TY - JOUR
T1 - A multi-analytical approach to predict the Facebook usage in higher education
AU - Sharma, Sujeet Kumar
AU - Joshi, Ankita
AU - Sharma, Himanshu
N1 - Publisher Copyright:
© 2015 Elsevier Ltd. All rights reserved.
PY - 2016/2/1
Y1 - 2016/2/1
N2 - Socio constructivist approach has an important say in cognitive absorption of learning in a student's life. This era of social networking services has given substantial importance to collaborative nature of learning, thus supporting Vygotsky's socio constructivist approach. The aim of this paper is to predict key determinants that affect students' intention towards academic use of Facebook. The usable data were gathered from 215 Omani students, and multi-analytical methods were employed to test the proposed research model. The results obtained from structural equation modeling (SEM) showed that resource sharing is the most influencing determinant in the decision of Facebook usage in higher education, followed by perceived usefulness, perceived enjoyment, collaboration and social influence. Further, the results obtained from SEM were used as input to the neural network model and results showed that collaboration is the most important predictor of Facebook adoption for academic purposes followed by, resource sharing, perceived enjoyment, social influence, and perceived usefulness. The findings of this study can be used to enhance the use of social media tool like Facebook for teaching and learning purposes. This is the first study which analyzed Facebook adoption for academic purposes by using a linear and nonlinear modelling. Theoretical and practical implications are discussed.
AB - Socio constructivist approach has an important say in cognitive absorption of learning in a student's life. This era of social networking services has given substantial importance to collaborative nature of learning, thus supporting Vygotsky's socio constructivist approach. The aim of this paper is to predict key determinants that affect students' intention towards academic use of Facebook. The usable data were gathered from 215 Omani students, and multi-analytical methods were employed to test the proposed research model. The results obtained from structural equation modeling (SEM) showed that resource sharing is the most influencing determinant in the decision of Facebook usage in higher education, followed by perceived usefulness, perceived enjoyment, collaboration and social influence. Further, the results obtained from SEM were used as input to the neural network model and results showed that collaboration is the most important predictor of Facebook adoption for academic purposes followed by, resource sharing, perceived enjoyment, social influence, and perceived usefulness. The findings of this study can be used to enhance the use of social media tool like Facebook for teaching and learning purposes. This is the first study which analyzed Facebook adoption for academic purposes by using a linear and nonlinear modelling. Theoretical and practical implications are discussed.
KW - Facebook
KW - Higher education
KW - Neural network
KW - Oman
KW - Social media
KW - Structural equation modeling
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U2 - 10.1016/j.chb.2015.09.020
DO - 10.1016/j.chb.2015.09.020
M3 - Article
AN - SCOPUS:84942772431
SN - 0747-5632
VL - 55
SP - 340
EP - 353
JO - Computers in Human Behavior
JF - Computers in Human Behavior
ER -