Effectiveness of Online Dance Teaching in College Dance Majors: Case of Jinjiang College of Sichuan University
Article Sidebar
Main Article Content
Abstract
Online is a popular media or pedagogical approach in schools these days, and dancing courses are no exception. Empirical research about the perceptions of students towards online dancing classes is rare. As a result, the goal of this study was to develop a model that explains students’ continuing support for online dance classes: based on the three stages of learning (pre-class preparation, in-class learning, and post-class revision) as a predictive base for student satisfaction, following the theory of planned behavior model. The comparative and parallel plots demonstrate considerable changes in perceptions between online and traditional dance learning phases, which have significant consequences. Furthermore, to confirm the suggested model guided by the theory of planned behavior, this work used structural equation modeling (SEM) analysis. Specifically, this study discovered that the quality of online dancing learning is the weakest link during the learning stage, after-class revisions and feedback have received favorable comparative responses compared to traditional online dancing learning, which has less revision demand; and the traditional dancing learning mode demonstrates the weakest link in the after-class stage, relating to revision materials provision. Similarly, the traditional learning approach has demonstrated some laxity in terms of pre-class preparation compared to online, which provides more extensive preparation by its very nature. The most significant contributions are twofold, first, satisfaction has been shown to be an important driver in influencing the attitudes, subjective norms, and perceived behavioral control of the students towards the online dance teaching mode, and thus, secondly, this study contributes to the theory of planned behavior from the role of satisfaction. For this study, the theory of planned behavior culminates in students showing continuing support for online dance teaching, which infers and reflects the effectiveness of the pedagogical interventions.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Views and opinions appearing in articles in the Journal of Arts of Management It is the responsibility of the author of the article. and does not constitute the view and responsibility of the editorial team I agree that the article is copyright of the Arts and Management Journal.
References
Ajzen, I. (1991). The theory of planned behavior, organizational behavior and human decision. Processes, 50(2),179-211.
An, J. S., & Thomas, N. (2021). Students’ beliefs about the role of interaction for science learning and language learning in EMI science classes evidence from high schools in China. Linguistics and Education, 65, 100972. https://doi.org/10.1016/j.linged.2021.100972
Brownmiller, S. N., & Dickinson, D.C. (1998). The literature of dance. Reflective Service Review, 16(1/2), 115-120. https://doi.org/10.1108/eb049019.
Buckler, B. (1996). A learning process model to achieve continuous improvement and innovation, The Learning Organization, 3(3), 31-39.
Catalano, T., Ganesan, U., Barbici-Wagner, A., Reeves, J., Leonard, A. E., & Wessels, S. (2021). Dance as dialog: a metaphor analysis on the development of interculturality through arts and community-based learning with preservice teachers and a local refugee community. Teaching and Teacher Education, 104, 103369. https://doi.org/10.1016/j.tate.2021.103369
Chan, K. H., Chong, L. L., & Ng, T. H. (2022). Integrating extended theory of planned behavior and norm activation model to examine the effects of environmental practices among Malaysian companies. Journal of Entrepreneurship in Emerging Economies. https://doi.org/ 10.1108/JEEE-08-2021-0317
Chao, H. S., Wu, C. C., & Tsai, C. W. (2021). Do socio-cultural differences matter? A study of the. learning effects and satisfaction with physical activity from digital learning assimilated into a university dance course. Computers & Education, 165, 104150.
https://doi.org/10.1016/j.compedu.2021.104150
Cheng, D., & Li, M. (2020). Screencast video feedback in online TESOL classes. Computers and Composition, 58, 102612. https://doi.org/10.1016/j.compcom.2020.102612
Cordano, M., & Frieze, I. H. (2000). Pollution reduction preferences of U.S. environmental managers: Applying Ajzen’s theory of planned behavior. Academy of Management Journal, 43(4), 627-641. https://doi.org/10.2307/1556358
Cunningham, G. B. (2007). Development of the physical activity class satisfaction questionnaire (PACSQ). Measurement in Physical Education and Exercise Science, 11(3), 161-176. https://doi.org/10.1080/10913670701326443.
Curatman, A., Suroso, A., & Suliyanto (2021). Loyalty program and communication effectiveness as drivers of store loyalty. Measuring Business Excellence, Doi: 10.1108/MBE-11-2020-0154.
