Integrated the role of UTAUT and TTF model to evaluate social media use for teaching and learning in higher education
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 t...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/7631/1/J14508_0c1f15f72df3e695cfcb1e71506f0408.pdf http://eprints.uthm.edu.my/7631/ https://doi.org/ 10.3389/fpubh.2022.905968 |
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| Summary: | 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. |
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