مطالعه کیفی ابعاد هوش مصنوعی در رشته علوم ورزشی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری مدیریت ورزشی، گروه رفتار حرکتی و مدیریت ورزشی، دانشکده علوم ورزشی، دانشگاه اصفهان، اصفهان، ایران.

2 استادیار مدیریت ورزشی، گروه رفتار حرکتی و مدیریت ورزشی، دانشکده علوم ورزشی، دانشگاه اصفهان، اصفهان، ایران.

چکیده

هدف از پژوهش حاضر مطالعه کیفی ابعاد هوش مصنوعی در رشته علوم ورزشی می‌باشد. روش تحقیق کیفی و به روش تحلیل مضمون انجام شد. طی نمونه‌گیری به روش‌های هدفمند و گلوله‌برفی با ۲۳ نفر از کارشناسان و خبرگان فعال در حوزه‌های رسانه و ارتباطات، هوش مصنوعی و علوم ورزشی مصاحبه‌های نیمه‌ساختاریافته به عمل آمد. انجام مصاحبه‌ها تا رسیدن داده‌ها به مرحله اشباع نظری ادامه یافت. داده‌های استخراج شده از متن مصاحبه‌ها با استفاده از روش تحلیل تم، تجزیه‌وتحلیل شدند. پس از تحلیل و کدگذاری داده‌ها، سه تم اصلی شامل فرصت‌های هوش مصنوعی در علوم ورزشی (۵ تم فرعی و ۲۳ مفهوم)، تهدیدهای هوش مصنوعی در علوم ورزشی (۶ تم فرعی و ۲۱ مفهوم) و راهکارهای مدیریت هوش مصنوعی در حوزه علوم ورزشی (۸ تم فرعی و ۲۴ مفهوم) دسته‌بندی شدند. در مجموع، ابعاد شناسایی شده در قالب ۳ تم اصلی، ۱۹ تم فرعی و ۶۸ مفهوم دسته‌بندی شدند. پیشنهاد می‌شود جهت توانمندسازی اساتید، دانشجویان و کارکنان دانشگاه‌ها دوره‌های کاربردی هوش مصنوعی که دربرگیرنده کارکردها و تهدیدات این فناوری است، برگزار شود. علاوه ‌بر آن، سیاست‌های آموزشی و پژوهشی دانشگاه‌ها باید مبتنی بر ورود این فناوری مورد بازبینی قرار گیرد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Qualitative Analysis of Artificial Intelligence Dimensions in the Field of Sports Science

نویسندگان [English]

  • Amir Hossein Labbaf 1
  • Mohsen Vahdani 2
1 Ph.D. Candidate, Department of Motor Behavior and Sport Management, Faculty of Sport Sciences, University of Isfahan, Isfahan, Iran.
2 Assistant Professor, Department of Motor Behavior and Sport Management, Faculty of Sport Sciences, University of Isfahan, Isfahan, Iran.
چکیده [English]

This qualitative study investigates artificial intelligence dimensions in the field of sports science. Semi-structured interviews were conducted with 23 experts active in the fields of media and communication, artificial intelligence, and sports science through targeted and snowball sampling. Conducting interviews continued until the data reached the theoretical saturation stage. The data extracted from the text of the interviews were analyzed using the theme analysis method. After analyzing and coding the data, three main themes including the opportunities of artificial intelligence in sports science (5 sub-themes and 23 concepts), the threats of artificial intelligence in sports science (6 sub-themes and 21 concepts) and the solutions of intelligence management synthetics were categorized in the field of sports science (8 sub-themes and 24 concepts). In total, the identified dimensions were categorized into 3 main themes, 19 sub-themes and 68 concepts. To empower professors, students, and university employees, it is suggested to hold artificial intelligence courses that include the functions and threats of this technology. In addition, the educational and research policies of universities should be reviewed based on the introduction of this technology.

