Araştırma Makalesi
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YAPAY ZEKA TEKNOLOJİSİNDEKİ GELİŞMELER KARİYER KARARLILIĞINI ETKİLER Mİ? SPOR BİLİMLERİ FAKÜLTESİ ÖĞRENCİLERİNE YÖNELİK BİR ARAŞTIRMA

Yıl 2025, Cilt: 6 Sayı: 3, 24 - 36, 22.12.2025

Muhammet Mavibaş , Ali Er Muhammed Fatih Yuşa Başkaya

Öz

Bu araştırma, Spor Bilimleri Fakültesi öğrencilerinin yapay zekâ kaygı düzeylerinin kariyer kararlılıkları üzerindeki etkisini incelemeyi ve bu değişkenleri demografik faktörlere göre karşılaştırmayı amaçlamaktadır.
Araştırma ilişkisel tarama modeliyle yürütülmüştür. Evreni Atatürk, Bayburt ve Erzurum Teknik Üniversiteleri Spor Bilimleri Fakülteleri; örneklemi ise 461 öğrenciden oluşmaktadır. Veri toplamak için Kişisel Bilgi Formu, Yapay Zekâ Kaygısı Ölçeği ve Kariyer Kararlılığı Ölçeği kullanılmıştır.
Veriler betimsel istatistikler, basıklık-çarpıklık ve güvenilirlik analizleriyle incelenmiş; iki grup karşılaştırmaları için bağımsız örneklemler t-testi, üç ve daha fazla grup için tek yönlü ANOVA ve farklılık kaynağı için Tukey post-hoc testi uygulanmıştır. Ayrıca, yapay zekâ kaygısının kariyer kararlılığı üzerindeki etkisini belirlemek için basit ve çoklu regresyon analizleri yapılmıştır.
Bulgular, öğrencilerin üniversitelerine göre yapay zekâ kaygısı ve kariyer kararlılığı düzeylerinde anlamlı farklılıklar olduğunu göstermiştir (p<0,05). Yapay zekâ kaygısının kariyer kararlılığı üzerinde anlamlı ve negatif bir etkisi bulunmuş, basit regresyon analizinde bu değişkenin kariyer kararlılığındaki varyansın %6,8’ini açıkladığı tespit edilmiştir.
Atatürk Üniversitesi öğrencilerinin yapay zekâ kaygı düzeyleri (X=3,96±1,23), Bayburt (X=3,47±1,10) ve Erzurum Teknik (X=3,14±1,41) öğrencilerine göre daha yüksektir. Buna karşılık, kariyer kararlılığı Erzurum Teknik Üniversitesi öğrencilerinde (X=3,47±0,83) en yüksek düzeydedir. Yapay zekâ kaygısındaki artışın kariyer kararlılığını olumsuz etkilediği (β=-0,260, t=-5,766, p<,001) belirlenmiştir.

Anahtar Kelimeler

Spor Bilimleri Fakültesi Öğrenci Yapay Zeka Teknolojisi Kariyer Kararlılığı

Etik Beyan

Bu çalışma kapsamında yürütülen “Yapay Zeka Teknolojisindeki Gelişmeler Kariyer Kararlılığını Etkiler Mi? Spor Bilimleri Fakültesi Öğrencilerine Yönelik Bir Araştırma” başlıklı araştırma için, Erzurum Teknik Üniversitesi Bilimsel Araştırma ve Yayın Etik Kurulu’ndan 04.04.2024 tarihli, 04 sayılı toplantı ve 21 sayılı karar ile etik kurul onayı alınmıştır.

Destekleyen Kurum

TÜBİTAK | Türkiye Bilimsel ve Teknolojik Araştırma Kurumu

Proje Numarası

1919B012333138

Teşekkür

Bu çalışma, Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK) tarafından yürütülen “Üniversite Öğrencileri Araştırma Projeleri Destekleme Programı” kapsamında, 2209-A kodlu proje desteği ile gerçekleştirilmiştir (Proje No: 1919B012333138). Çalışmanın yürütülmesine katkı sağlayan TÜBİTAK'a teşekkür ederiz.

