Skip to main content
SpringerLink
Log in

Enhancing online learning for dance majors: A customized teaching approach using massive open online courses

  • Published:
Education and Information Technologies Aims and scope Submit manuscript

Abstract

The purpose of this study was to investigate the correlation among the components affecting MOOC ability to learn the Chinese dance majors. MOOC courses are easy to register and access whereas SPOC derived from MOOC allows access to selected students. MOOC implementing AI for teaching improves the quality of courses as AI determines content with data stored for subject and analysis in a short span. The subjects of this study are 200 dance students from Hanan Mass Media Vocational and Technical College in China. The researchers collected questionnaires based on the components affecting MOOC learning adaptability face-to-face one-on-one. The collected questionnaire data used in this study were analyzed by SPSS. As a result of the research, learning motivation, learning self-efficacy, MOOC platform, course content quality, learning support and teacher teaching are all important factors affecting learning adaptability. In this way, it not only provides guidance for MOOC teaching, but also provides help for dance students to adapt to MOOC learning.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Code availability

Not applicable.

References

  • Adams, N. R. (2021). Self-efficacy of college students with a learning disability during freshman year (Doctoral dissertation, Walden University).

  • Afdhalina, A. (2022). The effect of reading strategis and learning styles on the students achievement in reading comprehension. Jurnal Scientia, 10(2), 172–186.

    Google Scholar 

  • Alqurashi, E. (2019). Predicting student satisfaction and perceived learning within online learning environments. Distance Education, 40(1), 133–148.

    Article  Google Scholar 

  • Anand Shankar Raja, M., & Kallarakal, T. K. (2021). COVID-19 and students perception about MOOCs, a case of indian higher educational institutions. Interactive Technology and Smart Education, 18(3), 450–474.

    Article  Google Scholar 

  • Astaiza, A. R. C., Astaiza, C. P. B., & Sarasty, M. F. S. (2021). Challenges of converting an in-person dance course to a MOOC course. Revista Ingenierías Universidad de Medellín, 20(38), 119–131.

    Article  Google Scholar 

  • Astaiza, Y., Yue, Q., & Jiqiong, Y. (2020). Research on online and offline blended teaching mode based on “MOOC +SPOC +flipped class.” Learning Disability Quarterly, 34(1), 9–20.

  • Asyhari, A., & Islamia, I. (2023). The influence of massive open online courses (moocs) and face-to-face learning on motivation and self-regulated learning (srl). Journal of Educators Online, 20(1), 122–124.

    Google Scholar 

  • Averill, R. M., & Major, J. (2020). What motivates higher education educators to innovate? Exploring competence, autonomy, and relatedness–and connections with wellbeing. Educational Research, 62(2), 146–161.

    Article  Google Scholar 

  • Bárkányi, Z. (2021). Motivation, self-efficacy beliefs, and speaking anxiety in language MOOCs. ReCALL, 33(2), 143–160.

    Article  Google Scholar 

  • Baszuk, P. A., & Heath, M. L. (2020). Using Kahoot! To increase exam scores and engagement. Journal of Education for Business, 95(8), 548–552.

    Article  Google Scholar 

  • Belarbi, N., Chafiq, N., Talbi, M., Namir, A., & Benlahmar, H. (2019). A recommender system for videos suggestion in a SPOC: A proposed personalized learning method. Big Data and Smart Digital Environment (pp. 92–101). Springer International Publishing.

  • Bokayev, B., Torebekova, Z., Davletbayeva, Z., & Zhakypova, F. (2021). Distance learning in Kazakhstan: Estimating parent’s satisfaction of educational quality during the coronavirus. Technology Pedagogy and Education, 30(1), 27–39.

    Article  Google Scholar 

  • Cai, S., Liu, C., Wang, T., Liu, E., & Liang, J. C. (2021). Effects of learning physics using augmented reality on students’ self-efficacy and conceptions of learning. British Journal of Educational Technology, 52(1), 235–251.

    Article  Google Scholar 

  • Carroll, M. W. (2021). Rules of engagement: Copyright and automated gatekeepers’ influence on creative expression. Seton Hall Law Review, 52, 1137.

    Google Scholar 

  • Castro, M. D. B., & Tumibay, G. M. (2021). A literature review: Efficacy of online learning courses for higher education institution using meta-analysis. Education and Information Technologies, 26, 1367–1385.

    Article  Google Scholar 

  • Chen, Y. (2021, April). Dance teaching activities in the context of informatization. In Journal of Physics: Conference Series. IOP Publishing, 1852(2), 022049.

  • Chua, S. M. (2022). Discourse practices in MOOC discussions. Open World Learning, 76(2), 66–67.