کلیدواژه‌ها [English]

  • Technology
  • Education
  • Research
  • University
Abd-Alrazaq, A., AlSaad, R., Aziz, S., Ahmed, A., Denecke, K., Househ, M., ..., & Sheikh, J. (2023). Wearable artificial intelligence for anxiety and depression: scoping review. Journal of Medical Internet Research, 25, e42672. https://doi.org/10.2196/42672
Abolghasemi Atany, S. , Rahimizadeh, M. and Monazami, A. H. (2024). Designing an Artificial Intelligence-Based Electronic Marketing Pattern in the Iranian Sports Industry. Communication Management in Sport Media, (), -. https://doi.org/10.30473/jsm.2024.69704.1817
AmirHoseni, S. E. , Lotfi, G. and Asadoallhi, S. (2023). Presenting the knowledge ecosystem development model in Iranian school sports with emphasis on new technologies. Communication Management in Sport Media, (), -. https://doi.org/10.30473/jsm.2023.66518.1710
Adadi, A., & Berrada, M. (2018). Peeking inside the black-box: A survey on explainable artificial intelligence (XAI). IEEE Access, 6, 52138-52160. https://doi.org/10.1109/ACCESS.2018.2870052
Agrawal, P., Narain, R., & Ullah, I. (2019). Analysis of barriers in implementation of digital transformation of supply chain using interpretive structural modelling approach. Journal of Modelling in Management, 15(1), 297-317.‏ https://doi.org/10.1108/JM2-03-2019-0066
Badami, M. A., Meghdadi, M. M., & Pilevar, M. (2022). Investigating the Impact of Cyberspace on the Abuse of the Right to Raise a Child with Emphasis on Religious Education. Journal of Legal Research, 21(50), 457-494.‏ https://doi.org/10.48300/JLR.2021.279730.1619 (In Persian)
Bojorque, R., & Pesántez-Avilés, F. (2020). Academic quality management system audit using artificial intelligence techniques. In Advances in Artificial Intelligence, Software and Systems Engineering: Proceedings of the AHFE 2019 International Conference on Human Factors in Artificial Intelligence and Social Computing, the AHFE International Conference on Human Factors, Software, Service and Systems Engineering, and the AHFE International Conference of Human Factors in Energy, July 24-28, 2019, Washington DC, USA 10 (pp. 275-283). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-20454-9_28
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa
Brendel, A. B., Mirbabaie, M., Lembcke, T. B., & Hofeditz, L. (2021). Ethical management of artificial intelligence. Sustainability, 13(4), 1974. https://doi.org/10.3390/su13041974 ‏
Calderón, A., & Tannehill, D. (2021). Enacting a new curriculum models-based framework supported by digital technology within a learning community. European Physical Education Review, 27(3), 473-492. https://doi.org/10.1177/1356336X20962126 ‏
Calderón, A., Merono, L., & MacPhail, A. (2020). A student-centred digital technology approach: The relationship between intrinsic motivation, learning climate and academic achievement of physical education pre-service teachers. European Physical Education Review, 26(1), 241-262. https://doi.org/10.1177/1356336X19850852
Casey, A., & Jones, B. (2011). Using digital technology to enhance student engagement in physical education. Asia-Pacific Journal of Health, Sport and Physical Education, 2(2), 51-66. https://doi.org/10.1080/18377122.2011.9730351‏ ‏
Chai, C. S., Wang, X., & Xu, C. (2020). An extended theory of planned behavior for the modelling of Chinese secondary school students’ intention to learn artificial intelligence. Mathematics, 8(11), 2089.‏ https://doi.org/10.3390/math8112089
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. Ieee Access, 8, 75264-75278. https://doi.org/10.1109/ACCESS.2020.2988510
Cukurova, M., Kent, C., & Luckin, R. (2019). Artificial intelligence and multimodal data in the service of human decision‐making: A case study in debate tutoring. British Journal of Educational Technology, 50(6), 3032-3046.‏ https://doi.org/10.1111/bjet.12829
Ding, P. (2019, August). Analysis of artificial intelligence (AI) application in sports. In Journal of Physics: Conference Series (Vol. 1302, No. 3, p. 032044). IOP Publishing.‏ https://doi.org/10.1088/1742-6596/1302/3/032044
Dremliuga, R., & Koshel, A. (2018). Artificial intelligence as a social regulator: Pros and cons. Revis. Dilemas Contemp. Educ. Política Valores, 3, 55-68. https://doi.org/10.24866/1813-3274/2018-3/55-68
