Modelling technology acceptance in education: A study of pre-service teachers
By Timothy Teo. Comput. Educ., 2009
1,014 citations recorded by the source corpus.
Subfields: Gender Studies, Information Systems and Management, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/8f8a9ca964de9e6763fe2143a2fcf7397bf5d5a6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Gender Studies
- Xiaoquan Pan
- Anastasios A. Economides
- Timothy Teo
- Vasileios Terzis
- Jo Tondeur
- Dominik Petko
- Eugenia M. W. Ng
- Ronnie H. Shroff
In Information Systems and Management
- Xiaoquan Pan
- Anastasios A. Economides
- Jo Tondeur
- Fazilat Siddiq
- Ronny Scherer
- Timothy Teo
- Vasileios Terzis
- Eugenia M. W. Ng
In Sociology and Political Science
- Xiaoquan Pan
- Anastasios A. Economides
- Vasileios Terzis
- Jo Tondeur
- Eugenia M. W. Ng
- Ronnie H. Shroff
- Christopher C. Deneen
- Dominik Petko
Citations in the corpus
- The acceptance and use of computer based assessment (2011, methodology): “Assessment is a very important supplementary of the educational process because it measures the students’ learning (e.g. Joosten-ten Brinke, van Bruggen, Hermans, Burgers, Giesbers, Koper et al., 2007).”
- Technology Acceptance, Technological Self-Efficacy, and Attitude Toward Technology-Based Self-Directed Learning: Learning Motivation as a Mediator (2020, methodology): “Although previous studies highlighted the links of related variables of students’ technology acceptance (Teo, 2009; Lai, 2013), the other generating constructs (e.g., learning motivation) that may affect these associations have not been revealed.”
- Analysis of the technology acceptance model in examining students' behavioural intention to use an e-portfolio system (2011, methodology): “Overall, the technology acceptance model (TAM) has received empirical support for being robust in predicting technology adoption in various contexts and with a variety of technologies (Gao, 2005; McKinnon & Igonor, 2008; Park, 2009; Sugar, Crawley & Fine, 2004; Teo, 2009).”
- The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers' adoption of digital technology in education (2019, background): “This is in fact a strong assumption in the context of TAM, since a considerable number of studies uncovered that full measurement invariance might not hold even across smaller sets of study samples or countries (e.g., Teo, 2015; Teo et al., 2009).”
- Technology acceptance among pre-service teachers: Does gender matter? (2015, background): “non-users (Teo, 2009).”
- Assessing the intention to use technology among pre-service teachers in Singapore and Malaysia: A multigroup invariance analysis of the Technology Acceptance Model (TAM) (2009, background): “…2005), students’ acceptance of an online course companion site of a textbook (Gao, 2005), the effect of technical support on students’ acceptance towards WebCT (Ngai, Poon, & Chan, 2007), and the attitudes of pre-service teachers towards the use of technology in education (Teo, 2008a, 2009).”
- A meta-analysis of e-learning technology acceptance: The role of user types and e-learning technology types (2011, neutral): “…Klobas (2009) 269 Students E-learning System (WebCT) TTF Teo, Lee, Chai, and Wong (2009) 250/245 Teachers/ professors E-learning Technology/Tool TAM Teo (2009) 475 Teachers/ professors E-learning Technology/Tool TAM Sørebø, Halvari, Gulli, and Kristiansen (2009) 124 Teachers/ professors E-learning…”
- Teachers' pedagogical beliefs and their use of digital media in classrooms: Sharpening the focus of the 'will, skill, tool' model and integrating teachers' constructivist orientations (2012, background): “These conditions generate a positive attitude and increased willingness to use these technologies (Davis, 1989; Teo, 2009).”
- An investigation of mobile learning readiness in higher education based on the theory of planned behavior (2012, background): “TAM argues that there are causal relationships between perceived ease of use, perceived usefulness, attitude toward a new system, and behavioral intention to use the system (Davis, 1989; Teo, 2009).”