Technology-enhanced learning and research using databases in higher education: the application of the ODAS model

Chen, Hongyan; Islam, A.Y.M. Atiquil; Gu, Xiaoqing; Teo, Timothy; Peng, Zhengmei

doi:10.1080/01443410.2019.1614149

Cited by 18 publications

(43 citation statements)

References 33 publications

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“…Many previous studies have validated the significant associations between computer self-efficacy, perceived ease of use and usefulness (Abdullah & Ward, 2016;Bin et al, 2020;Chen et al, 2019;Thongsri et al, 2019;Yalçın & Kutlu, 2019). For instance, according to Abdullah and Ward's (2016) meta-analysis, computer self-efficacy is the greatest predictor of students' perceptions of the ease of use of online learning systems or platforms, and it is also an important predictor of students' perceived usefulness.…”

Section: Hypothesesmentioning

confidence: 85%

“…Extensive studies have shown that computer self-efficacy significantly impacts learners in various ways within a technology-supported environment (Dong et al, 2020;Heckel & Ringeisen, 2019;Wang et al, 2019;Zhu & Mok, 2020). Most importantly, recent studies have found that computer self-efficacy is directly related to the two key motivation variables in the TAM, perceived ease of use and usefulness (Bin et al, 2020;Chen et al, 2019;Thongsri et al, 2019;Yalçın & Kutlu, 2019). In other words, it is probable that university students with high computer self-efficacy find it easy to use online learning platforms as well as realize their value and benefits.…”

Section: Hypothesesmentioning

confidence: 99%

“…On the one hand, perceived ease of use and usefulness have frequently been considered core variables in different studies on online learning (Ameen et al, 2019;Esteban-Millat et al, 2018;Farhan et al, 2019;. On the other hand, technology satisfaction is also directly impacted by perceived ease of use and usefulness (Bin et al, 2020;Chen et al, 2019;Islam, 2016;Islam et al, 2018;Islam & Sheikh, 2020). However, as far as our knowledge is concerned, students' satisfaction with using online learning platforms has seldom been measured by perceived ease of use and usefulness in Chinese higher education.…”

Section: Hypothesesmentioning

confidence: 99%

“…For instance, according to Abdullah and Ward's (2016) meta-analysis, computer self-efficacy is the greatest predictor of students' perceptions of the ease of use of online learning systems or platforms, and it is also an important predictor of students' perceived usefulness. Moreover, Chen et al (2019), Islam et al (2018), and Islam and Sheikh (2020) argued that learners' satisfaction can also be influenced by computer self-efficacy and mediated by perceived ease of use and usefulness. However, very few studies on online learning platforms have validated the indirect impact in China.…”

Section: Hypothesesmentioning

confidence: 99%

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Online learning satisfaction in higher education during the COVID-19 pandemic: A regional comparison between Eastern and Western Chinese universities

et al. 2021

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Student satisfaction is of great significance in online learning, but few studies have explored its determinants in emerging countries. This study investigated the determinants of university students’ satisfaction with online learning platforms in China through applying the Technology Satisfaction Model during the COVID-19 pandemic, when an unprecedented amount of learning began to take place online due to the closure of educational institutions. A total of 928 students from five universities in four Chinese provinces or municipalities were surveyed through a purposive sampling technique and analyzed through structural equation modeling and the Rasch model. Findings show that Chinese university students’ satisfaction with online learning platforms is directly and indirectly impacted by their computer self-efficacy and the perceived ease of use and usefulness of the platforms. Findings also show that regional differences moderate the associations among these components. The current study adds to theoretical, methodical and practical understanding of university students’ satisfaction with using online learning platforms, which have been recognized as irreplaceable emergency educational tools.

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Section: Hypothesesmentioning

confidence: 85%

Section: Hypothesesmentioning

confidence: 99%

Section: Hypothesesmentioning

confidence: 99%

Section: Hypothesesmentioning

confidence: 99%

See 2 more Smart Citations

Online learning satisfaction in higher education during the COVID-19 pandemic: A regional comparison between Eastern and Western Chinese universities

et al. 2021

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“…For instance, Bin et al (2020) found that technical and vocational college teachers' perception of self-efficacy and subsequent satisfaction with new technologies were indirectly influenced by the technologies' PU and PEOU. Chen et al (2020) claimed that the online database adoption and satisfaction (ODAS) model confirmed that the PEOU and PU of databases are indirectly associated with postgraduate students' CSELE and satisfaction with the databases. According to Islam (2015), "lecturer satisfaction" is the degree to which the use of new technology is in line with lecturers' present values, needs, and experiences.…”

Section: Hypotheses Of the Tsm Modelmentioning

confidence: 99%

Assessment of ICT in Tertiary Education Applying Structural Equation Modeling and Rasch Model

Islam

Crook

et al. 2020

Sage Open

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Assessment studies using structural equation modeling and Rasch Model have long been prominent in all areas of educational psychology. Their emphases have covered, but have not been limited to, the improvement of quality in teaching, learning, and research as well as the pursuit of research productivity. However, such methodological approaches have rarely taken place in the arena of information and communication technology (ICT) in tertiary education. As such, this study assesses Chinese lecturers’ expression of ICT satisfaction through the technology satisfaction model (TSM). Data from 196 Chinese lecturers were collected using stratified random sampling and analyzed applying structural equation modeling and the Rasch model. The findings suggested that Chinese lecturers’ satisfaction around ICT use was explored by the three underlying antecedents of computer self-efficacy, perceived usefulness, and ease of use. Computer self-efficacy was evidently a powerful exogenous variable in assessing direct and indirect causal associations among the dimensions of TSM. In future research, it is recommended that assessment of Chinese lecturers’ ICT use for teaching and research purposes should be considered through structural equation modeling and the Rasch model. This would support future researchers, academicians, and practitioners in performing technological measurements in all the arenas of tertiary education.

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Medical and nursing students’ satisfaction with e-learning platforms during the COVID-19 pandemic: Initial findings of an experimental project in China

Chen,

Morgado,

Jiang

et al. 2024

Heliyon

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Technology-enhanced learning and research using databases in higher education: the application of the ODAS model

Cited by 18 publications

References 33 publications

Online learning satisfaction in higher education during the COVID-19 pandemic: A regional comparison between Eastern and Western Chinese universities

Online learning satisfaction in higher education during the COVID-19 pandemic: A regional comparison between Eastern and Western Chinese universities

Assessment of ICT in Tertiary Education Applying Structural Equation Modeling and Rasch Model

Medical and nursing students’ satisfaction with e-learning platforms during the COVID-19 pandemic: Initial findings of an experimental project in China

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