Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning

Cheung, Ronnie; Vogel, Doug

doi:10.1016/j.compedu.2012.12.003

Cited by 677 publications

(494 citation statements)

References 50 publications

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“…Companies that want to avoid the under-utilisation of technological resources must focus on implementing effective strategies to encourage continued usage and participation intentions amongst users (Weng et al, 2015). Research involving intention to use emphasises the investigation of the antecedents that increase intended technology usage in the future (Armenteros, Liaw, Fernández, Díaz, & Sánchez, 2013;Cheung & Vogel, 2013;Chu & Chen, 2016). One of many theoretical models developed to study user behaviour is the theory of reasoned action (TRA), and according to the TRA, the immediate determinant of behaviour is the user's intention to perform or not to perform a given behaviour (Fishbein & Azjen, 1975).…”

Section: Intention To Use E-learningmentioning

confidence: 99%

Intention to Use and Satisfaction of e-Learning for Training in the Corporate Context

Esterhuyse

Scholtz

Venter

2016

IJIKM

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Together, the fields of education and information technology have identified the need for an online solution to training. The introduction of e-learning has optimised the learning process, allowing organisations to realise the many advantages that e-learning offers. The importance of user involvement in the success of e-learning makes it imperative that the forces driving intention to use e-learning and satisfaction thereof be determined. The purpose of this paper is to investigate the relationships between the metrics influencing intention to use and the satisfaction of using e-learning in companies.The results of a survey distributed amongst a South African software development company's customer base revealed that the 94 respondents have positive enjoyment and self-efficacy levels, and low computer anxiety levels. Correlation analysis revealed significant relationships between enjoyment and self-efficacy and between enjoyment and satisfaction. Companies should therefore ensure that users enjoy using e-learning as it can directly influence satisfaction and self-efficacy.

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Section: Intention To Use E-learningmentioning

confidence: 99%

Intention to Use and Satisfaction of e-Learning for Training in the Corporate Context

Esterhuyse

Scholtz

Venter

2016

IJIKM

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“…F. D. Davis (1985) first proposed TAM in 1985 to analyze the increasing important roles that technologies were playing in companies and organizations. TAM has also been utilized by many educational researchers over the years with respect to e-learning (Al-Mushasha, 2003;Cheung & Vogel, 2013), web-based collaborative learning systems (Liaw, Chen, & Huang, 2008), gamification (Torrente et al, 2014), e-textbooks (Ngafeeson & Sun, 2015), and computer technology education (Saleh, Prakash, & Manton, 2014). The application of TAM to study educational technologies follows from the argument that when examining the impact of a given technology on learning, one should also examine how students may accept the technology itself.…”

Section: Introductionmentioning

confidence: 99%

“…The results of their study showed that interactive content and cooperative learning approach utilized improved the enjoyment and curiosity of students, which in turn increased the use of the web-based tool. Cheung and Vogel (2013) explored TAM in the context of collaborative technologies for e-learning. Their work confirmed that TAM was a useful model for examining the effectiveness of technologies utilized in e-learning.…”

Section: Introductionmentioning

confidence: 99%

Impact of Collaborative Work on Technology Acceptance: A Case Study from Virtual Computing

Konak¹,

Kulturel-Konak²,

Nasereddin³

et al. 2017

JITE:Research

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Aim/PurposeThis paper utilizes the Technology Acceptance Model (TAM) to examine the extent to which acceptance of Remote Virtual Computer Laboratories (RVCLs) is affected by students' technological backgrounds and the role of collaborative work. BackgroundRVCLs are widely used in information technology and cyber security education to provide students with hands-on experimentation. However, students may not exploit their full benefits if they do not accept RVCLs as a viable educational technology. MethodologyIn order to study the impact of collaborative work on technology acceptance, an empirical study was conducted using collaborative and individual versions of an introductory level computer networking exercise in an RVCL. Trials for the empirical study included students from technology intensive and nontechnology intensive programs. ContributionThe relationship between the technological background of students and their acceptance of an RVCL and the effect of collaborative work on this relationship were explored for the first time in the literature. FindingsThe findings of the study supported that collaborative work could improve non-technology students' acceptance of RVCLs. However, no significant effect of collaborative work on technology acceptance was observed in the case of technology students. Impact of Collaborative Work on Technology Acceptance 16 Recommendations for PractitionersEducators should consider the benefits of collaborative work while introducing a new technology to students who may not have background in the technology introduced. Recommendation for ResearchersIn this study, student technological background was found to be a significant factor for technology acceptance; hence, it is recommended that technological background is included in TAM studies as an external factor. Future ResearchRepeating similar studies with multiple exercises with varying degrees of challenge is required for a better understanding of how collaborative work and student technological background affect technology acceptance.

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“…In an attempt to explore and understand the device, users could learn the device's compatibility−the degree to which a technology is perceived as being consistent with existing values, needs, and experiences of the users (Moore and Benbassat, as cited in [49]), the easiness and practicality in using it, and the information and instructions provided and shared [49]. By the efforts of learning, finding out (experiencing), and mastering the IoT health device in accordance with users' goals, they could construct and determine whether they perceive the device as useful.…”

Section: Results and Analysismentioning

confidence: 99%

Behavioral Intention to Use IoT Health Device: The Role of Perceived Usefulness, Facilitated Appropriation, Big Five Personality Traits, and Cultural Value Orientations

Prayoga¹,

Abraham²

2016

IJECE

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As one of the biggest technology breakthrough, Internet of Things (IoT) has been gaining much attention in every industry it’s involved in. Especially in the healthcare sector, IoT health devices have been proved to have a great impact on individual’s health regulation. Through many beneficial features from tracking sleep patterns to tracking chemicals in the blood, individuals will gain a better understanding of their body and how to keep it healthy. However, great benefit is one thing, and it does not immediately equal users’ acceptance. In this study, we seek to find elements that we propose to have an impact in predicting user’s intention of using IoT health device and integrate them into a model. We will analyze user’s technology acceptance from the perspective of Technology Acceptance Model, using Perceived Usefulness as the main predictor for Behavioral Intention. We also integrate Personality Traits and Facilitated Appropriation as factors to determine Perceived Usefulness, and finally using Hofstede’s Cultural Value, we seek to determine the antecedent of Facilitated Appropriation. The research design was correlational predictive, with path analysis technique. Participants of this study were 186 college students from IT campus (75 males, 111 females; mean of age = 20.86 years of old, standard deviation of age = 2.01 years) across Greater Jakarta. The results showed that Perceived Usefulness can predict intention to use the device. However, Personality Traits were found to be irrelevant in predicting perceived usefulness. Only Facilitated Appropriation could predict perceived usefulness. Among cultural values proposed, only the Long-term Orientation can predict user’s tendency to engage in Facilitated Appropriation. Also, we did not find any correlation between age and all technology acceptance factors (Behavioral Intention, Perceived Usefulness, and Facilitated Appropriation).

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Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning

Cited by 677 publications

References 50 publications

Intention to Use and Satisfaction of e-Learning for Training in the Corporate Context

Intention to Use and Satisfaction of e-Learning for Training in the Corporate Context

Impact of Collaborative Work on Technology Acceptance: A Case Study from Virtual Computing

Behavioral Intention to Use IoT Health Device: The Role of Perceived Usefulness, Facilitated Appropriation, Big Five Personality Traits, and Cultural Value Orientations

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