    Google Scholar 

  • Coates, J. K., Harris, J., & Waring, M. (2020). The effectiveness of a special school experience for improving preservice teachers’ efficacy to teach children with special educational needs and disabilities. British Educational Research Journal, 46(5), 909–928.

    Article  Google Scholar 

  • Conde Gafaro, B. (2022). First steps towards self-regulated learning. Setting goals in MOOCs, 44(3), 63–75.

    Google Scholar 

  • Dang, Y., & Chen, L. (2021, January). An empirical study on the curriculum design for dance teachers in china. In6th Annual International Conference on Social Science and Contemporary Humanity Development (SSCHD 2020) (pp. 434–439). Atlantis Press.

  • Deng, R., & Gao, Y. (2023). Using learner reviews to inform instructional video design in MOOCs. Behavioral Sciences, 13(4), 330.

    Article  PubMed  PubMed Central  Google Scholar 

  • Filgona, J., Sakiyo, J., Gwany, D. M., & Okoronka, A. U. (2020). Motivation in learning. Asian Journal of Education and Social Studies, 10(4), 16–37.

    Article  Google Scholar 

  • Gunder, A., Vignare, K., Adams, S., McGuire, A., & Rafferty, J. P. (2021). Optimizing High-Quality Digital Learning Experiences: A Playbook for Faculty. Online Learning Consortium.

  • Guo, H., Zou, S., Xu, Y., Yang, H., Wang, J., Zhang, H., & Chen, W. (2022). DanceVis: Toward better understanding of online cheer and dance training. Journal of Visualization, 25(1), 159–174.

    Article  Google Scholar 

  • Hava, K. (2021). Exploring the role of digital storytelling in student motivation and satisfaction in EFL education. Computer Assisted Language Learning, 34(7), 958–978.

    Article  Google Scholar 

  • Hou, Y. (2022, December). The Collision of Digital Tools and Dance Education During the Period of COVID-19. In 2022 2nd International Conference on Modern Educational Technology and Social Sciences (ICMETSS 2022) (pp.844–852). Atlantis Press.

  • Hsia, L. H., & Sung, H. Y. (2020). Effects of a mobile technology-supported peer assessment approach on students’ learning motivation and perceptions in a college flipped dance class. International Journal of Mobile Learning and Organisation, 14(1), 99–113.

    Article  Google Scholar 

  • Huang, R. H., Liu, D. J., Tlili, A., Yang, J. F., & Wang, H. H. (2020). Handbook on facilitating flexible learning during educational disruption: The Chinese experience in maintaining undisrupted learning in COVID-19 outbreak. Beijing: Smart Learning Institute of Beijing Normal University, 46.

  • Iniesto, F., & Hillaire, G. (2022). UDL and its implications in MOOC accessibility evaluation. Open world learning: research, innovation and the challenges of high-quality education (pp. 208–224).

  • Iniesto, F., Rodrigo, C., & Hillaire, G. (2019). Applying UDL principles in an inclusive design project based on MOOCs reviews. Universal Access through Inclusive Instructional Design (pp. 197–207). Routledge.

  • Kang, J., Kang, C., Yoon, J., Ji, H., Li, T., Moon, H., & Han, J. (2023). Dancing on the inside: A qualitative study on online dance learning with teacher-AI cooperation. Education andInformation Technologies, 12(3), 1–31.

    Google Scholar 

  • Karyati, D., Sabaria, R., Mariah, Y. S., & Budiman, A. (2022, June). Online Learning Design in Dance Studios as Anticipation of Social Distancing in the Pandemic Era. In 4th International Conference on Arts and Design Education (ICADE 2021) (pp.75–80). Atlantis Press.

  • Kemp, N. (2020). University student’s perceived effort and learning in face-to-face and online classes. Journal of Applied Learning and Teaching, 3(1), 69–77.

    Google Scholar 

  • Khan, T., Johnston, K., & Ophoff, J. (2019). The impact of an augmented reality application on learning motivation of students. Advances in Human-Computer Interaction, 20(19), 12–14.

    Google Scholar 

  • Korir, M., Mittelmeier, J., & Rienties, B. C. (2019). Is mixed methods social network analysis ethical?.

  • Lewin, C. (1997). Test driving CARS: Addressing the issues in the evaluation of computer-assisted Reading Software. Journal of Computing in Childhood Education, 8(6), 44–49.

    Google Scholar 

  • Li, Z. (2021). Creativity and opportunity: How COVID-19 fosters digital dance education. Digital Creativity, 32(3), 188–207.

    Article  Google Scholar 

  • Li, Y. (2019, May). MOOCs in higher education: opportunities and challenges. In 2019 5th International Conference on Humanities and Social Science Research (ICHSSR 2019) (pp.48–55). Atlantis Press.

