What drives students’ intention to use tablet computers: An extended technology acceptance model

Zheng, Juan; Li, Shan

doi:10.1016/j.ijer.2020.101612

Cited by 88 publications

(75 citation statements)

References 53 publications

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“…Studies have revealed that social influence does not affect student attitude towards computers and the use of other devices because society's overall positive views cancel the effect of these forms of social influence [78,79]. However, Zheng and Li [80] demonstrated that in student acceptance of computers and the use of other devices, FS was a significant predictor of usefulness and ease of use. Overall, as students stayed at home and followed online courses during the pandemic, this study reasonably assumed that supporting students in their use of computers in online learning induced a positive effect on the students' perceived usefulness and ease of use of online learning.…”

Section: H5mentioning

confidence: 99%

Exploring the Critical Factors, the Online Learning Continuance Usage during COVID-19 Pandemic

Hsieh

Lin

et al. 2021

Sustainability

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In order to enable online learning to continue developing when the COVID-19 pandemic passes, this study aimed to identify the critical factors that affected the use of e-learning by university students during the pandemic. These critical factors will help to increase the efficiency of future development and deployment of online learning systems. Through a literature review, this study employed the technology acceptance model, social support, and task–technology fit as the theoretical basis to establish the framework of the online learning environment with regards to the technology acceptance model in the context of emergency management. A questionnaire survey was administered to students in universities that had implemented online teaching during the pandemic, and 552 valid responses were collected. The survey explored the factors affecting the willingness of higher education institution students to continue using online learning, and the following conclusions were drawn. (1) The easier an online learning platform was to navigate, the better it was perceived by the students, and thus the students were more willing to use it. (2) Ease of use and usefulness were associated with the teachers’ choice of platform and their ability to achieve a satisfactory fit between the course design and platform navigation, which thereby affected the students’ learning outcomes and attitude towards use. (3) The positive attitude of teachers towards teaching increased the students’ perceived ease of use of online learning. (4) During the pandemic, family support—a major support for teachers in online teaching—enhanced teachers’ attitudes towards, and willingness to provide, online teaching. A high level of support showed that the parents urged the students to learn and complete online learning tasks as instructed by the teachers, implying that family support could affect the students’ habits towards, adaptation to, and identification of online learning. The study results provide insights into the factors affecting the willingness of teachers and students to continue using e-learning platforms.

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Section: H5mentioning

confidence: 99%

Exploring the Critical Factors, the Online Learning Continuance Usage during COVID-19 Pandemic

Hsieh

Lin

et al. 2021

Sustainability

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“…Further studies have reinforced that PEU is a good predictor for perceived usefulness (Veloo & Masood, 2014;Elkaseh, Wong, & Fung, 2016;Zheng & Li, 2020). Prior experience and computer self-efficacy were found to positively influence PEU (Lee et al, 2013), while computer self-efficacy positively influences PEU, where PEU has a positive significant relationship towards behavioural intention (Hsia, Chang, & Tseng, 2014).…”

Section: Perceived Ease Of Use (Peu)mentioning

confidence: 93%

“…As SCT is commonly used in studies involving learning, knowledge management, human resource development, and career development (Kim & Park, 2018) and TAM is fundamental in exploring determinants of information technology usage (Choudhury & Pattniak, 2020;Zheng & Li, 2020), integrating these theories is appropriate to investigating behavioural intention to use e-learning. This study adopted computer self-efficacy and prior experience from SCT as well as perceived usefulness and perceived ease of use from TAM to form an integrated research model.…”

Section: Supporting Theoriesmentioning

confidence: 99%

“…Behavioural intention towards e-learning was found to be positively influenced by perceived usefulness (Zheng & Li, 2020) and negatively influenced by attitude (Lee, Hsieh, & Chen, 2013) or positively influenced by both perceived usefulness and attitude (Boateng, Mbrokoh, Boateng, Senyo, & Ansong, 2016). Perceived usefulness and perceived ease of use were found to increase behavioural intention to use e-learning (Ndubisi, 2004).…”

Section: Behavioural Intention To Use E-learning In the Workplace (Bi)mentioning

confidence: 99%

“…Perceived ease of use (PEU) refers to an individual's degree of belief that using a system is effortless (Boateng et al, 2016). PEU and perceived usefulness (Zheng & Li, 2020) positively impact both behavioural intention to use e-learning and actual usage (Rahmawati, 2019). Nevertheless, it has been found that PEU positively influences behavioural intention only through perceived usefulness and a positive attitude toward e-learning (Lee et al, 2013).…”

Section: Perceived Ease Of Use (Peu)mentioning

confidence: 99%

See 2 more Smart Citations

Predicting Behavioural Intention of Manufacturing Engineers in Malaysia to Use E-Learning in the Workplace

Teoh

Tan

2020

IRRODL

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This study aims to understand factors that affect the behavioural intention of manufacturing engineers in Malaysia to use e-learning in the workplace. Two hundred usable online questionnaires were collected from respondents who were engineers in Malaysian manufacturing companies. The data were analyzed using SPSS and Smart PLS version 3.2.6. Results supported all direct relationships except for the influence of prior experience in perceived ease of use. Interestingly, perceived usefulness and perceived ease of use fully mediated between computer self-efficacy and behavioural intention to adopt. The study provides theoretical implication to the technology acceptance model by confirming the mediating role of perceived ease of use and perceived usefulness in the context of a manufacturing setting in an emerging market. In practical terms, the study provides insights to guide organizations in designing e-learning systems that are well-received by employees at the workplace.

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Toward a comprehensive understanding of massive open online course adoption among college students

Huang,

Li,

2024

Future in Educational Research

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This paper investigated the factors affecting the behavioral intention (BI) and usage behavior (UB) of 548 Chinese college students in massive open online courses (MOOCs). We extended the unified theory of acceptance and use of technology model by incorporating self‐regulated learning (SRL) management, perceived pleasure (PP), and perceived cost constructs. This study also analyzed the moderating role of individual differences in gender, grade, major, and experience in MOOCs. Data were collected through both offline surveys across 10 universities and an online survey platform. Results from structural equation modeling and multi‐linear regression analyses revealed that students' BI was significantly and positively influenced by six factors: performance expectancy, effort expectancy, facilitating conditions (FC), social influence, SRL management (SM), and PP. Furthermore, we found that UB was predicted by BI, FC, and SM. Moreover, BI played a mediating role in the relationship between the two determining variables (i.e., FC and SM) and UB. Differences in MOOC experience level had a moderation effect. The study provided implications for various stakeholders regarding designing MOOC platforms, structures, and teaching activities.

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What drives students’ intention to use tablet computers: An extended technology acceptance model

Cited by 88 publications

References 53 publications

Exploring the Critical Factors, the Online Learning Continuance Usage during COVID-19 Pandemic

Exploring the Critical Factors, the Online Learning Continuance Usage during COVID-19 Pandemic

Predicting Behavioural Intention of Manufacturing Engineers in Malaysia to Use E-Learning in the Workplace

Toward a comprehensive understanding of massive open online course adoption among college students

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