Kaynakça

  • Abbas, M. A., Lim, H., & Bang, J. H. (2022). Memory effect in lithium titanate driven by interfacial oxygen vacancies. ACS Energy Letters, 7(3), 1086–1091. https://doi.org/10.1021/acsenergylett.2c00157
  • Agrawal, A., Gans, J., & Goldfarb, A. (Eds.). (2019). The economics of artificial intelligence: An agenda. University of Chicago Press.
  • Akçakanat, T., & Uzunbacak, H. H. (2019). Kariyer kararlılığı ölçeği: Türkçe’ye uyarlama, geçerlik ve güvenirlik çalışması. İktisadi İdari ve Siyasal Araştırmalar Dergisi, 4(9), 159–170. https://doi.org/10.25204/iktisad.576572
  • Arnett, J. J. (2000). Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist, 55(5), 469–480. https://doi.org/10.1037/0003-066X.55.5.469
  • Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986(23-28), 2.
  • Berkeley, E. C. (1949). Giant brains; or, machines that think. Science Press.
  • Bright, J. E. H., Pryor, R. G. L., & Harpham, L. (2005). The role of chance events in career decision making. Journal of Vocational Behavior, 66(3), 561–576. https://doi.org/10.1016/j.jvb.2004.05.001
  • Ceylan, L., Boyraz, D. E. A., Çaldıran, S., Ceylan, T., & Küçük, H. (2022). Examination of nutrition knowledge levels of individuals who received sports training. International Journal of Life Science and Pharma Research, 12(5), 11–17. https://doi.org/10.22376/ijpbs/lpr.2022.12.5.L11-17
  • Copeland, B. J. (2000). The turing test. Minds and Machines, 10(4), 519-539. https://doi.org/10.1023/A:1011285919106
  • Çavuş, H., & Günbatar, M. S. (2008). Bilgisayar kaygı ölçeğinin Türkçeye uyarlama çalışması. Gazi Üniversitesi Gazi Eğitim Fakültesi Dergisi, 28, 147–163.
  • Doğan, P. K., Doğan, İ., & Çetinkayalı, G. (2023). Spor Bilimleri öğrencilerinin yapay zekaya yönelik tutumları ile iş bulma kaygıları arasındaki ilişkinin incelenmesi. Yalova Üniversitesi Spor Bilimleri Dergisi, 2(3), 174–189.
  • El Naqa, I., & Murphy, M. J. (2015). What is machine learning? In Machine learning in radiation oncology, 3–11. Springer. https://doi.org/10.1007/978-3-319-18305-3_1
  • Epstein, S. (1972). The nature of anxiety with emphasis upon its relationship to expectancy. Anxiety: Current trends in theory and research, 2, 291-337.
  • Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation?. Technological forecasting and social change, 114, 254-280. https://doi.org/10.1016/j.techfore.2016.08.019
  • Fuchs, M., & Reichert, R. (2018). Introduction: Rethinking AI. Neural networks, biometrics and the new artificial intelligence. Digital Culture & Society, 4(1), 5–14. https://doi.org/10.14361/dcs-2018-0102
  • Gati, I., Krausz, M., & Osipow, S. H. (1996). A taxonomy of difficulties in career decision making. Journal of Counseling Psychology, 43(4), 510–526. https://doi.org/10.1037/0022-0167.43.4.510
  • Goodfellow, I., Bengio, Y., Courville, A., & Bengio, Y. (2016). Deep learning (Vol. 1, No. 2). Cambridge: MIT press.
  • Gültekin, Z., Urgan, S., & Ak, M. (2022). Yapay zekâ kaygısının kariyer kararlılığına etkisine yönelik bir araştırma: Ondokuz Mayıs Üniversitesi öğrencileri örneği. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 27(3), 477–491.
  • Hamzaçebi, C., & Kutay, F. (2004). Yapay sinir ağları ile Türkiye elektrik enerjisi tüketiminin 2010 yılına kadar tahmini. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 19(3), 375–384.
  • Hong, G. (2019). The translation of historical documents and the study of Korean history using artificial intelligence. International Journal of Korean History, 24(2), 71–97. https://doi.org/10.22372/ijkh.2019.24.2.71
  • Johnson, D. G., & Verdicchio, M. (2017). AI anxiety. Journal of the Association for Information Science and Technology, 68(9), 2267–2270. https://doi.org/10.1002/asi.23867
  • Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004
  • Kirmani, A. R. (2022). Artificial intelligence–enabled science poetry. ACS Energy Letters, 7(2), 574–576. https://doi.org/10.1021/acsenergylett.2c02758
