Developing a Learning Network on YouTube: Analysis of Student Satisfaction with a Learner-Generated Content Activity

  • Daniel BelancheEmail author
  • Luis V. Casaló
  • Carlos Orús
  • Alfredo Pérez-Rueda
Part of the Lecture Notes in Social Networks book series (LNSN)


This chapter focuses on an innovative learning project in which undergraduate marketing students create videos and post them on the official YouTube channel of the course. The project aims to apply new information technologies to university teaching, use social networks to disseminate information and knowledge, and provide students with a more active role in their learning process. We offer an overall vision to enable the appropriate application of this project and analyze students’ perceptions and satisfaction with the activity; we also offer a tool (e.g., rubric) to objectively evaluate the video content. The results of the first study show that students’ satisfaction with the activity is high and is affected by the emotions it generates, its perceived usefulness, and its ease of use. In a second study, we observe that the students are satisfied with the activity’s evaluation rubric, because it is a simple evaluation system and serves to guarantee an objective and consistent evaluation. The description of the project and discussion of the research findings will help academics to understand the key drivers of a satisfactory experience by students. It also provides scholars with advice on how to implement educational networking in their subjects.


YouTube Active learning Learner-generated content Satisfaction Rubric Networks 



Average variance extracted


European Higher Education Area


Information and communications technologies


Partial least squares


Technology acceptance model


  1. Alon, I., & Herath, R. K. (2014). Teaching international business via social media projects. Journal of Teaching in International Business, 25(1), 44–59.CrossRefGoogle Scholar
  2. Andrade, H. (2000). Using rubrics to promote thinking and learning. Educational Leadership, 57(5), 13–18.Google Scholar
  3. Azevedo, A., Apfelthaler, G., & Hurst, D. (2012). Competency development in business graduates: An industry-driven approach for examining the alignment of undergraduate business education with industry requirements. The International Journal of Management Education, 10(1), 12–28.CrossRefGoogle Scholar
  4. Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: Measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 20(4), 644–656.CrossRefGoogle Scholar
  5. Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 244–254.CrossRefGoogle Scholar
  6. Bagozzi, R. P., Belanche, D., Casaló, L. V., & Flavián, C. (2016). The role of anticipated emotions in purchase intentions. Psychology & Marketing, 33(8), 629–645.CrossRefGoogle Scholar
  7. Beauchamp, G., & Kennewell, S. (2010). Interactivity in the classroom and its impact on learning. Computers & Education, 54(3), 759–766.CrossRefGoogle Scholar
  8. Belanche, D., Casaló, L. V., & Flavián, C. (2010). Providing online public services successfully: The role of confirmation of citizens’ expectations. International Review on Public and Nonprofit Marketing, 7(2), 167–184.CrossRefGoogle Scholar
  9. Belanche, D., Casaló, L. V., & Flavián, C. (2012). Integrating trust and personal values into the Technology Acceptance Model: The case of e-government services adoption. Cuadernos de Economía y Dirección de la Empresa, 15(4), 192–204.CrossRefGoogle Scholar
  10. Belanche, D., Casaló, L. V., & Guinalíu, M. (2012). Website usability, consumer satisfaction and the intention to use a website: The moderating effect of perceived risk. Journal of Retailing and Consumer Services, 19(1), 124–132.CrossRefGoogle Scholar
  11. Bennett, S., Bishop, A., Dalgarno, B., Waycott, J., & Kennedy, G. (2012). Implementing Web 2.0 technologies in higher education: A collective case study. Computers & Education, 59(2), 524–534.CrossRefGoogle Scholar
  12. Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370.CrossRefGoogle Scholar
  13. Blasco-Arcas, L., Buil, I., Hernández-Ortega, B., & Sese, F. J. (2013). Using clickers in class. The role of interactivity, active collaborative learning and engagement in learning performance. Computers & Education, 62, 102–110.CrossRefGoogle Scholar
