Factors influencing instructors’ intentions to use information technologies in higher education amid the pandemic

Şahin, Ferhan; Doğan, Ezgi; İliç, Ulaş; Şahin, Yusuf Levent

doi:10.1007/s10639-021-10497-0

Cited by 21 publications

(22 citation statements)

References 82 publications

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“…The findings could shed light on the basic factors that affect faculty members to use e-learning systems in general in higher education. Finally, these findings can be the basis for future research and, in particular, in comparing findings before and during the COVID-19 pandemic (Şahin, et al, 2021 ) since faculty who use LMS at least once a week participated in this research. In this frame, it is of big importance that similar studies should be conducted.…”

Section: Discussionmentioning

confidence: 89%

“…In the case of technology, FC consist of features & functions of a particular IS, e.g., technical support in the form of instructions (Thompson et al, 1991 ). Numerous researches have been conducted about the system quality, with the results showing that the offered affordances and the facilitating factors of an IS influence a person's perception of the ease of use of such a system (Fathema et al, 2015 ; Şahin et al, 2021 ; Teo, 2010 ; Zheng et al, 2018 ) and contribute to the formation of a positive attitude toward the use of the said system (Fathema et al, 2015 ; Lavidas et al, 2019 ; Teo, 2010 ). Thus, the hypotheses arising from the literature are as follows:…”

Section: Conceptual Modelmentioning

confidence: 99%

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Explaining faculty members’ behavioral intention to use learning management systems

2022

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Utilizing learning management system (LMS) in higher education and the factors could explain it is an emerging research field. Limited research has investigated factors influencing the adoption of LMS as a distinct system of e-learning as well as these studies mainly investigate the determinants of intention to use LMS from students and less from the point of view of the university instructors. This study investigates the factors that explain LMS acceptance from the faculty members. A version of the technology acceptance model including five external factors (perceived self-efficacy, subjective norm, image, technological complexity, and facilitating conditions) is proposed. The sample consists of 378 faculty members from 20 universities of Greece who declared to use LMS. A variance-based structural equation modeling was applied and ten out of thirteen hypotheses were confirmed. The total explained variance of behavioral intention to use LMS is estimated at 73%. Attitudes toward use, perceived usefulness, perceived easy of use, technological complexity, perceived self-efficacy, and subjective norm are the main determinants of faculty members’ behavioral intention to use LMS. Implications for training, educational policy, as well as the design and/or use of educational information systems are discussed.

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Section: Discussionmentioning

confidence: 89%

Section: Conceptual Modelmentioning

confidence: 99%

Explaining faculty members’ behavioral intention to use learning management systems

2022

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“…In this context, self‐efficacy, social influence, compatibility and facilitating conditions are among the important external factors whose effects have been reported extensively in the adoption of information technologies (e‐learning systems, distance education platforms, etc.) in the field of education (Chang et al, 2017; Park et al, 2012; Şahin et al, 2021; Ursavaş, 2014; Ursavaş et al, 2019; Venkatesh & Davis, 2000). Furthermore, these variables are considered as crucial constructs that affect the adoption of e‐learning systems of university students with disability (Doğan et al, 2021; Şahin, Doğan, Yıldız, & Okur, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…whom the user considers important for himself/herself on the user's use of technology (Ajzen & Fishbein, 1980; Baydaş & Göktaş, 2017; Şahin, 2016). Self‐efficacy is expressed as the degree of the user's belief in his/her knowledge of using technology and his/her ability to perform a task using technology (Compeau & Higgins, 1995; Şahin et al, 2021). Compatibility is explained as the degree of relevance of the technology used to the user's task and the ability of the technology to meet the user's expectations regarding the task (Ursavaş, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…When the literature is reviewed, it is observed that there are various findings indicating that the relationships between the variables affecting the acceptance of information technologies in education differ according to gender. In some studies, external factors have stronger effects on technology adoption and use of women than men (Lu et al, 2019; Şahin, 2021; Şahin et al, 2021), while in some studies, men are more experienced in technology adaptation and computer use than women (Tarhini et al, 2014; Venkatesh & Davis, 2000). On the other hand, no study investigating whether the variables affecting the acceptance of information technologies differ according to male and female students with disability has been encountered.…”

Section: Introductionmentioning

confidence: 99%

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Influential factors on e‐learning adoption of university students with disability: Effects of type of disability

Yıldız

Şahin

Doğan

et al. 2022

Brit J Educational Tech

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The number of studies providing empirical evidence on e‐learning in the field of special education is limited. From this point of view, the aim of this study is to examine whether the factors influencing the e‐learning adoption of university students with disability differ according to the type of disability and gender. The participants of the study consist of 809 university students with a single disability (orthopaedic, visual or hearing). Confirmatory factor analysis and two‐way ANOVA were used in the analysis of the study. The factor analysis showed that validity and reliability of the measurement tool was established and the model fit was good. The results revealed that for all dependent variables (social influence, self‐efficacy, compatibility and facilitating conditions), students with orthopaedic disability and visual impairment had higher scores than students with hearing impairment. On the other hand, contrary to expectations, there was no difference between students with orthopaedic disability and students with visual impairment in any of the factors according to the type of disability. In addition, none of the factors differed by gender. The findings provide empirical evidence that can contribute to the planning of online education processes of students with disability by revealing the similarities and differences in the use of e‐learning systems according to the type of disability. What is already known about this topic The field of special education deals with the special needs of individuals and frequently uses technology to provide the support they need. It is observed that educational processes have been moved to online environments due to the COVID‐19 pandemic, which has affected the field of education nowadays and e‐learning systems in online environments have become indispensable for students with special needs. With their flexible structure, e‐learning systems create universal and inclusive learning environments for all students. Accessibility and special education adaptations are needed for individuals with special needs to use e‐learning systems effectively. For this, first of all, the effects of the disabilities of these individuals in using e‐learning systems should be determined. What this paper adds The results showed that social influence, self‐efficacy, compatibility, and facilitating conditions all differed significantly by type of disability. The research findings revealed that all factors differed significantly in terms of orthopaedic and visual impairment versus hearing impairment. The main contribution of the study can be summarized as investigating the relationships between technology adoption and types of disability with empirical evidence and the fact that the implications and inferences made for theory and practice have the potential to make critical contributions to technology acceptance and use of individuals with special needs. It can be stated that the tool adapted in this study offers a valid and reliable tool for future studies with university students with special n...

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Evaluating Technology Acceptance Model on the User Resistance Perspective: A Meta-analytic Approach

Dönmez-Turan

Odabas

2022

Communications in Computer and Information Science

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Factors influencing instructors’ intentions to use information technologies in higher education amid the pandemic

Cited by 21 publications

References 82 publications

Explaining faculty members’ behavioral intention to use learning management systems

Explaining faculty members’ behavioral intention to use learning management systems

Influential factors on e‐learning adoption of university students with disability: Effects of type of disability

Evaluating Technology Acceptance Model on the User Resistance Perspective: A Meta-analytic Approach

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