  • Liu, Q., Wang, Y., & Zhang, Y. (2021). Development and validation of an artificial intelligence anxiety scale: An initial application in predicting motivated learning behavior. Computers in Human Behavior, 124, 106932. https://doi.org/10.1080/10494820.2019.1674887
  • Liu, X., Zheng, Y., Du, Z., Ding, M., Qian, Y., Yang, Z., & Tang, J. (2021). GPT understands, too. arXiv preprint, arXiv:2103.10385. https://doi.org/10.48550/arXiv.2103.10385
  • Lounsbury, J. W., Tatum, H. E., Chambers, W., Owens, K., & Gibson, L. W. (1999). An investigation of career decidedness in relation to “Big Five” personality constructs and life satisfaction. College Student Journal, 33(4), 646–652. https://doi.org/10.1177/1069072704270272
  • Lund, B. D., & Wang, T. (2023). Chatting about ChatGPT: How may AI and GPT impact academia and libraries? Library Hi Tech News, 40(3), 26–29. https://doi.org/10.1108/LHTN-01-2023-0009
  • Mayor, A. (2018). Gods and robots: Myths, machines, and ancient dreams of technology. Princeton University Press.
  • Miller, A. D. (2011). Career decidedness, meaning in life, and anxiety: A mediation/moderation model [Unpublished master's thesis]. Southern Illinois University.
  • OECD. (2021). The future of work: AI and employment policy. OECD Publishing.
  • OECD. (2021, December). Artificial intelligence and employment. https://www.oecd.org/future-of-work/reports-and-data/AI-Employment-brief-2021.pdf
  • Oyedotun, O.K., & Khashman, A. (2017). Deep learning in vision-based static hand gesture recognition. Neural Comput & Applic, 28, 3941–3951. https://doi.org/10.1007/s00521-016-2294-8
  • Radford, A., Narasimhan, K., Salimans, T., & Sutskever, I. (2018). Improving language understanding by generative pre-training.
  • Rouhiainen, L. (2020). Yapay zeka: Geleceğimizle ilgili bugün bilmemiz gereken 101 şey (N. Bıyık, Trans.). Pegasus Yayınları.
  • Russo, S., Motyl, M., & Savani, K. (2023). Gender differences in AI-related anxiety: The mediating role of perceived control. Technology, Mind, and Behavior, 4(1). https://doi.org/10.1037/tmb0000068
  • Scharre, P. (2018). Army of none: Autonomous weapons and the future of war. WW Norton & Company.
  • Shadhar, A. M. (2022). The finger vein recognition using deep learning technique. Wasit Journal of Computer and Mathematics Science, 1(2), 1-7. https://doi.org/10.31185/wjcms.43
  • Singh, G., Mishra, A., & Sagar, D. (2013). An overview of artificial intelligence. SBIT journal of sciences and technology, 2(1), 1-4.
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Boston, MA: Pearson.
  • Tegmark, M. (2021). Yaşam 3.0: Yapay zeka çağında insan olmak (E. M. Tutar, Trans.). Pegasus Yayınları.
  • Terzi, R. (2020). An adaptation of Artificial Intelligence Anxiety Scale into Turkish: Reliability and validity study. International Online Journal of Education and Teaching, 7(4), 1501–1515.
  • Uçar, M., Çapuk, H., & Yiğit, M. F. (2025). The relationship between artificial intelligence anxiety and unemployment anxiety among university students. Work, 80(2), 701–710.
  • Wang, Y. M., Li, X., & Chen, Z. (2022). What drives students’ AI learning behavior: The role of artificial intelligence anxiety. Interactive Learning Environments, 30(5), 832–847.
  • Wang, Y. M., Wei, C. L., Lin, H. H., Wang, S. C., & Wang, Y. S. (2024). What drives students’ AI learning behavior: A perspective of AI anxiety. Interactive Learning Environments, 32(6), 2584-2600. https://doi.org/10.1080/10494820.2022.2153147
  • Wang, Y. Y., & Wang, Y. S. (2019). Development and validation of an artificial intelligence anxiety scale: An initial application in predicting motivated learning behavior. Interactive Learning Environments, 1-16.
  • Yaşar, S., & Karagucuk, H. (2025). The effect of artificial intelligence anxiety on career decidedness among students in English-related departments. Journal of Educational Technology Research, 12(2), 101–118.
  • Yazıcı, A. M. (2023). The moderator role of career decidedness in the effect of artificial intelligence anxiety on employment hope. Business & Management Studies: An International Journal, 11(4), 1260–1274