  14. Bonwell, C., & Eison, J. A. (1991). Active learning: Creating excitement in the classroom. Green Mountain Falls, CO: Eric Publications.Google Scholar
  15. British Columbia Ministry of Education. (2013). Defining cross-curricular competencies. Transforming curriculum and assessment. Ministry of Education. Technical Report, British Columbia Ministry of Education.Google Scholar
  16. Cano, E. (2008). La Evaluación por competencias en la Educación Superior. Profesorado: Revista de Currículum y Formación del Profesorado, 12(3), 11–27.Google Scholar
  17. Casaló, L. V., Flavián, C., & Guinalíu, M. (2008). The role of satisfaction and website usability in developing customer loyalty and positive word-of-mouth in the e-banking services. International Journal of Bank Marketing, 26(6), 399–417.CrossRefGoogle Scholar
  18. Chan, Y. M. (2010). Video instructions as support for beyond classroom learning. Procedia-Social and Behavioral Sciences, 9, 1313–1318.CrossRefGoogle Scholar
  19. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295–336.Google Scholar
  20. Chua, Y. P., & Chua, Y. P. (2017). How are e-leadership practices in implementing a school virtual learning environment enhanced? A grounded model study. Computers & Education, 109, 109–121.CrossRefGoogle Scholar
  21. Clifton, A., & Mann, C. (2011). Can YouTube enhance student nurse learning? Nurse Education Today, 31(4), 311–313.CrossRefGoogle Scholar
  22. Cole, M. (2009). Using Wiki technology to support student engagement: Lessons from the trenches. Computers & Education, 52(1), 141–146.CrossRefGoogle Scholar
  23. Cooper, P. (2019, January 22). YouTube stats that matter to marketers in 2019 [Online exclusive]. Hootsuite. Retrieved from:
  24. Davcik, N. S. (2014). The use and misuse of structural equation modeling in management research: A review and critique. Journal of Advances in Management Research, 11(1), 47–81.CrossRefGoogle Scholar
  25. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.CrossRefGoogle Scholar
  26. DeWitt, D., Alias, N., Siraj, S., Yaakub, M. Y., Ayob, J., & Ishak, R. (2013). The potential of Youtube for teaching and learning in the performing arts. Procedia-Social and Behavioral Sciences, 103, 1118–1126.CrossRefGoogle Scholar
  27. Dogtiev, A. (2019, January 7). YouTube revenue and usage statistics [Online exclusive]. Business of Apps. Retrieved from:
  28. Domínguez Fernández, G., & Llorente Cejudo, M. D. C. (2009). La educación social y la web 2.0: Nuevos espacios de innovación e interacción social en el espacio europeo de educación superior. Pixel-Bit. Revista de Medios y Educación, 35, 105–114.Google Scholar
  29. Duncan, I., Yarwood-Ross, L., & Haigh, C. (2013). YouTube as a source of clinical skills education. Nurse Education Today, 33(12), 1576–1580.CrossRefGoogle Scholar
  30. Dündar, H., & Akçayir, M. (2014). Implementing tablet PCs in schools: Students’ attitudes and opinions. Computers in Human Behavior, 32, 40–46.Google Scholar
  31. Dupuis, J., Coutu, J., & Laneuville, O. (2013). Application of linear mixed-effect models for the analysis of exam scores: Online video associated with higher scores for undergraduate students with lower grades. Computers & Education, 66, 64–73.CrossRefGoogle Scholar
  32. Eurico, S. T., da Silva, J. A. M., & do Valle, P. O. (2015). A model of graduates’ satisfaction and loyalty in tourism higher education: The role of employability. Journal of Hospitality, Leisure, Sport & Tourism Education, 16, 30–42.CrossRefGoogle Scholar
  33. Everson, M., Gundlach, E., & Miller, J. (2013). Social media and the introductory statistics course. Computers in Human Behavior, 29(5), 69–81.CrossRefGoogle Scholar
  34. Ferrer, F., Belvís, E., & Pàmies, J. (2011). Tablet PCs, academic results and educational inequalities. Computers & Education, 56(1), 280–288.CrossRefGoogle Scholar
  35. Fiorella, L., & Mayer, R. E. (2013). The relative benefits of learning by teaching and teaching expectancy. Contemporary Educational Psychology, 38(4), 281–288.CrossRefGoogle Scholar
  36. Fiorella, L., & Mayer, R. E. (2014). Role of expectations and explanations in learning by teaching. Contemporary Educational Psychology, 39(2), 75–85.CrossRefGoogle Scholar
