Integrating the Role of UTAUT and TTF Model to Evaluate Social Media Use for Teaching and Learning in Higher Education

Bibliographic Data

ID22087720
AuthorsAli Mugahed Al-Rahmi (0000-0002-1812-5800, Tun Hussein Onn University of Malaysia, corresponding author), Alina Shamsuddin (0000-0003-2700-7950, Tun Hussein Onn University of Malaysia), Eta Wahab (0000-0002-0706-7254, Tun Hussein Onn University of Malaysia), Waleed Mugahed Al-Rahmi (0000-0002-0980-7439, King Saud University), Uthman Alturki (0000-0002-5143-4779, King Saud University, corresponding author), Ahmed Aldraiweesh (0000-0003-2292-6907, King Saud University), Sultan Almutairy (King Saud University)
Year2022
Volume10
Pages905968-905968
Publication date2022-07-07
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2022.905968
PMID35875021
OpenAlexW4284712927
LanguageEN
Citations received9
References cited76

Investigation of task-technology fit and intention to use social media tools needs to focus specifically on higher education for teaching and learning, and its impact on students' academic performance. This article aims to develop a model that would identify essential aspects that are predicted to continue to play a large role in TTF for learning in BI, which could be used to improve academic performance in higher education. The purpose of this study was to investigate the characteristics and aspects of SM and the relationship between their use in the TTF and UTAUT theory to determine how they affect research students' satisfaction and AP in HE institutions. Data for the unified theory of acceptance and use of technology (UTAUT) and task-technology fit (TTF) theories were collected using a questionnaire survey. This research hypothesizes that behavioral intention to utilize social media and task-technology fit for learning will influence social characteristics, technology characteristics, performance expectancy, and effort expectancy, all of which will improve academic performance. As a test bed for this research, a structural equation model (SEM) was constructed examining the relationships between factors that affect students' academic performance. A stratified random sample strategy was used to disseminate the main tool of data collection, a questionnaire, to 383 students. A quantitative method was used to examine the results. The obtained outcomes showed that there was a correlation among social characteristics, technological characteristics, behavioral intention to use social media, and task-technology fit for academic performance, which aided student performance and results. The study indicates that PEX and EEX also demonstrated a strong relation to task-technology fit and behavioral intent to use social media for academic purposes, both of which positively impacted academic performance. As a result, the study found that behavioral intention to utilize and task-technology-fit social media promote students' active learning and enable them to discuss and exchange knowledge and information more efficiently. In conclusion, we encourage students to use social media for educational purposes in their studies and teaching through lectures in HE institutions

Data collection · Dissemination · Expectancy theory · Knowledge management · Mathematics education · Social influence · Social media · Social science · Sociology · Statistics · Stratified sampling · Structural equation modeling · Unified theory of acceptance and use of technology · Applied Psychology · Computer Science · Engineering · Impact of Technology on Adolescents · Knowledge Management and Sharing · Mathematics · Psychology · Social Psychology · Technology Adoption and User Behaviour

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