A survey of pre-service teachers’ acceptance of technology in Thailand

Teo, Timothy; Khlaisang, Jintavee; Thammetar, Thapanee; Ruangrit, Nammon; Satiman, Anirut; Sunphakitjumnong, Kobkul

doi:10.1007/s12564-014-9348-3

Cited by 10 publications

(6 citation statements)

References 20 publications

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“…Only a few studies have looked at the variables that impact Serbian pre-service teachers' intentions to utilize technology to date, mainly in the mathematics classroom (Milutinović, 2016;Teo & Milutinović, 2015;Teo et al, 2017). Researchers in Serbia, as well as those in other developing countries, are interested in knowing more about the important factors in implementing technology in the classroom (Mei et al, 2018;Teo et al, 2014;Kafyulilo et al, 2015).…”

Section: Present Studymentioning

confidence: 99%

Examining the influence of pre-service teachers’ digital native traits on their technology acceptance: A Serbian perspective

Milutinović

2022

Educ Inf Technol

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Many seem to believe that today’s pre-service teachers as born after 1980 are digital natives, or that they are “native speakers” of the digital language. Nevertheless, there is no evidence that their digital native characteristics determine whether or not they would use technology in the classroom. Although not widely evaluated, the four-factor, 21-item Digital Nativity Assessment Scale (DNAS) was one of the first instruments to assess digital nativeness (DN). This study aim is to explore the influence of pre-service teachers’ DN on their intention to use technology in the future classroom in Serbia, by evaluating the DNAS on Serbian sample and using it for measuring the DN. Six variables were incorporated to examine their mutual relationships based on technology acceptance model: digital nativeness, behavioral intention (BI), perceived usefulness (PU), perceived ease of use (PEU), subjective norm (SN), and technological complexity (TC). Data were collected from 688 pre-service teachers in Serbia. Exploratory factor analysis confirmed a four-factor model for the DNAS, and Serbian pre-service teachers demonstrated a high level of DN. To evaluate the hypothesized model structural equation modeling was utilized. The suggested model had a good fit for describing the BI of Serbian pre-service teachers, accounting for 27.1% of the variance in BI. It was found that direct dominant predictors of BI are digital native traits, perceived usefulness, and perceived ease of use. Significant influence of digital native traits on all other variables in the model was also confirmed. The implications for theory and practice are discussed.

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Section: Present Studymentioning

confidence: 99%

Examining the influence of pre-service teachers’ digital native traits on their technology acceptance: A Serbian perspective

Milutinović

2022

Educ Inf Technol

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“…In this sense, both PEOU and TSE share commonalities, and empirical studies testified that the two constructs are interwoven (Scherer, Siddiq, & Teo, 2015); (2) One may distinguish further between the beliefs related to the interaction between technology and the Self (PEOU and PU) and the attitudes and self-beliefs (ATT and TSE), next to the external beliefs (SN and FC). The close relationship between ATT and TSE, for instance, surfaced in many studies of technology acceptance (e.g., Scherer et al, 2018); (3) Finally, it could also be assumed that all variables represent the technology acceptance construct without any grouping (Teo et al, 2014). This assumption is based on the finding that the technology acceptance variables are all substantially intercorrelated Yen, Sousa, & Bakken, 2014), perhaps due to their conceptual overlap (i.e., they all represent attitudes and beliefs related to technology) and the common method variance their assessments share (i.e., they are all assessed by self-reports; see Sharma, Yetton, & Crawford, 2009).…”

Section: Technology Acceptance Models and Measuresmentioning

confidence: 99%

“…The question, however, remains whether and to what extent these variables represent an overall technology acceptance construct (Nistor, 2014). Teo et al (2014), for instance, found that a second-order factor of technology acceptance could be established that was indicated by the technology acceptance variables as first-order factors.…”

Section: The Diversity Of Findings On the Relations Between Technolog...mentioning

confidence: 99%

“…Consequently, examining how technology acceptance can be represented as a construct measured by several indicators is part of the crafting of a validity argument (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 2014). To our best knowledge, this perspective has largely been ignored, and only few studies exist that tested the assumption of an overall technology acceptance construct represented by multiple indicators, namely PU, PEOU, ATT, TSE, SN, and FC (Teo et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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All the same or different? Revisiting measures of teachers' technology acceptance

Scherer

Siddiq

Tondeur

2020

Computers & Education

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“…Its development is carried out in gathering and evaluating related research on a particular topic focus [23], [24]. This research is carried out for various purposes [25], including identifying, studying [26], evaluating, and interpreting almost all available research with the topic area of the phenomenon of interest, with certain relevant research questions [27]. Besides that, it is often needed as a research agenda determination, part of a dissertation or thesis, and is a part that complements the substantive requirements for research grant applications [28], [29].…”

Section: Methodsmentioning

confidence: 99%

Acceptance of Technology in Online Learning Perspective at Educational Institutions : A Systematic Literature Review

Pamuji¹

2020

ITEJ

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Today, many applications or technologies have been produced by every software developer. However, the success of all there is the decision of each user. Users have two possibilities to accept or reject a technology that is presented. The TAM model has been widely researched and undergone development and changes besides being quite reliable in predicting the level of technology acceptance in all countries in the world. In this study, we will recapitulate all studies on the acceptance of technology in the field of Education that handles online learning. The results showed that there was 51 article review publication were selected through some process of review. The period taken ranges from 2011 to 2020. The main findings show that there are differences in the models, methods, and applications identified. Since the TAM model has two basic variables, namely perceived ease of use and perceived usefulness as a framework for analyzing the make and influence technology acceptance. In this study also provides information about the results of the identification of some of the gaps in current research and also in the future. Therefore, the results of a systematic literature review were able to provide a better understanding of TAM especially in the perspective of education in online learning.

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A survey of pre-service teachers’ acceptance of technology in Thailand

Cited by 10 publications

References 20 publications

Examining the influence of pre-service teachers’ digital native traits on their technology acceptance: A Serbian perspective

Examining the influence of pre-service teachers’ digital native traits on their technology acceptance: A Serbian perspective

All the same or different? Revisiting measures of teachers' technology acceptance

Acceptance of Technology in Online Learning Perspective at Educational Institutions : A Systematic Literature Review

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