Goksel, N., & Bozkurt, A. (2019). Artificial intelligence in education: Current insights and future perspectives. In Handbook of Research on Learning in the Age of Transhumanism (pp. 224-236). IGI Global. https://doi.org/10.4018/978-1-5225-8431-5.ch014
Goodyear, V. A., Blain, D., Quarmby, T., & Wainwright, N. (2016). Dylan: The use of mobile apps within a tactical inquiry approach. In Digital Technologies and Learning in Physical Education (pp. 13-30). London: Routledge. https://doi.org/10.4324/9781315670164-2
Hailong, L. (2021). Role of artificial intelligence algorithm for taekwondo teaching effect evaluation model. Journal of Intelligent & Fuzzy Systems, 40(2), 3239-3250. https://doi.org/10.3233/JIFS-189364
Jackson, P. C. (2019). Introduction to artificial intelligence. New York: Courier Dover Publications.‏
Kang, H. (2023). Artificial intelligence and its influence in adult learning in China. Higher Education, Skills and Work-Based Learning, 13(3), 450-464.‏ https://doi.org/10.1108/HESWBL-01-2023-0017
Kazimzade, G., Patzer, Y., & Pinkwart, N. (2019). Artificial intelligence in education meets inclusive educational technology—The technical state-of-the-art and possible directions. Artificial Intelligence and Inclusive Education: Speculative Futures and Emerging Practices, 61-73.‏ https://doi.org/10.1007/978-981-13-8161-4_4
Keath, A., Wyant, J., & Towner, B. (2024). ChatGPE: Does artificial intelligence have a place in the physical education setting? Journal of Physical Education, Recreation & Dance, 95(2), 59-61.‏ https://doi.org/10.1080/07303084.2023.2292941
Kharbat, F. F., Alshawabkeh, A., & Woolsey, M. L. (2021). Identifying gaps in using artificial intelligence to support students with intellectual disabilities from education and health perspectives. Aslib Journal of Information Management, 73(1), 101-128.‏ https://doi.org/10.1108/AJIM-02-2020-0054
Killian, C. M., Marttinen, R., Howley, D., Sargent, J., & Jones, E. M. (2023). “Knock, Knock… Who’s There?” ChatGPT and artificial intelligence-powered large language models: Reflections on potential impacts within health and physical education teacher education. Journal of Teaching in Physical Education, 42(3), 385-389.‏ https://doi.org/10.1123/jtpe.2023-0058
Lameras, P., & Arnab, S. (2021). Power to the teachers: an exploratory review on artificial intelligence in education. Information, 13(1), 14. https://doi.org/10.3390/info13010014 ‏
Laupichler, M. C., Aster, A., Perschewski, J. O., & Schleiss, J. (2023). Evaluating AI Courses: A valid and reliable instrument for assessing artificial-intelligence learning through comparative self-assessment. Education Sciences, 13(10), 978.‏ https://doi.org/10.3390/educsci13100978
Lee, H. S., & Lee, J. (2021). Applying artificial intelligence in physical education and future perspectives. Sustainability, 13(1), 351.‏ https://doi.org/10.3390/su13010351
Li, J., & Huang, J. S. (2020). Dimensions of artificial intelligence anxiety based on the integrated fear acquisition theory. Technology in Society, 63, 101410. https://doi.org/10.1016/j.techsoc.2020.101410
Long, D., & Magerko, B. (2020, April). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-16). https://doi.org/10.1145/3313831.3376727‏
Ma, Y., Ping, K., Wu, C., Chen, L., Shi, H., & Chong, D. (2020). Artificial Intelligence powered Internet of Things and smart public service. Library Hi Tech, 38(1), 165-179.‏ https://doi.org/10.1108/LHT-12-2017-0274
Majumdar, D., & Chattopadhyay, H. K. (2020). Emergence of AI and its implication towards data privacy: from Indian legal perspective. International Journal of Law Management & Humanities, 4(3), 1-20. https://ijlmh.com/emergence-of-ai-and-its-implication-towards-data-privacy-from-indian-legal-perspective/
McCabe, A., & Trevathan, J. (2008). Artificial intelligence in sports prediction. In Fifth International Conference on Information Technology: New Generations (itng 2008) (pp. 1194-1197). IEEE. https://doi.org/10.1109/ITNG.2008.203
Merriam, S. B., & Tisdell, E. J. (2015). Qualitative research: A guide to design and implementation. San Francisco, CA: John Wiley & Sons.
