With the rapid development of online education, it has become crucial to assess and ensure the quality of online teaching in various fields, including sports rehabilitation. This paper aims to construct an evaluation index system for measuring the quality of online teaching in the context of sports rehabilitation and conduct empirical research to validate its effectiveness. In the construction of the evaluation index system, a comprehensive and systematic approach was adopted. Through literature review, expert consultation, and data analysis, a set of key indicators relevant to online teaching quality in sports rehabilitation was identified. These indicators cover various aspects, such as content design, teaching methods, interaction, assessment, and student satisfaction. To validate the effectiveness of the evaluation index system, empirical research was conducted. A sample of sports rehabilitation online courses was selected, and data was collected through surveys and assessments. The collected data were analyzed using statistical methods to examine the relationship between the evaluation index system and the overall teaching quality. The research findings indicate that the evaluation index system for online teaching quality in sports rehabilitation is reliable and valid. It effectively captures the essential elements that contribute to effective online teaching and provides a reliable measure of teaching quality. Moreover, it offers valuable insights and practical guidance for educators and institutions to enhance their online teaching practices in the field of sports rehabilitation.
| Published in | Education Journal (Volume 12, Issue 5) |
| DOI | 10.11648/j.edu.20231205.15 |
| Page(s) | 224-230 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2023. Published by Science Publishing Group |
Online Teaching Quality, Evaluation Index System, Sports Rehabilitation, Empirical Research
| [1] | Núez-Canal, Margarita, De Obesso, M. D. L. M., & Pérez-Rivero, Carlos Alberto. (2022). New challenges in higher education: a study of the digital competence of educators in covid times. Technological Forecasting and Social Change, 174. doi: 10.1016/j.techfore.2021.121270. |
| [2] | Wang, W., & Yin, G. (2021). Analysis and research on the application of internet technology in sports track and field teaching. Journal of Physics: Conference Series, 1881 (4), 042026 (7pp). doi: 10.1088/1742-6596/1881/4/042026. |
| [3] | Kabir, M. R., Islam, M. A., Kabir, M. R., & Islam, M. A. (2021). Extension of TAM explaining the determinants of I-banking adoption: Bangladesh perspective. 8th International Conference on Advanced Material Engineering & Technology (ICAMET2020). doi: 10.1063/5.0051656. |
| [4] | Nabeeha Tashkandi, Laura Taylor, Litaba Efraim Kolobe, Sharon Chellan & Loh Cheng Cheng. (2022). Optimizing Post-Surgical Pain Management in Adult Surgical Patients: Effects of Training Interventions on Surgical Nurses’ Knowledge. American Journal of Nursing Science (2). doi: 10.11648/J.AJNS.20221102.14. |
| [5] | Oliveira, K. K. D. S., & De Souza, R. A. C. (2022). Digital transformation towards education 4.0. Informatics in Education, 21. doi: 10.15388/infedu.2022.1. |
| [6] | Jiao, L., Sui, Y., Yang, G., Wang, P., Li, Q., & Chen, J., et al. (2021). The construction of the evaluation system of nurses' post‐training and the application of the system in 25 grade-a general hospitals in china. Nursing Open, 8 (1). doi: 10.1002/nop2.651. |
| [7] | Zheng, H., Yin, Q, Li, X., & Jie, X. (2021). Construction of Evaluation Index System for the Ecological Civilization in Rural Tourism Destinations. International Conference on Management Science and Engineering Management. Springer, Cham. doi: 10.1007/978-3-030-49889-4_18. |
| [8] | Wang, Y., Yun, L., & Sun, X. (2021). Construction of evaluation index system for the adaptability of narrowband Internet of things and power business. Journal of Physics Conference Series, 1748 (5), 052058. doi: 10.1088/1742-6596/1748/5/052058. |
| [9] | Kupiec, T., Dorota Celińska-Janowicz, & Valérie Pattyn. (2023). Understanding evaluation use from an organizational perspective: a review of the literature and a research agenda. Evaluation, 29 (3), 338-355. doi: 10.1177/13563890231185164. |
| [10] | Faith, L., James, R., Samia, M., Valeria, K., Parashkev, N., & Harpreet, H. (2023). Automated vasari feature set reporting for gliomas is efficient and effective. Neuro-Oncology (Supplement_3), Supplement_3. doi: 10.1093/neuonc/noad147.079. |
