ERIC Number: EJ1347225
Record Type: Journal
Publication Date: 2022-Aug
Pages: 35
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1360-2357
EISSN: EISSN-1573-7608
Facebook/Meta Usage in Higher Education: A Deep Learning-Based Dual-Stage SEM-ANN Analysis
Education and Information Technologies, v27 n7 p9821-9855 Aug 2022
The paper's main aim is to investigate and predict major factors in students' behavioral intentions toward academic use of Facebook/Meta as a virtual classroom, taking into account its adoption level, purpose, and education usage. In contrast to earlier social network research, this one utilized a novel technique that comprised a two-phase analysis and an upcoming the Artificial Neural Network (ANN) analysis approach known as deep learning was engaged to sort out relatively significant predictors acquired from Structural Equation Modeling (SEM). This study has confirmed that perceived task-technology fit is the most affirmative and meaningful effect on Facebook/Meta usage in higher education. Moreover, facilitating conditions, collaboration, subjective norms, and perceived ease of use has strong influence on Facebook usage in higher education. The study's findings can be utilized to improve the usage of social media tools for teaching and learning, such as Facebook/Meta. There is a discussion of both theoretical and practical implications.
Descriptors: Social Media, Virtual Classrooms, Higher Education, Technology Uses in Education, Intention, Student Behavior, Social Networks, Predictor Variables, Structural Equation Models, Usability, Electronic Learning, Artificial Intelligence
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A