Students’ Perceptions of Social Networks Platforms use in Higher Education: A Qualitative Research

  • Alhussain T
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Abstract

The use of social networks platforms for interactions, cooperative learning, and knowledge sharing for sharing information to improve students’ educational achievement seems to be one of the more widely examined topics in the Information Systems (IS) domain compared to the adoption of other technologies. However, as social networks platforms use distracts from studies and affects study habits, using social networks platforms can result in academic difficulties. Therefore, this research seeks to identify the interaction elements such as interaction with peers, cooperative learning and engagement for sharing information and perceptual elements such as perceived usefulness and perceived ease of use social networks platforms to improve educational achievement among students. This study is designed in accordance with the theory of constructivism. Qualitative research was applied to interviews conducted with a sample of 37 students. Data were analyzed using SPSS Statistics 20, and NVivo 11 was used for qualitative coding to investigate relationships between variables. The study found that interactions among students and interactions with lecturers enhance learning significantly. Additionally, the perceived overall benefits of using media platforms for learning and knowledge sharing that enhances satisfaction and affects educational achievement were high. Furthermore, the impact of social networks platforms use for education and knowledge sharing was also significant. Finally, the results indicate that students are satisfied with the use of media platforms as a means of learning and knowledge sharing. Findings show that using social networks platforms for learning and knowledge sharing should positively affected educational achievement of students.

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CITATION STYLE

APA

Alhussain, T. (2020). Students’ Perceptions of Social Networks Platforms use in Higher Education: A Qualitative Research. International Journal of Advanced Trends in Computer Science and Engineering, 9(3), 2589–2603. https://doi.org/10.30534/ijatcse/2020/16932020

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