| [11] | Clarke, J., Langley-Johnson, C., Davies, B., Hughes, L., & Marks, J. (2022). Bsw long covid rehab assessment clinic – a service evaluation and future development. Physiotherapy. doi: 10.1016/j.physio.2021.12.141. |
| [12] | Sarahdiner. (2023). Potential consciousness of human cerebral organoids on similarity based views in precautionary discourse. Neuroethics, 16 (3). doi: 10.1007/s12152-023-09533-2. |
| [13] | Zhao, M., & Rabiei, K. (2023). Feasibility of implementing the human resource payroll management system based on cloud computing. Kybernetes: The International Journal of Systems & Cybernetics. |
| [14] | Santally, M. I., & Harrykrishna, P. (2008). Inculcating an innovative culture of e-learning at the uom: the case study of a gem module on "educational technology and computer-based learning environments". (1). |
| [15] | Liu, P., Wang, X., & Teng, F. (2021). Online teaching quality evaluation based on multi-granularity probabilistic linguistic term sets. Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology (5), 40. |
| [16] | Wei, Z. (2023). Metaverse-based online English teaching scheme in multi-source and cross-domain environment. Fractals. doi: 10.1142/s0218348x23401539. |
| [17] | Wang, F. (2022). Reliability Evaluation Model of Online Teaching Quality Based on Big Data Technology. IoT and Big Data Technologies for Health Care. Springer, Cham. doi: 10.1007/978-3-030-94185-7_26. |
| [18] | Li, T., Wang, W., Li, Z., Wang, H., & Liu, X. (2022). Problem-based or lecture-based learning, old topic in the new field: a meta-analysis on the effects of pbl teaching method in chinese standardized residency training. BMC Medical Education, 22 (1), 1-20. doi: 10.1186/s12909-022-03254-5. |
| [19] | Khirsheh, O., Yusuf, K., Dutta, A., Serino, C., & Rafiq, I. (2023). 295 education and training to improve compliance to the boast guidelines on assessing and documenting peripheral nerve status and injury. British Journal of Surgery (Supplement_7), Supplement_7. doi: 10.1093/bjs/znad258.656. |
| [20] | Ignatowicz, A., Slowther, A. M., Bassford, C., Griffiths, F., Johnson, S., & Rees, K. (2023). Evaluating interventions to improve ethical decision making in clinical practice: a review of the literature and reflections on the challenges posed. Journal of Medical Ethics, 49 (2), 136-142. doi: 10.1136/medethics-2021-107966. |
| [21] | Zhang, S., Liu, W., Wan, H., Bai, Y., Yang, Y., & Ma, Y., et al. (2023). Combing data-driven and model-driven methods for high proportion renewable energy distribution network reliability evaluation. International journal of electrical power and energy systems. |
| [22] | Pozo, C., Kozloski, G., Ribeiro-Filho, H., & Silveira, V. (2023). Evaluation of the pampa corte model for predicting dry matter intake and digestibility by sheep-fed tropical forages. Livestock Science. doi: 10.1016/j.livsci.2022.105147. |
| [23] | Nhi, V. V., Minh, M. T. H., & Hong, L. T. C. (2021). Factors affecting the application of the pbb model: review on the theoretical framework. doi: 10.2991/aebmr.k.211119.004. |
| [24] | Harguem, S., & Boubaker, K. B. (2023). Towards a simplified view of data management maturity models. Journal of Information & Knowledge Management, 22 (04). doi: 10.1142/S0219649223500375. |
| [25] | Li, Z. W. H. (2021). The effectiveness of physical education teaching in college based on artificial intelligence methods. Journal of intelligent & fuzzy systems: Applications in Engineering and Technology, 40 (2). |
| [26] | Darius, P. S. H., Gundabattini, E., & Solomon, D. G. (2021). A survey on the effectiveness of online teaching–learning methods for university and college students. Journal of The Institution of Engineers (India) Series B (2), 1-10. doi: 10.1007/s40031-021-00581-x. |
| [27] | Zou, B., Huang, L., Ma, W., & Qiu, Y. (2021). Evaluation of the effectiveness of EFL online teaching during the covid-19 pandemic. SAGE Open, 11. doi: 10.1177/21582440211054491. |
| [28] | Prat, J., Llorens, A., Salvador, F., Alier, M., & Amo, D. (2021). A methodology to study the university's online teaching activity from virtual platform indicators: the effect of the covid-19 pandemic at universitat politècnica de catalunya. Sustainability (9). doi: 10.3390/SU13095177. |
APA Style
Jianchang Ren, Haili Xiao. (2023). Construction and Empirical Research on the Evaluation Index System for Online Teaching Quality: A Case Study of Sports Rehabilitation . Education Journal, 12(5), 224-230. https://doi.org/10.11648/j.edu.20231205.15
ACS Style
Jianchang Ren; Haili Xiao. Construction and Empirical Research on the Evaluation Index System for Online Teaching Quality: A Case Study of Sports Rehabilitation . Educ. J. 2023, 12(5), 224-230. doi: 10.11648/j.edu.20231205.15