  37. Fiorella, L., & Mayer, R. E. (2016). Eight ways to promote generative learning. Educational Psychology Review, 28(4), 717–741.CrossRefGoogle Scholar
  38. Forbes, H., Oprescu, F. I., Downer, T., Phillips, N. M., McTier, L., Lord, B., et al. (2016). Use of videos to support teaching and learning of clinical skills in nursing education: A review. Nurse Education Today, 42, 53–56.CrossRefGoogle Scholar
  39. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.CrossRefGoogle Scholar
  40. Fralinger, B., & Owens, R. (2009). YouTube as a learning tool. Journal of College Teaching & Learning, 6(8), 15–28.Google Scholar
  41. Gao, H., Hu, J., Wilson, C., Li, Z., Chen, Y., & Zhao, B. Y. (2010). Detecting and characterizing social spam campaigns. In Proceedings of the 10th ACM SIGCOMM conference on Internet measurement (pp. 35–47). New York: ACM.Google Scholar
  42. Gupta, S. (2014). Choosing Web 2.0 tools for instruction: An extension of task-technology fit. International Journal of Information and Communication Technology Education, 10(2), 25–35.CrossRefGoogle Scholar
  43. Gutiérrez Martín, A., & Tyner, K. (2012). Educación Para Los Medios, Alfabetización Mediática y Competencia Digital. Comunicar, 19(38), 31–39.CrossRefGoogle Scholar
  44. Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In R. R. Sinkovics & P. N. Ghauri (Eds.), New challenges to international marketing (pp. 277–319). Bingley: Emerald Group Publishing Limited.CrossRefGoogle Scholar
  45. Hofacker, C. F., & Belanche, D. (2016). Eight social media challenges for marketing managers. Spanish Journal of Marketing-ESIC, 20(2), 73–80.CrossRefGoogle Scholar
  46. Hoogerheide, V., Deijkers, L., Loyens, S. M., Heijltjes, A., & van Gog, T. (2016). Gaining from explaining: Learning improves from explaining to fictitious others on video, not from writing to them. Contemporary Educational Psychology, 44, 95–106.CrossRefGoogle Scholar
  47. Ifenthaler, D., & Schweinbenz, V. (2013). The acceptance of Tablet-PCs in classroom instruction: The teachers’ perspectives. Computers in Human Behavior, 29(3), 525–534.CrossRefGoogle Scholar
  48. Jenkins, J. J., & Dillon, P. J. (2013). Learning through YouTube. In S. P. Ferris & H. A. Wilder (Eds.), The plugged-in professor (pp. 81–89). Oxford: Chandos Publishing.CrossRefGoogle Scholar
  49. Johnson, D. W., Johnson, R. T., & Smith, K. A. (1998). Active learning: Cooperation in the college classroom. Edina, MN: Interaction Book Company.Google Scholar
  50. Jonsson, A. (2014). Rubrics as a way of providing transparency in assessment. Assessment & Evaluation in Higher Education, 39(7), 840–852.CrossRefGoogle Scholar
  51. Kay, R. H. (2012). Exploring the use of video podcasts in education: A comprehensive review of the literature. Computers in Human Behavior, 28(3), 820–831.CrossRefGoogle Scholar
  52. Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205–223.CrossRefGoogle Scholar
  53. Krauskopf, K., Zahn, C., & Hesse, F. W. (2012). Leveraging the affordances of Youtube: The role of pedagogical knowledge and mental models of technology functions for lesson planning with technology. Computers & Education, 58(4), 1194–1206.CrossRefGoogle Scholar
  54. Lee, C. S., Osop, H., Goh, D. H. L., & Kelni, G. (2017). Making sense of comments on YouTube educational videos: A self-directed learning perspective. Online Information Review, 41(5), 611–625.CrossRefGoogle Scholar
  55. Lee, M. J., & McLoughlin, C. (2007). Teaching and learning in the Web 2.0 era: Empowering students through learner-generated content. International Journal of Instructional Technology and Distance Learning, 4(10), 21–34.Google Scholar
  56. Levina, N., & Arriaga, M. (2014). Distinction and status production on user-generated content platforms: Using Bourdieu’s theory of cultural production to understand social dynamics in online fields. Information Systems Research, 25(3), 468–488.CrossRefGoogle Scholar
  57. Lewis, S., Pea, R., & Rosen, J. (2010). Beyond participation to co-creation of meaning: Mobile social media in generative learning communities. Social Science Information, 49(3), 351–369.CrossRefGoogle Scholar
  58. Liao, Y. W., Huang, Y. M., Chen, H. C., & Huang, S. H. (2015). Exploring the antecedents of collaborative learning performance over social networking sites in a ubiquitous learning context. Computers in Human Behavior, 43, 313–323.CrossRefGoogle Scholar