Dodge, Y. (2008). The concise encyclopedia of statistics. Springer.
dos Santos, A. D. P, Loke, L., Yacef, K., & Martinez-Maldonado, R. (2022). Enriching teachers’ assessments of rhythmic Forró dance skills by modeling motion sensor data. International Journal of Human-Computer Studies, 161, 102776. https://doi.org/10.1016/j.ijhcs.2022. 102776.
Douglah, J. (2021). Boom, so it will be like an attack demonstrating in a dance class through verbal, sound and body imagery, Learning. Culture and Social Interaction, 29, 100488. https://doi.org/10.1016/j.lcsi.2020.100488.
Gonick, L. (1993). The cartoon guide to statistics. Harper Perennial.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis. Pearson Education.
Hancox, J. E., Quested, E., Ntoumanis, N., & Duda, J. L. (2017). Teacher-created social environment, basic psychological needs, and dancers’ affective states during class: a diary study. Personality and Individual Differences, 115, 137–143. https://doi.org/10.1016/j.paid. 2016.03.033.
Hanninen, N., & Karjaluoto, H. (2017). The effect of marketing communication on business relationship loyalty. Marketing Intelligence & Planning, 35(4), 458-472. Doi: 10.1108/MIP-01-2016-0006.
Hayward, K., Brown, M., Pendergast, N., Nicholson, M., Newell, J., Fancy, T., & Cameron, H. (2021). IPE via online education: pedagogical pathways spanning the distance. Journal of Interprofessional Education & Practice, 24, 100447. https://doi.org/10.1016/j.xjep.2021. 100447.
Hu, M., & Wang, J. (2021). Artificial intelligence in dance education: dance for students with special educational needs. Technology in Society, 67, 101784. https://doi.org/10.1016/ j.techsoc.2021.101784.
Hutain, J., & Michinov, N. (2022). Improving student engagement during in-person classes by using functionalities of a digital learning environment. Computers & Education, 183, 104496. https://doi.org/1010.1016/j.compedu.2022.104496.
Jose, K. A., & Sia, S. K. (2022). Theory of planned behavior in predicting the construction of eco-friendly houses. Management of Environmental Quality, 33(4), 938-954. https://doi.org/ 10.1108/MEQ-10-2021-0249.
Klein, G. (2013). The cartoon introduction to statistics. Hill & Wamg.
Laird, K. T., Vergeer, I., Hennelly, S. E., & Siddarth, P. (2021). Conscious dance: Perceived benefits and psychological well-being of participants. Contemporary Therapies in Clinical Practice, 44, 101440. https://doi.org/10.1016/j.ctcp.2021.101440.
Launay, F., Menard, M., Bourgin, M., Mhadhbi, H., Sutre, F., & Draper-Rodi, J. (2021). Impact of different types of revision materials on the learning of musculoskeletal techniques. International Journal of Osteopathic Medicine, 39, 47-53. https://doi.org/1010.1016/j.ijosm. 2020.08.003.
Lin, Y. N., Hsia, L. H., & Hwang, G. J. (2021). Promoting pre-class guidance and in-class reflection: A SQIRC-based mobile flipped learning approach to promoting students’ billiards skills, motivation and self-efficacy. Computers & Education, 160, 104035. https://doi.org/10. 1016/j.compedu.2020.104035.
Lorenza, L., & Carter, D. (2021). Emergency online teaching during COVID-19: a case study of Australian tertiary students in teacher education and creative arts. International Journal of Educational Research Open, 2, 100057. https://doi.org/10.1016/j.ijedro.2021.100057.
Naeve, A., Sicilia, M. A., & Lytras, M. D. (2008). Learning processes and processing learning: from organizational needs to learning designs. Journal of Knowledge Management, 12(6), 5-14. https://doi.org/10.1108/13673270810913586.
Niu, L. G. (2019). Decision-making determinants of students participating in MOOCs: Merging the theory of planned behavior and self-regulated learning model. Computers & Education, 134, 50-62. https://doi.org/10.1016/j.compedu.2019.02.004.