DO DEVELOPMENTS IN ARTIFICIAL INTELLIGENCE TECHNOLOGY AFFECT CAREER DECISION-MAKING? A STUDY ON STUDENTS OF FACULTIES OF SPORTS SCIENCES

Yıl 2025, Cilt: 6 Sayı: 3, 24 - 36, 22.12.2025

Muhammet Mavibaş , Ali Er Muhammed Fatih Yuşa Başkaya

Öz

This study aims to examine the effect of Sports Sciences Faculty students’ artificial intelligence (AI) anxiety levels on their career decision-making and to compare these variables according to demographic factors.
The research was conducted using a relational survey model. The population consisted of students from the Sports Sciences Faculties of Atatürk, Bayburt, and Erzurum Technical Universities, and the sample comprised 461 students. Data were collected using a Personal Information Form, the Artificial Intelligence Anxiety Scale, and the Career Decision-Making Scale.
The data were analyzed using descriptive statistics, skewness-kurtosis tests, and reliability analyses. Independent samples t-tests were employed for two-group comparisons, one-way ANOVA for three or more groups, and Tukey post-hoc tests to determine the source of differences. In addition, simple and multiple regression analyses were performed to examine the effect of AI anxiety on career decision-making.
The findings revealed significant differences in AI anxiety and career decision-making levels according to the university attended (p<,05). AI anxiety had a significant and negative effect on career decision-making, and simple regression analysis showed that AI anxiety accounted for approximately 6.8% of the variance in career decision-making.
AI anxiety levels of Atatürk University students (X=3,96±1,23) were higher than those of Bayburt (X=3,47±1,10) and Erzurum Technical University students (X=3,14±1,41). Conversely, career decision-making levels were highest among Erzurum Technical University students (X=3,47±0,83). It was concluded that increasing AI anxiety negatively affects career decision-making (β=-0,260, t=-5,766, p<,001).

Anahtar Kelimeler

Faculty of Sports Sciences Student Artificial Intelligence Technology Career Decision-Making

Etik Beyan

For the research titled "Do Developments in Artificial Intelligence Technology Affect Career Determination? A Research on Students of the Faculty of Sports Sciences" conducted within the scope of this study, ethics committee approval was received from the Scientific Research and Publication Ethics Committee of Erzurum Technical University with the meeting number 04 and decision number 21 dated 04.04.2024.

Destekleyen Kurum

TÜBİTAK | The Scientific and Technological Research Council of Türkiye

Proje Numarası

1919B012333138

Teşekkür

This study was carried out within the scope of the "University Students Research Projects Support Program" conducted by the Scientific and Technological Research Council of Turkey (TÜBİTAK) with project support under project code 2209-A (Project No: 1919B012333138). We would like to thank TÜBİTAK for their contribution to the conduct of the study.