  59. Lichtenstein, D. R., Netemeyer, R. G., & Burton, S. (1990). Distinguishing coupon proneness from value consciousness: An acquisition-transaction utility theory perspective. Journal of Marketing, 54(3), 54–67.CrossRefGoogle Scholar
  60. Mayer, R. E. (2001). Multimedia learning. Cambridge: University Press.CrossRefGoogle Scholar
  61. Merchant, Z., Goetz, E. T., Cifuentes, L., Keeney-Kennicutt, W., & Davis, T. J. (2014). Effectiveness of virtual reality-based instruction on students’ learning outcomes in K-12 and higher education: A meta-analysis. Computers & Education, 70, 29–40.CrossRefGoogle Scholar
  62. Michael, J. (2006). Where’s the evidence that active learning works? Advances in Physiology Education, 30(4), 159–167.CrossRefGoogle Scholar
  63. Momeni, E., Cardie, C., & Diakopoulos, N. (2016). A survey on assessment and ranking methodologies for user-generated content on the web. ACM Computing Surveys (CSUR), 48(3), 41.54.Google Scholar
  64. Mon, F. M. E., & Cervera, M. G. (2011). El nuevo paradigma de aprendizaje y las nuevas tecnologías. REDU: Revista de Docencia Universitaria, 9(3), 55–73.CrossRefGoogle Scholar
  65. Okita, S. Y., Turkay, S., Kim, M., & Murai, Y. (2013). Learning by teaching with virtual peers and the effects of technological design choices on learning. Computers & Education, 63, 176–196.CrossRefGoogle Scholar
  66. Oliver, R. L. (1993). Cognitive, affective, and attribute bases of the satisfaction response. Journal of Consumer Research, 20(3), 418–430.CrossRefGoogle Scholar
  67. Orús, C., Barlés, M. J., Belanche, D., Casaló, L., Fraj, E., & Gurrea, R. (2016). The effects of learner-generated videos for YouTube on learning outcomes and satisfaction. Computers & Education, 95, 254–269.CrossRefGoogle Scholar
  68. Panadero, E., Jonsson, A., & Botella, J. (2017). Effects of self-assessment on self-regulated learning and self-efficacy: Four meta-analyses. Educational Research Review, 22, 74–98.CrossRefGoogle Scholar
  69. Pârvu, I., Ipate, D. M., & Mitran, P. C. (2014). Identification of employability skills-starting point for the curriculum design process. Economics, Management and Financial Markets, 9(1), 237–246.Google Scholar
  70. Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002). Academic emotions in students’ self-regulated learning and achievement: A program of qualitative and quantitative research. Educational Psychologist, 37(2), 91–105.CrossRefGoogle Scholar
  71. Pereira, J., Echeazarra, L., Sanz-Santamaría, S., & Gutiérrez, J. (2014). Student-generated online videos to develop cross-curricular and curricular competencies in Nursing Studies. Computers in Human Behavior, 31, 580–590.CrossRefGoogle Scholar
  72. Pérez-Mateo, M., Maina, M. F., Guitert, M., & Romero, M. (2011). Learner generated content: Quality criteria in online collaborative learning. European Journal of Open, Distance and E-Learning, 14(2), 1–12.Google Scholar
  73. Prince, M. (2004). Does active learning work? A review of the research. Journal of Engineering Education, 93(3), 223–231.CrossRefGoogle Scholar
  74. Real, J. C., Leal, A., & Roldán, J. L. (2006). Information technology as a determinant of organizational learning and technological distinctive competencies. Industrial Marketing Management, 35(4), 505–521.CrossRefGoogle Scholar
  75. Reddy, M. Y. (2007). Rubrics and the enhancement of student learning. Educate, 7(1), 3–17.Google Scholar
  76. Ringle, C. M. (2018). SmartPLS 2.0 (M3). Retrieved from:
  77. Rodriguez, J. E. (2011). Social media use in higher education: Key areas to consider for educators. Journal of Online Learning and Teaching, 7, 539–550.Google Scholar
  78. Roldán, J. L., & Sánchez-Franco, M. J. (2012). Variance-based structural equation modeling: Guidelines for using partial least squares in information systems research. In M. Mora, O. Gelman, A. L. Steenkamp, & M. Raisinghani (Eds.), Research methodologies, innovations and philosophies in software systems engineering and information systems (pp. 193–221). Hershey, PA: Information Science Reference.CrossRefGoogle Scholar
  79. Ryan, B. M. (2017). A review of protocols in higher education; How my experience made me question the process. Higher Education Studies, 7(4), 71–73.CrossRefGoogle Scholar