  • Li, Z., Zhou, M., & Lam, K. K. L. (2022). Dance in Zoom: Using video conferencing tools to develop students’ 4 C skills and self-efficacy during COVID-19. Thinking Skills and Creativity, 46, 101102.

    Article  PubMed  PubMed Central  Google Scholar 

  • Liu, H. (2020a). Analysis on the reform path of college dance teaching in the internet era. Frontiers in Educational Research, 3(14), 66–69.

    Google Scholar 

  • Liu, L. (2020). Explore the Cultivation Mode of College students’ creative thinking in Dance Teaching in Colleges and Universities. Lifelong Education, 9(4), 116–117.

    Article  MathSciNet  Google Scholar 

  • Liyanagunawardena, T. R., Lundqvist, K., Mitchell, R., Warburton, S., & Williams, S. A. (2019). A MOOC taxonomy based on classification schemes of MOOCs. European Journal of Open Distance and E-learning, 22(1), 85–103.

    Article  Google Scholar 

  • Ma, L., & Lee, C. S. (2023). Leveraging MOOCs for learners in economically disadvantaged regions. Education and Information Technologies, 14(7), 1–26.

    Google Scholar 

  • Ma, N., Li, Y. M., Guo, J. H., Laurillard, D., & Yang, M. (2022). A learning model for improving in-service teachers’ course completion in MOOCs. Interactive Learning Environments, 21(7), 1–16.

    CAS  Google Scholar 

  • Mian, Z., Bai, Y., & Ur, R. K. (2021, June). Research on College Computer-Computing and Information Literacy online course based on MOOC: taking the North Minzu University as an example. In 2021 IEEE 3rd International Conference on Computer Science and Educational Informatization (CSEI) IEEE (pp. 300–306).

  • Pham, L., Limbu, Y. B., Bui, T. K., Nguyen, H. T., & Pham, H. T. (2019). Does e-learning service quality influence e-learning student satisfaction and loyalty? Evidence from Vietnam. International Journal of Educational Technology in Higher Education, 16(1), 1–26.

    Article  Google Scholar 

  • Qin, J., & Fu, G. S. (2019). Research on influencing factors and intervention of college students’ blended learning adaptability based on MOOC (Doctoral dissertation, Shaanxi Normal University).

  • Rabin, E., Henderikx, M., Yoram, M. K., & Kalz, M. (2020). What are the barriers to learners’ satisfaction in MOOCs and what predicts them? The role of age, intention, self-regulation, self-efficacy and motivation. Australasian Journal of Educational Technology, 36(3), 119–131.

    Article  Google Scholar 

  • Rahiem, M. D. (2021). Remaining motivated despite the limitations: University students’ learning propensity during the COVID-19 pandemic. Children and Youth Services Review, 120, 105802.

  • Rizvi, S., Rienties, B., Rogaten, J., & Kizilcec, R. (2022a). Culturally adaptive learning design. Open World Learning, 103(1), 39–43.

    Google Scholar 

  • Rizvi, S., Rienties, B., Rogaten, J., & Kizilcec, R. F. (2022b). Beyond one-size-fits-all in MOOCs: Variation in learning design and persistence of learners in different cultural and socioeconomic contexts. Computers in Human Behavior, 126, 106973.

    Article  Google Scholar 

  • Rodrigo, C., Iniesto, F., & García-Serrano, A. (2020). Reflections on instructional design guidelines from the MOOCification of distance education: A case study of a course on design for all. UXD and UCD Approaches for Accessible Education (pp. 21–37). IGI Global.

  • Ruipérez-Valiente, J. A., Martin, S., Reich, J., & Castro, M. (2020). The unMOOCing process: Extending the impact of MOOC educational resources as OERs. Sustainability, 12(18), 7346.

    Article  Google Scholar 

  • Ruipérez-Valiente, J. A., Staubitz, T., Jenner, M., Halawa, S., Zhang, J., Despujol, I., & Reich, J. (2022). Large scale analytics of global and regional MOOC providers: Differences in learners’ demographics, preferences, and perceptions. Computers & Education, 180, 104426.

    Article  Google Scholar 

  • Shao, K., Kutuk, G., Fryer, L. K., Nicholson, L. J., & Guo, J. (2023). Factors influencing chinese undergraduate students’ emotions in an online EFL learning context during the COVID pandemic. Journal of Computer Assisted Learning, 91(4), 37–38.

    Google Scholar 

  • Sharma, P. C., & Pandey, A. (2023). Significance of e-Learning in indian Modern Higher Education System: A review. Redefining Virtual Teaching Learning Pedagogy, 97–109.

  • Sheffler, P., Rodriguez, T. M., Cheung, C. S., & Wu, R. (2022). Cognitive and metacognitive, motivational, and resource considerations for learning new skills across the lifespan. Wiley Interdisciplinary Reviews: Cognitive Science, 13(2), e1585.