Kaynakça

  • Abbas, M. A., Lim, H., & Bang, J. H. (2022). Memory effect in lithium titanate driven by interfacial oxygen vacancies. ACS Energy Letters, 7(3), 1086–1091. https://doi.org/10.1021/acsenergylett.2c00157
  • Agrawal, A., Gans, J., & Goldfarb, A. (Eds.). (2019). The economics of artificial intelligence: An agenda. University of Chicago Press.
  • Akçakanat, T., & Uzunbacak, H. H. (2019). Kariyer kararlılığı ölçeği: Türkçe’ye uyarlama, geçerlik ve güvenirlik çalışması. İktisadi İdari ve Siyasal Araştırmalar Dergisi, 4(9), 159–170. https://doi.org/10.25204/iktisad.576572
  • Arnett, J. J. (2000). Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist, 55(5), 469–480. https://doi.org/10.1037/0003-066X.55.5.469
  • Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986(23-28), 2.
  • Berkeley, E. C. (1949). Giant brains; or, machines that think. Science Press.
  • Bright, J. E. H., Pryor, R. G. L., & Harpham, L. (2005). The role of chance events in career decision making. Journal of Vocational Behavior, 66(3), 561–576. https://doi.org/10.1016/j.jvb.2004.05.001
  • Ceylan, L., Boyraz, D. E. A., Çaldıran, S., Ceylan, T., & Küçük, H. (2022). Examination of nutrition knowledge levels of individuals who received sports training. International Journal of Life Science and Pharma Research, 12(5), 11–17. https://doi.org/10.22376/ijpbs/lpr.2022.12.5.L11-17
  • Copeland, B. J. (2000). The turing test. Minds and Machines, 10(4), 519-539. https://doi.org/10.1023/A:1011285919106
  • Çavuş, H., & Günbatar, M. S. (2008). Bilgisayar kaygı ölçeğinin Türkçeye uyarlama çalışması. Gazi Üniversitesi Gazi Eğitim Fakültesi Dergisi, 28, 147–163.
  • Doğan, P. K., Doğan, İ., & Çetinkayalı, G. (2023). Spor Bilimleri öğrencilerinin yapay zekaya yönelik tutumları ile iş bulma kaygıları arasındaki ilişkinin incelenmesi. Yalova Üniversitesi Spor Bilimleri Dergisi, 2(3), 174–189.
  • El Naqa, I., & Murphy, M. J. (2015). What is machine learning? In Machine learning in radiation oncology, 3–11. Springer. https://doi.org/10.1007/978-3-319-18305-3_1
  • Epstein, S. (1972). The nature of anxiety with emphasis upon its relationship to expectancy. Anxiety: Current trends in theory and research, 2, 291-337.
  • Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation?. Technological forecasting and social change, 114, 254-280. https://doi.org/10.1016/j.techfore.2016.08.019
  • Fuchs, M., & Reichert, R. (2018). Introduction: Rethinking AI. Neural networks, biometrics and the new artificial intelligence. Digital Culture & Society, 4(1), 5–14. https://doi.org/10.14361/dcs-2018-0102
  • Gati, I., Krausz, M., & Osipow, S. H. (1996). A taxonomy of difficulties in career decision making. Journal of Counseling Psychology, 43(4), 510–526. https://doi.org/10.1037/0022-0167.43.4.510
  • Goodfellow, I., Bengio, Y., Courville, A., & Bengio, Y. (2016). Deep learning (Vol. 1, No. 2). Cambridge: MIT press.
  • Gültekin, Z., Urgan, S., & Ak, M. (2022). Yapay zekâ kaygısının kariyer kararlılığına etkisine yönelik bir araştırma: Ondokuz Mayıs Üniversitesi öğrencileri örneği. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 27(3), 477–491.
  • Hamzaçebi, C., & Kutay, F. (2004). Yapay sinir ağları ile Türkiye elektrik enerjisi tüketiminin 2010 yılına kadar tahmini. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 19(3), 375–384.
  • Hong, G. (2019). The translation of historical documents and the study of Korean history using artificial intelligence. International Journal of Korean History, 24(2), 71–97. https://doi.org/10.22372/ijkh.2019.24.2.71
  • Johnson, D. G., & Verdicchio, M. (2017). AI anxiety. Journal of the Association for Information Science and Technology, 68(9), 2267–2270. https://doi.org/10.1002/asi.23867
  • Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004
  • Kirmani, A. R. (2022). Artificial intelligence–enabled science poetry. ACS Energy Letters, 7(2), 574–576. https://doi.org/10.1021/acsenergylett.2c02758
  • Liu, Q., Wang, Y., & Zhang, Y. (2021). Development and validation of an artificial intelligence anxiety scale: An initial application in predicting motivated learning behavior. Computers in Human Behavior, 124, 106932. https://doi.org/10.1080/10494820.2019.1674887
  • Liu, X., Zheng, Y., Du, Z., Ding, M., Qian, Y., Yang, Z., & Tang, J. (2021). GPT understands, too. arXiv preprint, arXiv:2103.10385. https://doi.org/10.48550/arXiv.2103.10385
