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Granic, Andrina – Education and Information Technologies, 2022
During the past decades a respectable number and variety of theoretical perspectives and practical approaches have been advanced for studying determinants for prediction and explanation of user's behavior towards acceptance and adoption of educational technology. Aiming to identify the most prominent factors affecting and reliably predicting…
Descriptors: Educational Technology, Technology Integration, Predictor Variables, Electronic Learning
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Liu, Leping; Chen, Li-Ting; Li, Wenzhen – International Journal of Technology in Teaching and Learning, 2021
With new technology tools available for educators and students, effectively using these tools to improve teaching and learning has become a constant theme for research and practice in the field of education. In this study, case-analysis was conducted on 305 published studies (from 140 peer-reviewed regional, national and international journals)…
Descriptors: Educational Technology, STEM Education, Mathematics Education, Science Education
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Kumar, Jeya Amantha; Bervell, Brandford – Education and Information Technologies, 2019
The study adopted a modified Unified Theory of Acceptance and Use of Technology2(UTAUT2) as a theoretical foundation to investigate students' initial perceptions of Google Classroom as a mobile learning platform. By including six non-linear relationships within the modified model, the study examined the nuances in interaction terms between Habit…
Descriptors: Technology Uses in Education, Electronic Learning, Higher Education, Student Attitudes
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Qashou, Abeer – Education and Information Technologies, 2021
The tremendous and rapid developments in the information and communications technology sector as well as mobile devices have resulted in modern technologies, one of which is Mobile Learning (M-learning). M-learning is a new technique for learning that helps students to do their educational activities and access the learning materials easily…
Descriptors: Educational Technology, Technology Uses in Education, Telecommunications, Handheld Devices
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Tsang, Jenny T. Y.; So, Mike K. P.; Chong, Andy C. Y.; Lam, Benson S. Y.; Chu, Amanda M. Y. – Education Sciences, 2021
The global coronavirus disease (COVID-19) outbreak forced a shift from face-to-face education to online learning in higher education settings around the world. From the outset, COVID-19 online learning (CoOL) has differed from conventional online learning due to the limited time that students, instructors, and institutions had to adapt to the…
Descriptors: COVID-19, Pandemics, Online Courses, Educational Technology
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Ssemugenyi, Fred; Nuru Seje, Tindi – Cogent Education, 2021
This study examined the question of whether the "emergency remote teaching" that was accidentally adopted during the pandemic will eventually lead to an acceleration of digitalizing the teaching and learning processes at PNGUoT. Utilizing a mixed-method explanatory sequential design, quantitative data were collected first and followed by…
Descriptors: Foreign Countries, COVID-19, Pandemics, Distance Education
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Martín-García, Antonio Víctor; Martínez-Abad, Fernando; Reyes-González, David – British Journal of Educational Technology, 2019
The purpose of the study is to analyse and identify the stages of adoption of the blended learning (BL or b-learning) methodology in higher education contexts, and to assess the relationship of these stages with a set of variables related to personal and professional characteristics, attributes perceived on BL and contextual variables. About 980…
Descriptors: Blended Learning, Adoption (Ideas), Higher Education, Educational Technology
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Pozón-López, I.; Kalinic, Zoran; Higueras-Castillo, Elena; Liébana-Cabanillas, Francisco – Interactive Learning Environments, 2020
The purpose of this study is to classify the predictors of satisfaction and intention to use in Massive Open Online Courses (MOOC). Informed by a scientific literature review, this work poses a behavioral model to explain intention to use via various constructs. To this end, the authors have carried out a study through an online survey of Spanish…
Descriptors: Online Courses, Large Group Instruction, Predictor Variables, Student Satisfaction
Pechek, Ashley Ascherl – ProQuest LLC, 2018
The study examines students' counseling self-efficacy as measured by the Counseling Self-Estimate Inventory (COSE). A non-experimental design was implemented with 136 participants from 11 CACREP-accredited counselor education programs across the United States. Participants were enrolled in one of two learning modalities (e.g., face-to-face or…
Descriptors: Counselor Training, Self Efficacy, Statistical Analysis, Learning Modalities
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Montgomery, Amanda P.; Mousavi, Amin; Carbonaro, Michael; Hayward, Denyse V.; Dunn, William – British Journal of Educational Technology, 2019
Blended learning (BL) is a popular e-Learning model in higher education that has the potential to take advantage of learning analytics (LA) to support student learning. This study utilized LA to investigate fourth-year undergraduates' (n = 157) use of self-regulated learning (SRL) within the online components of a previously unexamined BL…
Descriptors: Blended Learning, Educational Technology, Higher Education, Undergraduate Students
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Mubuke, Faisal; Kituyi, Geoffrey Mayoka; Masaba, Kutosi Ayub; Ogenmungu, Cosmas; Nagujja, Shakilah – Journal of Educational Technology, 2018
Among information systems, mobile learning systems are acknowledged for the exponential growth in recent years into education sector specifically in the higher education learning institutions. Mobile learning systems are viewed as a kind of information system, which universities use to better serve their students efficiently and effectively in…
Descriptors: Foreign Countries, Social Influences, Predictor Variables, Intention
Beasley, Shannon Wilson Sewell – ProQuest LLC, 2016
Since the seminal work of Davis in 1989 produced the Technology Acceptance Model (TAM), researchers have sought to extend the framework and use the resulting models to describe the predictors of technology adoption specific to various populations. Although the TAM has been used to understand the adoption of technology in higher education, most of…
Descriptors: Adoption (Ideas), Educational Technology, Technical Education, Multivariate Analysis
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Shelton, Brett E.; Hung, Jui-Long; Lowenthal, Patrick R. – Distance Education, 2017
Early-warning intervention for students at risk of failing their online courses is increasingly important for higher education institutions. Students who show high levels of engagement appear less likely to be at risk of failing, and how engaged a student is in their online experience can be characterized as factors contributing to their social…
Descriptors: Asynchronous Communication, Online Courses, Educational Technology, Integrated Learning Systems
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Chan, Tan Fung Ivan; Borja, Marianne; Welch, Brett; Batiuk, Mary Ellen – Journal of Information Technology Education: Research, 2016
Instructional technologies can be effective tools to foster student engagement, but university faculty may be reluctant to integrate innovative and evidence-based modern learning technologies into instruction. Based on Rogers' diffusion of innovation theory, this quantitative, nonexperimental, one-shot cross-sectional survey determined what…
Descriptors: Probability, Faculty, Higher Education, Audience Response Systems
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Karatas, Serçin; Yilmaz, Ayse Bagriacik; Dikmen, Cemal Hakan; Ermis, Ugur Ferhat; Gürbüz, Onur – Quarterly Review of Distance Education, 2017
The aim of this study is to determine the trend concerning interaction in distance education between the years 2011 and 2015. According to this aim, 544 articles in the databases of EBSCO, Scopus, and Web of Science were examined. The examination has been conducted on the basis of various variables including year, country, number of authors,…
Descriptors: Distance Education, Trend Analysis, Interaction, Qualitative Research
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