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Journals / Kastamonu Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi / 2025 / Cilt: 27 Sayı: 2

Investigating The Factors Affecting Students' Behaviour Of Using Youtube For Academic Purposes

Öğrencilerin Youtube'u Akademik Amaçlı Kullanma Davranışlarını Etkileyen Faktörlerin İncelenmesi

Veysel Yılmaz(ESKİŞEHİR OSMANGAZİ ÜNİVERSİTESİ)0000-0001-5147-5047
Fatema Alzahraa Ied(ESKİŞEHİR OSMANGAZİ ÜNİVERSİTESİ, FEN BİLİMLERİ ENSTİTÜSÜ)0000-0001-6564-7129
Hüseyin Gürbüz(Anadolu Üniversitesi İİBF İşletme Bölümü Sayısal Yöntemler Anabilim Dalı)0000-0002-1085-9164
Pages
461–480
Publication Date
2025-12-29
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

According to the results of the study, all hypotheses were supported.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:YouTube is one of the popular social media networks used intensively by young people, especially university students, for both entertainment and academic learning.
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Key Findings & Data:The effects of these factors on perceived benefits, perceived ease of use and students' behavioural intentions towards their academic performance were examined with the help of structural equation modelling (SEM).
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Conclusion & Impact:According to the results of the study, all hypotheses were supported.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:Akademik Performans · Teknoloji Kabul Modeli · Üniversite Öğrencileri

Abstract

YouTube is one of the popular social media networks used intensively by young people, especially university students, for both entertainment and academic learning. This study was conducted to investigate the factors affecting the quality of scientific services offered by YouTube and their impact on behavioural intention in the academic use of YouTube. In the study, a research model was proposed based on the Technology Acceptance Model (TAM). In addition to the factors in the TAM, the proposed research model includes YouTube video quality, content richness and source reliability. The effects of these factors on perceived benefits, perceived ease of use and students' behavioural intentions towards their academic performance were examined with the help of structural equation modelling (SEM). For this purpose, a questionnaire was designed by using the literature to measure the factors of the model, and the questionnaire was conducted online by sharing it on social media. The survey was carried out with the voluntary participation of 360 Arab university students studying in Turkish universities. The fit of the proposed model and the test of structural relationships were analysed by partial least squares structural equation modelling (PLS-SEM). According to the results of the study, all hypotheses were supported. A one-unit increase in the perceived utility of using YouTube for academic purposes leads to a 0.648-unit increase in user satisfaction, and a one-unit increase in user satisfaction leads to a 0.635-unit increase in behavioural intention. It was evaluated that the higher the user satisfaction, the higher the average academic performance of the student or researcher.

Özet

YouTube gençler ve özellikle üniversite öğrencileri tarafından yoğun bir şekilde hem eğlence hem de akademik olarak öğrenme amaçlı kullanılan popüler sosyal medya ağlarından birisidir. Bu çalışma, YouTube'un sunduğu bilimsel hizmetlerin kalitesini etkileyen faktörleri ve bunların YouTube 'un akademik kullanımında davranışsal niyet üzerindeki etkisini araştırmak amacıyla gerçekleştirmiştir. Çalışmada, Teknoloji Kabul Modeli (TKM) temel alınarak bir araştırma model önerilmiştir. TKM’deki faktörlere ilave olarak önerilen araştırma modelinde; YouTube video kalitesi, içerik zenginliği ve kaynak güvenilirliği yer almaktadır. Temel olarak eklenen bu faktörlerin algılanan faydalar, algılanan kullanım kolaylığı ve öğrencilerin akademik performanslarına yönelik davranışsal niyetleri üzerindeki etkileri yapısal eşitlik modellemesi (YEM) yardımıyla incelenmiştir. Bu amaçla, modelin faktörlerini ölçmek için Literatürden yararlanarak bir anket tasarlanmış, anket sosyal medyada paylaşılarak online olarak yapılmıştır. Ankete Türk üniversitelerinde öğrenim gören 360 Arap üniversite öğrencisinin gönüllü katılımıyla gerçekleştirilmiştir. Önerilen modelinin uyumu ve yapısal ilişkilerin testi, kısmi en küçük kareler yapısal eşitlik modellemesi (PLS-SEM) ile analiz edilmiştir. Araştırma sonuçlarına göre tüm hipotezler desteklenmiştir. YouTube'u akademik amaçlı kullanmanın algılanan faydadaki bir birimlik artışın, kullanıcı memnuniyetinde 0,648 birimlik artışa, kullanıcı memnuniyetindeki bir birimlik artış davranışsal niyetinde 0,635 birim artışa neden olmaktadır. Kullanıcı memnuniyeti ne kadar yüksek olursa, öğrencinin veya araştırmacının ortalama akademik performansı da o kadar yüksek olacağı değerlendirilmiştir.