  80. Schmid, R. F., Bernard, R. M., Borokhovski, E., Tamim, R. M., Abrami, P. C., Surkes, M. A., et al. (2014). The effects of technology use in postsecondary education: A meta-analysis of classroom applications. Computers & Education, 72, 271–291.CrossRefGoogle Scholar
  81. Schulze, C., Schöler, L., & Skiera, B. (2014). Not all fun and games: Viral marketing for utilitarian products. Journal of Marketing, 78(1), 1–19.CrossRefGoogle Scholar
  82. Severt, D. E. (2002). The customer’s path to loyalty: A partial test of the relationships of prior experience, justice, and customer satisfaction (Doctoral dissertation, Virginia Tech).Google Scholar
  83. Shekhar, P., Prince, M., Finelli, C., Demonbrun, M., & Waters, C. (2019). Integrating quantitative and qualitative research methods to examine student resistance to active learning. European Journal of Engineering Education, 44(1–2), 6–18.CrossRefGoogle Scholar
  84. Sherer, P., & Shea, T. (2011). Using online video to support student learning and engagement. College Teaching, 59(2), 56–59.CrossRefGoogle Scholar
  85. Spisak, K. (2019, January 2). Social media trends & statistics [Online exclusive]. Business to Community. Retrieved from:–social-media-trends-statistics-02156179
  86. Stanley, D., & Zhang, Y. (2018). Student-produced videos can enhance engagement and learning in the online environment. Online Learning, 22(2), 5–26.CrossRefGoogle Scholar
  87. Steenkamp, J. B., & Geyskens, I. (2006). How country characteristics affect the perceived value of a website. Journal of Marketing, 70(3), 136–150.CrossRefGoogle Scholar
  88. Stickney, L. T., Bento, R. F., Aggarwal, A., & Adlakha, V. (2019). Online higher education: Faculty satisfaction and its antecedents. Journal of Management Education, Early cite. Scholar
  89. Stiggins, R. J. (2001). Student-involved classroom assessment. Upper Saddle River, NJ: Merrill Prentice Hall.Google Scholar
  90. Torres-Ramírez, M., García-Domingo, B., Aguilera, J., & De La Casa, J. (2014). Video-sharing educational tool applied to the teaching in renewable energy subjects. Computers & Education, 73, 160–177.CrossRefGoogle Scholar
  91. Tugrul, T. O. (2012). Student perceptions of an educational technology tool: Video recordings of project presentations. Procedia-Social and Behavioral Sciences, 64, 133–140.CrossRefGoogle Scholar
  92. van Diepen, N. M., Stefanova, E., & Miranowicz, M. (2009). Mastering skills using ICT: An active learning approach. In Research, reflections and innovations in integrating ICT in education (pp. 226–233). Badajoz, Spain: Formatex.Google Scholar
  93. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.CrossRefGoogle Scholar
  94. Whitaker, J. A., Orman, E. K., & Yarbrough, C. (2016). The effect of selected parameters on perceptions of a music education video posted on YouTube. In International perspectives on research in music education, 255–272.Google Scholar
  95. Wiertz, C., & de Ruyter, K. (2007). Beyond the call of duty: Why customers contribute to firm-hosted commercial online communities. Organization Studies, 28(3), 347–376.CrossRefGoogle Scholar
  96. Wright, G. B. (2011). Student-centered learning in higher education. International Journal of Teaching and Learning in Higher Education, 23(1), 92–97.Google Scholar
  97. Zahn, C., Schaeffeler, N., Giel, K. E., Wessel, D., Thiel, A., Zipfel, S., et al. (2014). Video clips for YouTube: Collaborative video creation as an educational concept for knowledge acquisition and attitude change related to obesity stigmatization. Education and Information Technologies, 19(3), 603–621.CrossRefGoogle Scholar
  98. Zaichkowsky, J. L. (1985). Measuring the involvement construct. Journal of Consumer Research, 12(3), 341–352.CrossRefGoogle Scholar
  99. Zote, J. (2019, February 1). 65 social media statistics to bookmark in 2019 [Online exclusive]. Sprout Social. Retrieved from:

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Daniel Belanche
    • 1
    Email author
  • Luis V. Casaló
    • 2
  • Carlos Orús
    • 1
  • Alfredo Pérez-Rueda
    • 3
  1. 1.Facultad de Economía y EmpresaUniversidad de ZaragozaZaragozaSpain
  2. 2.Facultad de Empresa y Gestión PúblicaUniversidad de ZaragozaHuescaSpain
  3. 3.Facultad de Ciencias Sociales y HumanasUniversidad de ZaragozaTeruelSpain

Personalised recommendations