AMA Style
Jianchang Ren, Haili Xiao. Construction and Empirical Research on the Evaluation Index System for Online Teaching Quality: A Case Study of Sports Rehabilitation . Educ J. 2023;12(5):224-230. doi: 10.11648/j.edu.20231205.15
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Download@article{10.11648/j.edu.20231205.15,
author = {Jianchang Ren and Haili Xiao},
title = {Construction and Empirical Research on the Evaluation Index System for Online Teaching Quality: A Case Study of Sports Rehabilitation
},
journal = {Education Journal},
volume = {12},
number = {5},
pages = {224-230},
doi = {10.11648/j.edu.20231205.15},
url = {https://doi.org/10.11648/j.edu.20231205.15},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.edu.20231205.15},
abstract = {With the rapid development of online education, it has become crucial to assess and ensure the quality of online teaching in various fields, including sports rehabilitation. This paper aims to construct an evaluation index system for measuring the quality of online teaching in the context of sports rehabilitation and conduct empirical research to validate its effectiveness. In the construction of the evaluation index system, a comprehensive and systematic approach was adopted. Through literature review, expert consultation, and data analysis, a set of key indicators relevant to online teaching quality in sports rehabilitation was identified. These indicators cover various aspects, such as content design, teaching methods, interaction, assessment, and student satisfaction. To validate the effectiveness of the evaluation index system, empirical research was conducted. A sample of sports rehabilitation online courses was selected, and data was collected through surveys and assessments. The collected data were analyzed using statistical methods to examine the relationship between the evaluation index system and the overall teaching quality. The research findings indicate that the evaluation index system for online teaching quality in sports rehabilitation is reliable and valid. It effectively captures the essential elements that contribute to effective online teaching and provides a reliable measure of teaching quality. Moreover, it offers valuable insights and practical guidance for educators and institutions to enhance their online teaching practices in the field of sports rehabilitation.
},
year = {2023}
}
TY - JOUR T1 - Construction and Empirical Research on the Evaluation Index System for Online Teaching Quality: A Case Study of Sports Rehabilitation AU - Jianchang Ren AU - Haili Xiao Y1 - 2023/10/28 PY - 2023 N1 - https://doi.org/10.11648/j.edu.20231205.15 DO - 10.11648/j.edu.20231205.15 T2 - Education Journal JF - Education Journal JO - Education Journal SP - 224 EP - 230 PB - Science Publishing Group SN - 2327-2619 UR - https://doi.org/10.11648/j.edu.20231205.15 AB - With the rapid development of online education, it has become crucial to assess and ensure the quality of online teaching in various fields, including sports rehabilitation. This paper aims to construct an evaluation index system for measuring the quality of online teaching in the context of sports rehabilitation and conduct empirical research to validate its effectiveness. In the construction of the evaluation index system, a comprehensive and systematic approach was adopted. Through literature review, expert consultation, and data analysis, a set of key indicators relevant to online teaching quality in sports rehabilitation was identified. These indicators cover various aspects, such as content design, teaching methods, interaction, assessment, and student satisfaction. To validate the effectiveness of the evaluation index system, empirical research was conducted. A sample of sports rehabilitation online courses was selected, and data was collected through surveys and assessments. The collected data were analyzed using statistical methods to examine the relationship between the evaluation index system and the overall teaching quality. The research findings indicate that the evaluation index system for online teaching quality in sports rehabilitation is reliable and valid. It effectively captures the essential elements that contribute to effective online teaching and provides a reliable measure of teaching quality. Moreover, it offers valuable insights and practical guidance for educators and institutions to enhance their online teaching practices in the field of sports rehabilitation. VL - 12 IS - 5 ER -
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