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Cite This Article

Yılmaz, V., Ied, F. A., Gürbüz, H. (2025). Investigating The Factors Affecting Students' Behaviour Of Using Youtube For Academic Purposes. Kastamonu Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Cilt: 27 Sayı: 2, 461–480. https://doi.org/10.21180/iibfdkastamonu.1589563

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References (41)

  1. Abu-Taieh, E., AlHadid, I., Masa’deh, R. E., Alkhawaldeh, R. S., Khwaldeh, S. & Alrowwad, A. A. (2022). Factors Influencing Youtube as A Learning Tool and its Influence on Academic Achievement in a Bilingual Environment Using Extended Information Adoption Model (iam) with Ml Prediction—Jordan Case Study. Applied Sciences, 12(12), 5856.‏ https://doi.org/10.3390/app12125856
  2. Aruğaslan, E. & Çivril, H. (2023). Öğrenme Ortamı Olarak Youtube’un Kullanılmasına İlişkin Öğrenci Görüşleri. Açıköğretim Uygulamaları ve Araştırmaları Dergisi (AUAd), 9(1), 356-375. https://doi.org/10.51948/auad.1193826
  3. Bardakcı, S. (2019). Exploring High School Students’ Educational Use of YouTube. International Review of Research in Open and Distributed Learning, 20(2), 261-27. https://doi.org/10.19173/irrodl.v20i2.4074
  4. Brecht, H. D. (2012). Learning from Online Video Lectures. Journal of Information Technology Education. Innovations in Practice, 11, 227-250. https://doi.org/10.28945/1712
  5. Burton-Jones, A. & Hubona, G. S. (2005). Individual Differences and Usage Behavior: Revisiting a Technology Acceptance Model Assumption. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 36(2), 58-77.‏ https://doi.org/10.1145/1066149.1066155
  6. Cheung, R. & Vogel, D. (2013). Predicting User Acceptance of Collaborative Technologies: An Extension of the Technology Acceptance Model for E-Learning. Computers & Education, 63, 160-175.‏ https://doi.org/10.1016/j.compedu.2012.12.003
  7. Chin, W. W. (1998). The Partial Least Squares Approach to Structural Equation Modeling. Modern Methods for Business Research, 295(2), 295-336.
  8. Chintalapati, N. & Daruri, V. S. K. (2017). Examining the use of YouTube as a Learning Resource in Higher Education: Scale Development and Validation of TAM Model. Telematics and Informatics, 34(6), 853-860. https://doi.org/10.1016/j.tele.2016.08.008
  9. Chuchu, T. & Ndoro, T. (2019). An Examination of the Determinants of the Adoption of Mobile Applications as Learning Tools for Higher Education Students. International Journal of Interactive Mobile Technologie,‏ 13(3), 53–67. https://doi.org/10.3991/ijim.v13i03.10195
  10. Cohen, J. E. (1988). Statistical Power Analysis for the Behavioral Sciences. NJ: Lawrence Erlbaum Associates, Inc. https://doi.org/10.4324/9780203771587
  11. De Wulf, K., Schillewaert, N., Muylle, S. & Rangarajan, D. (2006). The Role of Pleasure in Web Site Success. Information & Management, 43(4), 434-446.‏ https://doi.org/10.1016/j.im.2005.10.005
  12. Elareshi, M., Habes, M., Youssef, E., Salloum, S. A., Alfaisal, R. & Ziani, A. (2022). SEM-ANN Based Approach to Understanding Students’ Academic-Performance Adoption of YouTube for Learning During Covid. Heliyon, 8(4), e09236.‏ https://doi.org/10.1016/j.heliyon.2022.e09236
