Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analysing commonly used external factors

By Fazil Abdullah, Rupert R. Ward. Computers in Human Behavior, 2016

912 citations recorded by the source corpus.

Subfields: Gender Studies, Information Systems and Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/3c4022d016aea37b358452f5fbec48a191e29122

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Citations in the corpus

The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers' adoption of digital technology in education (2019, methodology): “The selection of external variables comprised subjective norms, computer self-e ﬃ cacy, and facilitating conditions — three of the most prominent predictors of PEU and PU (Abdullah & Ward, 2016; Baydas & Goktas, 2017).”
Evaluating E-learning systems success: An empirical study (2020, methodology): “Based on the literature study conducted by Abdullah and Ward (2016), the five most used external factors by researchers and confirmed to have a relationship with TAM in the context of e-learning are self-efficacy, subjective norm, enjoyment, computer anxiety, and prior experience. According to the r”
Impact of flipped classroom on EFL learners' appropriate use of refusal: achievement, participation, perception (2018, background): “Abdullah and Ward’s (2016) study revealed that self-efficacy, subjective norm, enjoyment, computer anxiety, and experience were the most frequently used external factors affecting perceived usefulness and the perceived ease of use.”
Investigating the influence of the most commonly used external variables of TAM on students' Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) of e-portfolios (2016, methodology): “Based on extensive literature review on extended TAM in the context of e-learning, and in accordance with the GETAMEL developed by Abdullah and Ward (2016) (shown in figure 2), this study proposed the following research hypotheses: Hypothesis 1: SE positively affects students' PEOU of the…”
Determinants of E-government Adoption: Testing the Mediating Effects of Perceived Usefulness and Perceived Ease of Use (2019, background): “Other studies have also confirmed the significant effect of perceived ease of use on perceived usefulness (Abdullah & Ward, 2016; Alalwan et al., 2017; Baabdullah et al., 2016; Calisir & Calisir, 2004; Gefen & Straub, 2000; Susanto & Aljoza, 2015; Tobbin, 2010).”
College students’ use and acceptance of emergency online learning due to COVID-19 (2020, positive): “The ﬁndings from this study conﬁrm previous literature saying that students who are conﬁdent in applying a variety of self-regulated strategies are more likely to accomplish their academic tasks ( Abdullah & Ward, 2016 ; Alghamdi et al., 2020 ).”
Exploring the critical challenges and factors influencing the E-learning system usage during COVID-19 pandemic (2020, background): “Abdullah and Ward (2016) also investigated factors influencing e-learning acceptance using TAM.”
Examining university students’ behavioural intention to use e-learning during the COVID-19 pandemic: An extended TAM model (2021, background): “The prior studies found that experience positively impacted users’ perceived ease of use toward e-learning usage (Abdullah & Ward, 2016; Armenteros et al., 2013; Chang et al., 2017; De Smet et al., 2012; Lee et al., 2011; Tarhini et al., 2015).”
Exploring Students’ Acceptance of E-Learning Through the Development of a Comprehensive Technology Acceptance Model (2019, methodology): “Although Abdullah and Ward [24] achieved significant results by determining the most frequent factors affecting the e-learning adoption (i.”
“Extending the Technology Acceptance Model (TAM) to Predict University Students’ Intentions to Use Metaverse-Based Learning Platforms” (2023, background): “The importance of SE as a key determinant of PU and PEU in the educational field is well-established in the literature of technology adoption (Chahal & Rani, 2022; Abdullah et al., 2016 ).”