  • Shin, M., & Hickey, K. (2021). Needs a little TLC: Examining college students’ emergency remote teaching and learning experiences during COVID-19. Journal of Further and Higher Education, 45(7), 973–986.

    Article  Google Scholar 

  • Siddique, M., Hassan, K. H. U., & Akmal, F. (2023). The role of resilience for developing the self-efficacy among chemistry students in Pakistan. Linguistics & Education, 31(2), 187–206.

    Google Scholar 

  • Sugden, N., Brunton, R., MacDonald, J., Yeo, M., & Hicks, B. (2021). Evaluating student engagement and deep learning in interactive online psychology learning activities. Australasian Journal of Educational Technology, 37(2), 45–65.

    Article  Google Scholar 

  • Sugiarto, E., & Lestari, W. (2020). The collaboration of visual property and semarangan dance: A case study of student creativity in “Generation Z. International Journal of Innovation Creativity and Change, 10(12), 100–110.

    Google Scholar 

  • Tang, J. K., Xie, H., & Wong, T. L. (2015). A big data framework for early identification of dropout students in MOOC. In Technology in Education. Technology-Mediated Proactive Learning: Second International Conference, ICTE 2015, Hong Kong, China, July 2–4, 2015, Revised Selected Papers 2 (pp.127–132). Springer Berlin Heidelberg.

  • Tian Le, Z., Weixin, R., & Yue, Z. (2022, April). Research on improvement scheme of MOOC based on sequential recommendation algorithm and big data. In Proceedings of the 7th International Conference on Information and Education Innovations (pp.13–17).

  • Wang, Y. (2019). Artistic innovation of dance education in the context of cultural communication. Learning Culture and Social Interaction, 3(12), 134–1.

    Google Scholar 

  • Wang, Y., & Zheng, G. (2020). Application of artificial intelligence in college dance teaching and its performance analysis. International Journal of Emerging Technologies in Learning (iJET), 15(16), 178–190.

    Article  Google Scholar 

  • Wang, Q., Khan, M. S., & Khan, M. K. (2021). Predicting user perceived satisfaction and reuse intentions toward massive open online courses (MOOCs) in the Covid-19 pandemic: An application of the UTAUT model and quality factors. International Journal of Research in Business and Social Science (2147–4478), 10(2), 1–11.

  • Wilde, N., & Hsu, A. (2019). The influence of general self-efficacy on the interpretation of vicarious experience information within online learning. International Journal of Educational Technology in Higher Education, 16(1), 1–20.

    Article  Google Scholar 

  • Xie, X., Siau, K., & Nah, F. F. H. (2020). COVID-19 pandemic–online education in the new normal and the next normal. Journal of Information Technology Case and Application Research, 22(3), 175–187.

    Article  Google Scholar 

  • Yang, L. H. (2021). Online learning experiences of Irish University students during the COVID-19 pandemic. All Ireland Journal of Higher Education, 13(1), 11–20.

  • Yang, Q., & Lee, Y. C. (2021). The critical factors of student performance in MOOCs for sustainable education: A case of chinese universities. Sustainability, 13(14), 8089.

    Article  Google Scholar 

  • You, Y. (2022). Online technologies in dance education (China and worldwide experience). Research in Dance Education, 23(4), 396–412.

    Article  Google Scholar 

  • Zhao, H. (2019). A Summary of the Research on the Teaching Mode of MOOCs. Open Journal of Social Sciences, 7(02), 96.

    Article  Google Scholar 

  • Zhou, H., Sulee, W., & Wang, Z. (2022). The impact of curriculum innovation on student’s learning ability: An empirical study from primary and secondary schools in Guizhou, China.

  • Zulfikar, M. T. (2023). Improve learning programming through small private online course and virtual IDE. Engineering MAthematics and Computer Science (EMACS) Journal, 5(1), 7–10.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Film and Television Arts, Hunan Mass Media Vocational and Technical College, Hunan, China

    Jiazi Li, Jue Wang & Wei Ren

  2. School of Education, Sehan University, Yeongam-gun, South Korea

    Jiazi Li & Heung Kou

Authors
  1. Jiazi Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Heung Kou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jue Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wei Ren
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wei Ren.

Ethics declarations

Ethics approval

This article does not contain any studies with human participants.

Human and animal rights

This article does not contain any studies with human or animal subjects performed by any of the authors

Informed consent

Informed consent was obtained from all individual participants included in the study.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, J., Kou, H., Wang, J. et al. Enhancing online learning for dance majors: A customized teaching approach using massive open online courses. Educ Inf Technol 29, 5139–5167 (2024). https://doi.org/10.1007/s10639-023-11957-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10639-023-11957-5

Keywords

Search

Navigation