Task-Technology Fit Analysis: Measuring the Factors that influence Behavioural Intention to Use the Online Summary-with Automated Feedback in a MOOCs Platform
DOI:
https://doi.org/10.34190/ejel.22.1.3094Keywords:
Automated feedback, Formative assessment, Online summary, Task-Technology Fit (TTF), MOOCsAbstract
The purpose of this study was to evaluate the factors that influence behavioural intention (BI) to use the Online Summary-with Automated Feedback (OSAF) in a MOOCs platform. Task-Technology Fit (TTF) was the main framework used to analyse the match between task requirements and technology characteristics, predictng the utilisation of the technology. The relationships between TTF and BI was moderated by students’ performance. This TTF provides an illustration of the extent to which the suitability of technology support for tasks will affect the performance and utilization of technology. There were 9 hypotheses examined in this study. The participants consisted of 151 students at a public university in East Java, Indonesia. In order to analyse the collected data, PLS-SEM (partial least squares - structural equation modeling) was employed, using SmartPLS 3.0. In this study, several points can be concluded, namely: 1) task characteristics and technology characteristics were not positively and significantly effected by TTF, while students' characteristics had a positive and significant effect on TTF; 2) TTF and utilization which are influenced by social influence, have a positive effect on performance impact. In this case the performance impact is constructed from 3 dimensions, namely: learning performance, personal integrity, self-confidence, except TTF were not postitive and were significantly affected by self-confidence. 3) TTF and performance impact positively influence behavioural intention, except in the dimension of performance impact, personal integrity was not postively and significantly effected by behavioural intention.
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Copyright (c) 2024 Saida Ulfa, Ence Surahman, Izzul Fatawi, Hirashima Tsukasa

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