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Khalid Mohiuddin; Huda Fatima; Mohiuddin Ali Khan; Mohammad Abdul Khaleel; Zeenat Begum; Sajid Ali Khan; Omer Bin Hussain – SAGE Open, 2023
This article aims to design a novel edge-centric hierarchical cloud architecture to optimize mobile learning (m-learning) performance during learners executing computation-intensive learning applications. This research adopts the potential of distributed computing paradigms, that is, mobile edge, for improving the effectiveness of m-learning…
Descriptors: Computer Networks, Electronic Learning, College Students, Handheld Devices
Adzifome, Nixon Saba; Agyei, Douglas Darko – Education and Information Technologies, 2023
Mobile learning is the newest and emerging technology embraced by universities and this seems to be fast establishing itself as the preferred mode of learning in many countries. However, ways in which mobile devices are used to meet learning goals seem under-researched and may require more effort from researchers, especially in the context of…
Descriptors: Electronic Learning, Handheld Devices, College Students, Foreign Countries
Topa Ciftci, Gaye; Dogan, Murat Ertan; Unal, Burcin – Turkish Online Journal of Distance Education, 2023
This study aims to reveal the strengths and limitations of the WhatsApp application as a support service in distance education, conducted through a learning management system during the COVID-19 pandemic, and make suggestions on improving its use in this capacity. Despite the lack of readiness on the part of the students and the lack of sufficient…
Descriptors: Educational Technology, Distance Education, Social Media, COVID-19
Luis Alberto Laurens-Arredondo – Education and Information Technologies, 2024
The use of technologies in the classroom has become one of the main allies for university teachers in pedagogical innovation, especially during, and after the pandemic. Therefore, the main objective of this article is to investigate how different types of innovative technologies are most effective in increasing motivation among university…
Descriptors: Educational Technology, Student Motivation, Technology Uses in Education, College Students
Mills, Michael S.; Watson, Jessica Herring; Miller, Rachelle; Morrison, Mia – SRATE Journal, 2022
The focus of this research was measuring the effect of Twitter use in the classroom on students' acceptance of technology using the TAM-3 model. This mixed methods study revealed a significant effect from students' use of Twitter in classroom assignments not only on increasing candidates' view of Twitter as being useful, easy to use, and relevant…
Descriptors: Social Media, Technology Uses in Education, Telecommunications, Handheld Devices
Ikhsan, Ridho Bramulya; Prabowo, Hartiwi; Yuniart; Simamora, Bachtiar; Ruan, Ximing; Kumar, Vikas – Journal of Educators Online, 2023
A mobile learning management system (mobile LMS) facilitates the interaction between lecturers and students to transfer knowledge flexibly. With the high possibility of universities adopting a mobile LMS into their learning systems, predicting student acceptance of mobile LMS is critical. Based on an extension of the unified theory of acceptance…
Descriptors: Foreign Countries, Electronic Learning, Distance Education, College Students
Daisy Das; Masum Ahmed – E-Learning and Digital Media, 2024
Many educational institutions lack well-defined, targeted policies to address problems relating to student smartphone use on campus. In this study, we analyse the patterns of student smartphone use on academic campuses and propose a range of policy measures to address the problems arising from such use. Our research, which draws on primary data…
Descriptors: Student Attitudes, Telecommunications, Handheld Devices, Technology Uses in Education
Sarah Ransdell – Distance Learning, 2023
Ransdell and Rieck (2020) found that distance learning was a physical and mental challenge in the first year of the COVID-19 pandemic. The present study compares Zoom, Canvas, and smartphone use from 2020 to 2023, when the COVID-19 pandemic has receded. For many students, phones are used more and larger devices less. Students who realize that…
Descriptors: Handheld Devices, Telecommunications, COVID-19, Pandemics
Rodríguez, C. A.; Valderrama, Steven; Vargas, David; Eliseo, Maria Amelia; Fracchia, Claudia Carina; Roa, Katherine – Journal of Educators Online, 2023
The different commercial and open-source LMSs do not support pre-built activities for students in Augmented Reality (AR). To solve this challenge, this work combines AR technology and the Moodle platform to enhance the capabilities to motivate students during the learning process. For this, we developed and configured an AR app to receive and…
Descriptors: Case Studies, Learning Management Systems, Computer Simulation, Student Motivation
Orly Calderon; Susan Penque; David Luhr; Caryn Nahum; Lauren Scardigno – International Association for Development of the Information Society, 2023
The purpose of this mixed method research study is to describe the experiences of faculty and students in post-secondary education institutions as they shifted to remote education at the start of the COVID-19 pandemic, and to understand these experiences in the context of previous research about pre-pandemic remote or mobile education. One hundred…
Descriptors: College Faculty, College Students, Experience, COVID-19
David Imamyartha; Utami Widiati; M. Zaini Miftah – MEXTESOL Journal, 2024
Despite the recent growth of mobile instant messenger (MIM), research into the correlation between English learners' learning gains, learning engagement, and how this engagement helps develop authentic relationships remains underexplored. This mixed-method study involved 222 college English learners to investigate their engagement in team-based…
Descriptors: Discourse Analysis, Computer Software, Computer Mediated Communication, Synchronous Communication
Aziman Abdullah – International Society for Technology, Education, and Science, 2023
This study explores the potential of using screen time data in learning management systems (LMS) to estimate student learning time (SLT) and validate the credit value of courses. Gathering comprehensive data on actual student learning time is difficult, so this study uses LMS Moodle logs from a computer programming course with 490 students over 16…
Descriptors: Time Factors (Learning), Handheld Devices, Computer Use, Television Viewing
Maha Abbas M. Alazwari – ProQuest LLC, 2024
Our world is a rapidly changing society, surrounded by local and global challenges, the most important of which are technological and technical developments, and global openness represented by the spread of communication networks, the Internet, and others. Perhaps the most important of these technologies is what is known as smartphone applications…
Descriptors: Telecommunications, Handheld Devices, Computer Software, Sustainable Development
Ko, Myong-Hee – Computer Assisted Language Learning, 2022
The present study investigates South Korean university students' personal computer (PC) and smartphone usage patterns on an online Test of English for International Communication (TOEIC) website using learning analytics. A total of 107 students taking a "College TOEIC" course participated during one academic semester and records of their…
Descriptors: Computers, Telecommunications, Handheld Devices, English (Second Language)
Abou Adel, Mohammed – Arab World English Journal, 2022
This research aims to create a smart electronic course, which simplifies the information, and reduces the time and effort in acquiring it actively and interactively, with the implicit message that all courses should be updated and improved to a modern ornament that suits the learner's psychology, inclinations, and possibilities. It also meets the…
Descriptors: Second Language Learning, Second Language Instruction, Electronic Learning, Teaching Methods
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