  13. Fornell, C. & Larcker, D. F.(1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
  14. Habes, M., Salloum, S. A., Alghizzawi, M. & Mhamdi, C. (2019). The Relation Between Social Media and Students’ Academic Performance in Jordan: YouTube Perspective. In: A. E. Hassanien, K. Shaalan & M.F. Talba (Eds,), International Conference on Advanced Intelligent Systems and Informatics (pp. 382-392). Cham: Springer International Publishing.‏ https://doi.org/10.1007/978-3-030-31129-2_35
  15. Hair, J. F., Ringle, C. M. & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. The Journal of Marketing Theory and Practice, 19(2),139-152. https://doi.org/10.2753/MTP1069-6679190202
  16. Hair, J.F., Hult, G.T.M., Ringle, C.M. & Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage, Thousand Oaks. https://doi.org/10.1007/978-3-319-57413-4_15
  17. Hair, J. F., Hult, G. T., Ringle, C. M. & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd Edition). Los Angeles: SAGE.
  18. Hair, J. F., Risher, J. J., Sartstedt, M. & Ringle, C. M. (2019). When to Use and How to Report the Results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
  19. Jung, Y., Perez-Mira, B. & Wiley-Patton, S. (2009). Consumer Adoption of Mobile TV: Examining Psychological Flow and Media Content. Computers in Human Behavior, 25(1), 123-129.‏ https://doi.org/10.1016/j.chb.2008.07.011
  20. Jung, I. & Lee, Y. (2015). YouTube Acceptance by University Educators and Students: A Cross Cultural Perspective. Innovations in Education and Teaching International, 52(3), 243-253.‏ https://doi.org/10.1080/14703297.2013.805986
  21. Jung, J., Han, H. & Oh, M. (2017). Travelers’ Switching Behavior in the Airline Industry from the Perspective of the Push-Pull-Mooring Framework. Tourism Management, 59, 139-153. https://doi.org/10.1016/j.tourman.2016.07.018
  22. Jöreskog, K. G. & Wold, H. (1982). The ML and PLS Techniques for Modeling with Latent Variables: Historical and Comparative Aspects. In: H. Wold & K. G. Jöreskog (Eds.), Systems Under Indirect Observation: Causality, Structure, Prediction, part I (s. 263-270). Amsterdam: North-Holland.
  23. Kılıç, A. & Yılmaz, R. (2021). YouTube’un Eğitsel Amaçlı Kabul Durumunun İncelenmesi. Ahmet Keleşoğlu Eğitim Fakültesi Dergisi, 3(1), 69-89.
  24. Kock, N. (2015). Common Method Bias in PLS-SEM: A Full Collinearity Assessment Approach. International Journal of e-Collaboration, 11(4), 1-10. https://doi.org/10.4018/ijec.2015100101
  25. Lee, D. Y. & Lehto, M. R. (2013). User Acceptance of YouTube for Procedural Learning: An Extension of the Technology Acceptance Model. Computers & Education, 61, 193-208.‏ https://doi.org/10.1016/j.compedu.2012.10.001
  26. Maziriri, E. T., Gapa, P. & Chuchu, T. (2020). Student Perceptions Towards the use of YouTube as an Educational Tool for Learning and Tutorials. International Journal of Instruction, 13(2), 119-138. https://doi.org/10.29333/iji.2020.1329a
