User acceptance of social learning systems in higher education: an application of the extended Technology Acceptance Model

Akman, İbrahim; Turhan, Çiğdem

doi:10.1080/14703297.2015.1093426

Cited by 40 publications

(37 citation statements)

References 20 publications

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“…There is a large number of research studies carried out on this subject in the educational field related to RA, as well as a high number of meta-analyzes of the different educational models which allow to verify that they offer validity and solidity to how the intention of developing use of different technological environments in subjects. Recently, this has also been confirmed when analyzed with the structural equation models [55][56][57][58][59][60][61][62][63][64][65].…”

Section: Information Collection Instrumentsmentioning

confidence: 64%

Educational Uses of Augmented Reality (AR): Experiences in Educational Science

et al. 2019

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Augmented Reality (AR) is an emerging technology that is gaining greater influence on teaching every day. AR, together with mobile technology, is defined as one of the most efficient pairs for supporting significant and ubiquitous learning. Purpose of the study: the Instructional Material Motivational Survey (IMMS), by Keller, was used to determine the degree of motivation possessed by the Pedagogy students on the utilization of the notes enriched with AR in the classroom, available for their didactic use through mobile devices. Methods: through an app designed for the courses Education Technology (ET) and Information and Communication Technologies (ICT) Applied to Education, the motivation gained when participating in this experience, and how it influences the improvement of academic performance, was evaluated. Results and conclusions: the most notable main result was finding a strong relationship between the motivation of the students when using the enriched notes and the increase of performance in the academic subject where it was used. Likewise, it was proved that the use of Augmented Reality benefited the learning process itself.

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Section: Information Collection Instrumentsmentioning

confidence: 64%

Educational Uses of Augmented Reality (AR): Experiences in Educational Science

et al. 2019

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“…The findings indicated age and employment status were significant factors in predicting students' adoption of m-LMS. Akman and Turhan (2017) examined the users' acceptance of social learning systems in higher education with an extended TAM. They found that perceived usefulness, security awareness and ethical awareness were significant predictors of users' behaviour towards using social learning systems.…”

Section: Adoption Of M-lmsmentioning

confidence: 99%

Investigating university students’ intention to use mobile learning management systems in Sweden

Saroia

Gao

2018

Innovations in Education and Teaching International

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This study aims to explore university students' intention to use mobile learning management systems (m-LMS) in higher education in Sweden. To address this, a research model based on the technology acceptance model (TAM) and nine research hypotheses are developed. In addition to perceived usefulness and perceived ease of use from the TAM, the research model includes academic relevance, university management support and perceived mobility value from previous literature as external variables to study the adoption of m-LMS. The proposed research model and research hypotheses are empirically tested with 130 university students in Sweden. According to the results, support is found for seven of the nine research hypotheses. This study contributes to the validation of the extended TAM for mobile learning and demonstrates the hypothesised model moderately predicts students' intention to adopt m-LMS in higher education in Sweden.

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“…The TAM was specifically developed to predict and explain computer usage, and uses the TRA as a theoretical basis for establishing causal linkages between the constructs of PU, PEOU, ATU, behavioral intention to use, and actual use of technology. Many studies have integrated the TAM into their research models to analyze factors that influence the behavioral intention to adopt various ICTs in education, including mobile learning [37], [38], cloud computing at universities [39], [40], social media in higher education [41]- [43], electronic portfolios [44], the Line mobile app for English oral training [45], and massive open online courses [46].…”

Section: A Dgsmentioning

confidence: 99%

“…PEOU I find GeoGebra easy to use. [41], [42], [54] Learning to operate GeoGebra would be easy for me. It would be easy for me to become skillful at using GeoGebra.…”

Section: A Survey Instrumentmentioning

confidence: 99%

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Predicting the Determinants of Dynamic Geometry Software Acceptance: A Two-Staged Structural Equation Modeling — Neural Network Approach

Chen¹

2020

IJIET

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User acceptance of social learning systems in higher education: an application of the extended Technology Acceptance Model

Abstract: a department of computer Engineering, atilim university, ankara, turkey; b department of software Engineering, atilim university, ankara, turkey

Cited by 40 publications

References 20 publications

Educational Uses of Augmented Reality (AR): Experiences in Educational Science

Educational Uses of Augmented Reality (AR): Experiences in Educational Science

Investigating university students’ intention to use mobile learning management systems in Sweden

Predicting the Determinants of Dynamic Geometry Software Acceptance: A Two-Staged Structural Equation Modeling — Neural Network Approach

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