Moreno-Guerrero, A. J., López-Belmonte, J., Marín-Marín, J. A., & Soler-Costa, R. (2020). Scientific development of educational artificial intelligence in Web of Science. Future Internet, 12(8), 124.‏ https://doi.org/10.3390/fi12080124
Nekoonam, V. (2024). Research requirements of Communication and information data privacy in cyberspace. ModernTechnologies Law, 5(9), 27-40.‏ https://doi.org/10.22133/MTLJ.2023.390545.1188(In Persian)
Novatchkov, H., & Baca, A. (2013). Artificial intelligence in sports on the example of weight training. Journal of Sports Science & Medicine, 12(1), 27.‏ https://www.jssm.org/jssm-12-27.xml%3Eabst
Okunlaya, R. O., Syed Abdullah, N., & Alias, R. A. (2022). Artificial intelligence (AI) library services innovative conceptual framework for the digital transformation of university education. Library Hi Tech, 40(6), 1869-1892.‏ https://doi.org/10.1108/LHT-07-2021-0242
Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020.‏ https://doi.org/10.1016/j.caeai.2021.100020
Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence in Education, 26, 582-599.‏ https://doi.org/10.1007/s40593-016-0110-3
Rowshan, S. A., Yaqoubi, N., & Momeni, A. (2021). Application of artificial intelligence in the public sector (meta-combination study). Iranian Journal of Management Sciences, 16(61), 117-145. https://journal.iams.ir/article_349.html?lang=en‏ (In Persian)
Sadeghi Ordoubadi, B., Mohammadkazemi, R., & Hosseininia, G. (2023). Designing a conceptual model for the development of digital business ecosystem based on scientometric studies. Iranian Journal of Management Sciences, 17(68), 133-155. https://journal.iams.ir/article_392.html ‏ (In Persian)
Salimi, M., Tayebi, M., & Labbaf, A. H. (2023). Estimating Iranian Professional Football Players' prices a neural networks approach. Sports Business Journal, 3(3), 13-28. https://doi.org/10.22051/sbj.2023.42806.1069 (In Persian)
Sargent, J., & Calderón, A. (2021). Technology-enhanced learning physical education? a critical review of the literature. Journal of Teaching in Physical Education, 41(4), 689-709.‏ https://doi.org/10.1123/jtpe.2021-0136
Sargent, J., & Lynch, S. (2021). ‘None of my other teachers know my face/emotions/thoughts’: Digital technology and democratic assessment practices in higher education physical education. Technology, Pedagogy and Education, 30(5), 693-705.‏ https://doi.org/10.1080/1475939X.2021.1942972
Shahmansori, K., & Chenari, V. (2018). Pathology of health system transformation plan using theme analysis. Medical Journal of Mashhad University of Medical Sciences, 61(5), 4197-4212.‏ https://doi.org/10.22038/mjms.2021.20137 (In Persian)
Sullins, J., Craig, S. D., & Hu, X. (2015). Exploring the effectiveness of a novel feedback mechanism within an intelligent tutoring system. International Journal of Learning Technology, 10(3), 220-236.‏ https://doi.org/10.1504/IJLT.2015.072358
Wei, S., Huang, P., Li, R., Liu, Z., & Zou, Y. (2021). Exploring the application of artificial intelligence in sports training: A case study approach. Complexity, 2021, 1-8. https://doi.org/10.1155/2021/4658937
Wheatley, A., & Hervieux, S. (2019). Artificial intelligence in academic libraries: An environmental scan. Information Services & Use, 39(4), 347-356. https://doi.org/10.3233/ISU-190065
Wu, C., & Ma, Y. (2023). Current Status, hotspots and future prospects of intelligent education research in China: CiteSpace based visual analysis. Journal of Education, Humanities and Social Sciences, 14, 567-576.‏ https://doi.org/10.54097/ehss.v14i.8943
Yang, S. J., Ogata, H., Matsui, T., & Chen, N. S. (2021). Human-centered artificial intelligence in education: Seeing the invisible through the visible. Computers and Education: Artificial Intelligence, 2, 100008.‏ https://doi.org/10.1016/j.caeai.2021.100008
Zhang, H., & Zhu, J. (2022). Practicability of sports goods in the sports field based on artificial intelligence technology. Mobile Information Systems, 2022. https://doi.org/10.1155/2022/4964894 ‏ ‏
Zhang, T., & Li, H. (2018). Digital video and self-modeling in the PE classroom. In Digital technology in physical education (pp. 19-31). London: Routledge.‏ http://dx.doi.org/10.4324/9780203704011-2