Research Article
BibTex RIS Cite
Year 2022, Volume: 23 Issue: 2, 107 - 119, 30.03.2022
https://doi.org/10.17718/tojde.1096252

Abstract

References

  • Abdullah, F., & Ward, R. (2016). Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analysing commonly used external factors. Computers in Human Behavior, 56, 238-256.
  • Agudo-Peregrina, A. F., Hernandez-Garcia, A., & Pascual-Miguel, F. J. (2013). Behavioral intention, use behavior and the acceptance of electronic learning systems: differences between higher education and lifelong learning. Computers in Human Behavior, 34, 301-314.
  • Al-Abdullatif, A. M., & Aladsani, H. K. (2021). Understanding Instructors’ Cognitive Structure Toward the Academic Use of Social Network Sites: The Means–End Chain Theory. SAGE Open, 11(3)
  • Al-Adwan, A., Al-Madadha, A., & Zvirzdinaite, Z. (2018). Modeling Students’ Readiness to Adopt Mobile Learning in Higher Education: An Empirical Study. The International Review of Research in Open And Distributed Learning, 19(1). doi:http://dx.doi.org/10.19173/irrodl.v19i1.3256
  • Al-Emran, M., Elsherif, H. M., & Shaalan, K. (2016). Investigating attitudes towards the use of mobile learning in higher education. Computers in Human Behavior, 56, 93-102.
  • Almaiah, M. A., Al-Khasawneh, A., & Althunibat, A. (2020). Exploring the critical challenges and factors influencing the E-learning system usage during COVID-19 pandemic. Education and Information Technologies, 25, 5261-5280.
  • Al-Qaysi, N., Mohamad-Nordin, N., Al-Emran, M., & Al-Sharafi, M. A. (2019, October). Understanding the differences in students’ attitudes towards social media use: A case study from Oman. In 2019 IEEE Student Conference on Research and Development (SCOReD) (pp. 176-179). IEEE.
  • Al-Rahimi, W., & Othman, M. (2013). Using TAM model to measure the use of social media for collaborative learning. International Journal of Engineering Trends and Technology (IJETT), 5(2), 90-95.
  • Balakrishnan, V. (2014). Using social networks to enhance teaching and learning experiences in higher learning institutions. Innovations in Education and Teaching International, 51(6), 595-606.
  • Bell, F. (2011). Connectivism: Its place in theory-informed research and innovation in technology-enabled learning. The International Review of Research in Open and Distributed Learning, 12(3), 98-118.
  • Bennet, A., & Bennet, D. (2008). e-Learning as energetic learning. VINE: The Journal of Information & Knowledge Management Systems, 38(2), 206-220.
  • Bowers, J., & Kumar, P. (2017). Students’ perceptions of teaching and social presence: A comparative analysis of face-to-face and online learning environments. In Blended Learning: Concepts, Methodologies, Tools, and Applications, (pp. 1532-1550). IGI Global.

WHEN TECHNOLOGY-BASED LEARNING IS THE ONLY OPTION: EVALUATING PERCEIVED USEFULNESS OF SOCIAL MEDIA

Year 2022, Volume: 23 Issue: 2, 107 - 119, 30.03.2022
https://doi.org/10.17718/tojde.1096252

Abstract

During unusual times involving discontinued face to face sessions in formal education settings, mobile learning (m-learning) involving social networking sites has become a popular alternative since students are always in possession of handheld electronic devices. When connection through technology was the only option due to social distancing in current pandemic, students who were already active extensive users of social networks found online learning as a new way of getting formal education. The objective of this study was to explore how the state of student’s behavioral intention for social media based online learning is driven by external factors like subjective norm and self-efficacy. To fulfill this aim, this study uses a quantitative approach to study the factors that mediate the decision behavior of students towards social media employed as a learning platform and use of m-learning involving social networks. A sample of management science students (n= 255) from four universities participated in the research. Analysis of data suggested that subjective norm and self-efficacy were significant predictors for student participation in e-learning initiatives involving social media and networks. The proposed serial mediation model revealed that self-efficacy and perceived usefulness in that order were playing a positive significant role in student use of social networking for learning. No significant differences were observed between either gender when self-efficacy, perceived usefulness, and use of social media in education were considered.

References

  • Abdullah, F., & Ward, R. (2016). Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analysing commonly used external factors. Computers in Human Behavior, 56, 238-256.
  • Agudo-Peregrina, A. F., Hernandez-Garcia, A., & Pascual-Miguel, F. J. (2013). Behavioral intention, use behavior and the acceptance of electronic learning systems: differences between higher education and lifelong learning. Computers in Human Behavior, 34, 301-314.
  • Al-Abdullatif, A. M., & Aladsani, H. K. (2021). Understanding Instructors’ Cognitive Structure Toward the Academic Use of Social Network Sites: The Means–End Chain Theory. SAGE Open, 11(3)
  • Al-Adwan, A., Al-Madadha, A., & Zvirzdinaite, Z. (2018). Modeling Students’ Readiness to Adopt Mobile Learning in Higher Education: An Empirical Study. The International Review of Research in Open And Distributed Learning, 19(1). doi:http://dx.doi.org/10.19173/irrodl.v19i1.3256
  • Al-Emran, M., Elsherif, H. M., & Shaalan, K. (2016). Investigating attitudes towards the use of mobile learning in higher education. Computers in Human Behavior, 56, 93-102.
  • Almaiah, M. A., Al-Khasawneh, A., & Althunibat, A. (2020). Exploring the critical challenges and factors influencing the E-learning system usage during COVID-19 pandemic. Education and Information Technologies, 25, 5261-5280.
  • Al-Qaysi, N., Mohamad-Nordin, N., Al-Emran, M., & Al-Sharafi, M. A. (2019, October). Understanding the differences in students’ attitudes towards social media use: A case study from Oman. In 2019 IEEE Student Conference on Research and Development (SCOReD) (pp. 176-179). IEEE.
  • Al-Rahimi, W., & Othman, M. (2013). Using TAM model to measure the use of social media for collaborative learning. International Journal of Engineering Trends and Technology (IJETT), 5(2), 90-95.
  • Balakrishnan, V. (2014). Using social networks to enhance teaching and learning experiences in higher learning institutions. Innovations in Education and Teaching International, 51(6), 595-606.
  • Bell, F. (2011). Connectivism: Its place in theory-informed research and innovation in technology-enabled learning. The International Review of Research in Open and Distributed Learning, 12(3), 98-118.
  • Bennet, A., & Bennet, D. (2008). e-Learning as energetic learning. VINE: The Journal of Information & Knowledge Management Systems, 38(2), 206-220.
  • Bowers, J., & Kumar, P. (2017). Students’ perceptions of teaching and social presence: A comparative analysis of face-to-face and online learning environments. In Blended Learning: Concepts, Methodologies, Tools, and Applications, (pp. 1532-1550). IGI Global.
There are 12 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Aamer Hanıf This is me

Muhammad Imran This is me

Publication Date March 30, 2022
Submission Date November 12, 2020
Published in Issue Year 2022 Volume: 23 Issue: 2

Cite

APA Hanıf, A., & Imran, M. (2022). WHEN TECHNOLOGY-BASED LEARNING IS THE ONLY OPTION: EVALUATING PERCEIVED USEFULNESS OF SOCIAL MEDIA. Turkish Online Journal of Distance Education, 23(2), 107-119. https://doi.org/10.17718/tojde.1096252