Romero-Colmenares, L. M., & Reyes-Rodriguez, J. F. (2022). Sustainable entrepreneurial intentions: exploration of a model based on the theory of planned behavior among university students in north-east Colombia. International Journal of Management Education, 20, 100627. https://doi.org/10.1016/j.ijme.2022.100627
Shailesh, S., & Judy, M. V. (2022). Understanding dance semantics using spatio-temporal features coupled GRU networks. Entertainment Computing, 42, 100484. https://doi.org/10.1016/ j.entcom.2022.100484
Shin, S., Lee, K. Y., & Yang, S. B. (2017). How do uncertainty reduction strategies influence social networking site fan page visiting? Examining the role of uncertainty reduction strategies, loyalty and satisfaction in continuous visiting behavior. Telematics and Informatics, 34, 449-462. https://doi.org/10.1016/j.tele.2016.09.005.
Soot, A., & Viskus, E. (2014). Contemporary approaches to dance pedagogy – the challenges of the 21st century. Procedia – Social and Behavioral Sciences, 112, 290-299. https://doi.org/ 10.1016/j.sbspro.2014.01.1167.
Stewart, M. K. (2021). Social presence in online writing instruction: distinguishing between presence, comfort, attitudes, and learning. Computers and Composition, 62, 102669. https://doi.org/10.1016/j.compoem.2021.102669.
Sun, Z., & Xie, K. (2020). How do students prepare in the pre-class setting of a flipped undergraduate math course? A latent profile analysis of learning behavior and the impact of achievement goals. The Internet and Higher Education, 46, 100731. https://doi.org/ 10.1016/j.iheduc.2020.100731.
Tan, C. C. (2010). Beyond green ocean strategies to a Buddhist theory of learning based on mindfulness training at our Citta (heart-mind, consciousness) level directly. NIDA Human Resource and Organization Development Journal, 1, 19-64.
Tan, C. C. (2022). A Buddhist-spirituality base for artificial intelligence applications through conscious subjects. ASEAN Journal of Religious and Cultural Research, 5(2), 1-10.
Tan, C. C., Damdoen, S., Toprayoon, Y., Dabjan, N., & Damkan, K. (2022). An exploratory study of the spirituality-oriented experiences of tourists. In Srivastava, P., Thakur, S.S., Oros, G.I., AlJarrah, A.A., & Laohakosol, V. (Eds.). Mathematical, Computational Intelligence and Engineering Approaches for Tourism, Agriculture and Healthcare. Lecture Notes in Networks and Systems, 214. https://doi.org/10.1007/978-981-16-3807-7_25.
Tian, P. P. (2020). The challenges and opportunities of suspended classes and non-stop learning – a case study based on internet+ dance practice course. Dance, 3, 13-17.
Tseng, T. H., Wang, Y. M., Lin, H. H., Lin, S. J., Wang, Y. S., & Tsai, T. H. (2022). Relationships between locus of control, theory of planned behavior, and cyber entrepreneurial intention: the moderating role of cyber entrepreneurship education. The International Journal of Management Education, 20, 100682. https://doi.org/10.1016/j.ijme.2022.100682.
Vogt, W. P. (2005). Dictionary of statistics & methodology: A nontechnical guide for the social sciences. SAGE.
Wang, A. I., & Tahir, R. (2020). The effect of using Kahoot! For learning – a literature review. Computers and Education, 149, 103818. https://doi.org/10.1016/j.compedu.2020.103818.
Wang, Z. (2022). RETRACTED: Modern social dance teaching approaches: Studying creative and communicative components. Thinking skills and creativity, 43, 100974. https://doi.org/10. 1016/j.tsc.2021. 100974.
Wu, H. (2021). Design of embedded dance teaching control system based on FPGA and motion recognition processing. Microprocessors and Microsystems, 83, 103990. https://doi.org/10. 1016/j.micpro.2021.103990
Wu, M., & Wang, J. (2021). Artificial intelligence in dance education: dance for students with special. educational needs. Technology in Society, 67, 101784. https://doi.org/10.1016/ j.techsoc.2021.101784.
Xuto, P., Amphai, S., Srisawang, J., Chaiwuth, S., Prasitwattanaseree, P., Khwanngern, P., Sansirphun, N., Khetwang, K., & Sriarporn, P. (2022). Delivering midwifery concepts to undergraduate nursing students: a comparison study of the online flipped learning with the traditional in-class pedagogy. Teaching and Learning in Nursing, 17, 195-198. https://doi.org/10.1016/j.teln.2021.12.005
Zhao, Y. (2022). Teaching traditional Yao dance in the digital environment: forms of managing. subcultural forms of cultural capital in the practice of local creative industries. Technology in Society, 69, 101943. https://doi.org/10.1016/j.techsoc.2022.101943