  27. Park, Y., Son, H. & Kim, C. (2012). Investigating the Determinants of Construction Professionals’ Acceptance of Web-Based Training: An Extension of the Technology Acceptance Model. Automation in Construction, 22, 377-386.‏ https://doi.org/10.1016/j.autcon.2011.09.016
  28. Ramírez-Correa, P., Mariano-Melo, A. & Alfaro-Pérez, J. (2019). Predicting and Explaining the Acceptance of Social Video Platforms for Learning: The Case of Brazilian YouTube Users. Sustainability, 11(24), 7115.‏ https://doi.org/10.3390/su11247115
  29. Ringle, C.M. & Sarstedt, M. (2016). Gain More Insight from Your PLS-SEM Results: The Importance-Performance Map Analysis. Industrial Management & Data Systems, 116(9), 1865-1886. https://doi.org/10.1108/IMDS-10-2015-0449
  30. Riswandi, D. (2016). Use of YouTube-based Videos to Improve Students’ Speaking Skill. In Proceeding of The International Conference on Teacher Training and Education, 2(1), 298-306.‏
  31. Sarstedt, M., Ringle, C. M. & Hair, J. F. (2017). Partial Least Squares Structural Equation Modeling. Handbook of Market Research, 1–40. 10.1007/978-3-319-05542-8_15-1
  32. Tahat, K. M., Al-Sarayrah, W., Salloum, S. A., Habes, M. & Ali, S. (2022). The Influence of YouTube Videos on the Learning Experience of Disabled People During the COVID-19 Outbreak. In: A. Hassanein, S. M. Elghamrawy & I. Zelinka (Ed.), Advances in Data Science and Intelligent Data Communication Technologies for COVID-19 (pp. 239-252). Springer, Cham.‏ https://doi.org/10.1007/978-3-030-77302-1_13
  33. Teo, T. (2009). Modelling Technology Acceptance in Education: A Study of Pre-Service Teachers. Computers & Education, 52(2), 302-312.‏ https://doi.org/10.1016/j.compedu.2008.08.006
  34. Ümit, E. C. & Çelik, N. (2024). Youtube Videolarının Eğitimi Destekleyici Rolü. Avrasya 11th International Conference on Social Sciences, Tashkent, 55-71.
  35. Wold, H. (1982). Soft Modeling: The Basic Design and Some Extensions. In: K. G. Jöreskog & H. Wold (Eds.), Systems Under Indirect Observation (pp. 1-54). Amsterdam: The Netherlands: North- Holland.
  36. Wong, K. K. K. (2013). Partial Least Squares Structural Equation Modeling (PLS-SEM) Techniques Using SmartPLS. Marketing Bulletin, 24(1), 1-32.‏
  37. Yang, C., Hsu, Y. C. & Tan, S. (2010). Predicting the Determinants of Users’ Intentions for Using YouTube to Share Video: Moderating Gender Effects. Cyber Psychology, Behavior, and Social Networking, 13(2), 141-152.‏ https://doi.org/10.1089/cyber.2009.0105
  38. Yılmaz, V. (2004). Lisrel ile Yapısal Eşitlik Modelleri: Tüketici Şikâyetlerine Uygulanması.‏ Sosyal Bilimler Dergisi, 1, 77-90.
  39. Yılmaz, V. & Çelik, H.E. (2016). Lisrel 9.1ile Yapısal Eşitlik Modellemesi. Ankara: Anı Yayıncılık.
  40. Yılmaz, V., Can, Y. & Şen, H. (2018). Küresel Isınma ve Küresel İklim Değişikliğine İlişkin Bilginin Kaygı ile Farkındalık Üzerine Etkisi: Bir Yapısal Eşitlik Model Önerisi. Researcher: Social Science Studies, 6(1), 434-450.
  41. Yılmaz, V. & Kinaş, Y. (2020). Kısmi En Küçük Kareler Yapısal Eşitlik Modellemesiyle Bir Elektrik Dağıtım Şirketinin Hizmet Kalitesinin Araştırılması. Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 15(2), 437-456. https://doi.org/10.17153/oguiibf.534641