  • Lounsbury, J. W., Tatum, H. E., Chambers, W., Owens, K., & Gibson, L. W. (1999). An investigation of career decidedness in relation to “Big Five” personality constructs and life satisfaction. College Student Journal, 33(4), 646–652. https://doi.org/10.1177/1069072704270272
  • Lund, B. D., & Wang, T. (2023). Chatting about ChatGPT: How may AI and GPT impact academia and libraries? Library Hi Tech News, 40(3), 26–29. https://doi.org/10.1108/LHTN-01-2023-0009
  • Mayor, A. (2018). Gods and robots: Myths, machines, and ancient dreams of technology. Princeton University Press.
  • Miller, A. D. (2011). Career decidedness, meaning in life, and anxiety: A mediation/moderation model [Unpublished master's thesis]. Southern Illinois University.
  • OECD. (2021). The future of work: AI and employment policy. OECD Publishing.
  • OECD. (2021, December). Artificial intelligence and employment. https://www.oecd.org/future-of-work/reports-and-data/AI-Employment-brief-2021.pdf
  • Oyedotun, O.K., & Khashman, A. (2017). Deep learning in vision-based static hand gesture recognition. Neural Comput & Applic, 28, 3941–3951. https://doi.org/10.1007/s00521-016-2294-8
  • Radford, A., Narasimhan, K., Salimans, T., & Sutskever, I. (2018). Improving language understanding by generative pre-training.
  • Rouhiainen, L. (2020). Yapay zeka: Geleceğimizle ilgili bugün bilmemiz gereken 101 şey (N. Bıyık, Trans.). Pegasus Yayınları.
  • Russo, S., Motyl, M., & Savani, K. (2023). Gender differences in AI-related anxiety: The mediating role of perceived control. Technology, Mind, and Behavior, 4(1). https://doi.org/10.1037/tmb0000068
  • Scharre, P. (2018). Army of none: Autonomous weapons and the future of war. WW Norton & Company.
  • Shadhar, A. M. (2022). The finger vein recognition using deep learning technique. Wasit Journal of Computer and Mathematics Science, 1(2), 1-7. https://doi.org/10.31185/wjcms.43
  • Singh, G., Mishra, A., & Sagar, D. (2013). An overview of artificial intelligence. SBIT journal of sciences and technology, 2(1), 1-4.
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Boston, MA: Pearson.
  • Tegmark, M. (2021). Yaşam 3.0: Yapay zeka çağında insan olmak (E. M. Tutar, Trans.). Pegasus Yayınları.
  • Terzi, R. (2020). An adaptation of Artificial Intelligence Anxiety Scale into Turkish: Reliability and validity study. International Online Journal of Education and Teaching, 7(4), 1501–1515.
  • Uçar, M., Çapuk, H., & Yiğit, M. F. (2025). The relationship between artificial intelligence anxiety and unemployment anxiety among university students. Work, 80(2), 701–710.
  • Wang, Y. M., Li, X., & Chen, Z. (2022). What drives students’ AI learning behavior: The role of artificial intelligence anxiety. Interactive Learning Environments, 30(5), 832–847.
  • Wang, Y. M., Wei, C. L., Lin, H. H., Wang, S. C., & Wang, Y. S. (2024). What drives students’ AI learning behavior: A perspective of AI anxiety. Interactive Learning Environments, 32(6), 2584-2600. https://doi.org/10.1080/10494820.2022.2153147
  • Wang, Y. Y., & Wang, Y. S. (2019). Development and validation of an artificial intelligence anxiety scale: An initial application in predicting motivated learning behavior. Interactive Learning Environments, 1-16.
  • Yaşar, S., & Karagucuk, H. (2025). The effect of artificial intelligence anxiety on career decidedness among students in English-related departments. Journal of Educational Technology Research, 12(2), 101–118.
  • Yazıcı, A. M. (2023). The moderator role of career decidedness in the effect of artificial intelligence anxiety on employment hope. Business & Management Studies: An International Journal, 11(4), 1260–1274
Toplam 47 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Spor ve Rekreasyon, Egzersiz ve Spor Psikolojisi
Bölüm Araştırma Makalesi
Yazarlar

Muhammet Mavibaş 0000-0002-2771-2521

Ali Er 0009-0009-2273-8405

Muhammed Fatih Yuşa Başkaya 0009-0007-2922-1412

Proje Numarası 1919B012333138
Gönderilme Tarihi 7 Temmuz 2025
Kabul Tarihi 29 Eylül 2025
Yayımlanma Tarihi 22 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 6 Sayı: 3

Kaynak Göster

APA Mavibaş, M., Er, A., & Başkaya, M. F. Y. (2025). YAPAY ZEKA TEKNOLOJİSİNDEKİ GELİŞMELER KARİYER KARARLILIĞINI ETKİLER Mİ? SPOR BİLİMLERİ FAKÜLTESİ ÖĞRENCİLERİNE YÖNELİK BİR ARAŞTIRMA. Sivas Cumhuriyet Üniversitesi Spor Bilimleri Dergisi, 6(3), 24-36.