis and Decision Tree Model. Int. J. Emerg. Technol. Learn. 15(9). 245-257 (2020)

[13] Steven Landry, Myounghoon Jeon. Interactive sonification strategies for the motion and emotion of dance performances. J. Multimodal User Interfaces 14(2). 167-186 (2020)

[14] Fereshteh Behmanesh, Fatemeh Bakouei, Maryam Nikpour, Monireh Parvaneh. Comparing the Effects of Traditional Teaching and Flipped Classroom Methods on Midwifery Students’ Practical Learning. The Embedded Mixed Method. Technol. Knowl. Learn. 27(2). 599-608 (2022)

[15] Marina Prvan, Julije Ozegovic. Methods in Teaching Computer Networks. A Literature Review. ACM Trans. Comput. Educ. 20(3). 19.1-19.35 (2020)

[16] Dominik Raabe, Reinhard Nabben, Daniel Memmert. Graph representations for the analysis of multi-agent spatiotemporal sports data. Appl. Intell. 53(4). 3783-3803 (2023)

[17] Kanimozhi Soundararajan, Mala T. Sports highlight recognition and event detection using rule inference system. Concurr. Eng. Res. Appl. 30(2). 206-213 (2022)

[18] Hafsa Kabir Ahmad, Chao Qi, Zhenqiang Wu, Bello Ahmad Muhammad. ABiNE-CRS. course recommender system in online education using attributed bipartite network embedding. Appl. Intell. 53(4). 4665-4684 (2023)

[19] Monica Daniela Gomez Rios, Maximiliano Paredes-Velasco, Ruben Darío Hernández Beleño, José A. Fuentes-Pinargote. Analysis of emotions in the use of augmented reality technologies in education. A systematic review. Comput. Appl. Eng. Educ. 31(1). 216-234 (2023)

[20] Aisha Salim Ali Al-Harthi, Wajeha Thabit Al Ani. Learner readiness for MOOCs in Omani higher education institutions. disparities between projections and reality. Educ. Inf. Technol. 28(1). 303-319 (2023)