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Reham Adel Ali; Mohamed Soliman; Muhammad Roflee Weahama; Muhammadafeefee Assalihee; Imran Mahmud – Smart Learning Environments, 2025
The current study explores metaverse adoption among higher education institutions (HEIs) in the light of a theoretical framework to empower future perspectives of the metaverse as a learning platform. Even though this technology was just recently introduced to the higher education sector, very few attempts have been made to evaluate its impact.…
Descriptors: Technology Uses in Education, College Students, Student Attitudes, Private Colleges
Pellas, Nikolaos – Smart Learning Environments, 2023
Artificial Intelligence (AI) and Machine Learning (ML) technologies offer the potential to support digital content creation and media production, providing opportunities for individuals from diverse sociodemographic backgrounds to engage in creative activities and enhance their multimedia video content. However, less attention has been paid to…
Descriptors: Artificial Intelligence, Video Technology, Creative Activities, Undergraduate Students
Saja Wardat; Mohammed Akour – Smart Learning Environments, 2024
This research explores the key motivating factors that influence student engagement with wearable technology (WT) in teaching English to speakers of other languages (TESOL) education. The study employs a novel, integrated framework that merges elements from the established technology acceptance model (TAM), Flow Theory, and additional factors…
Descriptors: Technology Uses in Education, English (Second Language), Second Language Instruction, Educational Technology
Masoumeh Bagheri-Nesami; Mahsa Kamali; Amirabbas Mollaei – Smart Learning Environments, 2025
Nurses acknowledge that their understanding of the shortcomings in the utilization of medical devices stems from insufficient knowledge about their correct usage. The use of Quick Response (QR) technology has paved a new gateway for accessing information and resources. The available evidence confirmed the usefulness of QR codes for use in clinical…
Descriptors: Medical Services, Handheld Devices, Knowledge Level, Clinical Experience
Amir Reza Rahimi; Zahra Mosalli – Smart Learning Environments, 2025
Researchers have significantly explored language learners' attitudes toward ChatGPT through the lens of technology acceptance models, particularly with its development and integration into computer-assisted language learning (CALL). However, further research in this area is necessary to apply a theoretical framework with a pedagogical-oriented…
Descriptors: Second Language Learning, Second Language Instruction, Artificial Intelligence, Technology Uses in Education
An Expectancy Value Theory (EVT) Based Instrument for Measuring Student Perceptions of Generative AI
Chan, Cecilia Ka Yuk; Zhou, Wenxin – Smart Learning Environments, 2023
This study examines the relationship between student perceptions and their intention to use generative artificial intelligence (GenAI) in higher education. With a sample of 405 students participating in the study, their knowledge, perceived value, and perceived cost of using the technology were measured by an Expectancy-Value Theory (EVT)…
Descriptors: Student Attitudes, College Students, Artificial Intelligence, Technology Uses in Education
Michal Vorlicek; David Prycl; Josef Heidler; Manuel Herrador-Colmenero; Jitka Nabelkova; Josef Mitas; Erica Hinckson; Sandra Mandic; Karel Frömel – Smart Learning Environments, 2024
This study addresses the issue of insufficient physical activity (PA) among youths. The emergence of gamified interventions, such as Gamifiter web portal, offers a novel approach to promoting healthy habits and increasing intrinsic motivation for PA. Gamifiter engages users in virtual challenges linked to daily step counts and progress on a…
Descriptors: Parents, Middle School Students, Grade 7, Foreign Countries
Agbo, Friday Joseph; Olaleye, Sunday Adewale; Bower, Matt; Oyelere, Solomon Sunday – Smart Learning Environments, 2023
Researchers are increasingly exploring educational games in immersive virtual reality (IVR) environments to facilitate students' learning experiences. Mainly, the effect of IVR on learning outcomes has been the focus. However, far too little attention has been paid to the influence of game elements and IVR features on learners' perceived…
Descriptors: Student Attitudes, Technology Uses in Education, Cognitive Processes, Teaching Methods
Chan, Yuet Kai; Oh, Jae-Eun; Ma, Henry – Smart Learning Environments, 2023
This study explores the use of open educational resources (OERs) in studio-based learning and their influence on learning experiences. The research team conducted action research with 30 bachelor of arts students who were completing a video production subject. Students were required to learn from a website containing open online learning resources…
Descriptors: Open Educational Resources, Flipped Classroom, Action Research, Video Technology
Chan, Cecilia Ka Yuk; Lee, Katherine K. W. – Smart Learning Environments, 2023
This study aimed to explore the experiences, perceptions, knowledge, concerns, and intentions of Generation Z (Gen Z) students with Generation X (Gen X) and Generation Y (Gen Y) teachers regarding the use of generative AI (GenAI) in higher education. A sample of students and teachers were recruited to investigate the above using a survey…
Descriptors: Age Groups, Generational Differences, Artificial Intelligence, College Faculty
Sage, Kara; Jackson, Sophia; Fox, Emily; Mauer, Larissa – Smart Learning Environments, 2021
The COVID-19 pandemic caused many colleges to quickly shift to virtual learning, leading students to rely on technology to complete coursework while also experiencing new situations and stressors. The present study explored students' technology use in their online course in conjunction with several student outcomes and individual difference…
Descriptors: COVID-19, Pandemics, School Closing, Online Courses
Oliveira, David Manuel Duarte; Pedro, Luís; Santos, Carlos – Smart Learning Environments, 2021
This paper was developed within the scope of a PhD thesis that intends to characterize the use of mobile applications by the students of the University of Aveiro during class time. The main purpose of this paper is to present the results of an initial pilot study that aimed to fine-tune data collection methods in order to gather data that…
Descriptors: Telecommunications, Higher Education, Pilot Projects, Handheld Devices
Luo, Yan; Du, Huan – Smart Learning Environments, 2022
With advantages such as ease of use and low cost, desktop virtual reality (VR) technologies are increasingly being used in practical learning. This study aims to clarify the relationship among students' self-efficacy, goal orientation, technology acceptance [e.g., perceived usefulness (PU) and perceived ease of use (PEOU)] and learning behavior,…
Descriptors: Electronic Learning, Computer Simulation, Self Efficacy, Goal Orientation
Segbenya, Moses; Bervell, Brandford; Minadzi, Vincent Mensah; Somuah, Beatrice Asante – Smart Learning Environments, 2022
This study examined perspectives of distance education students on online learning based on their access gadgets (availability and functionality), online presentation or teaching methods, actual use of online learning coupled with its challenges. A quantitative approach and descriptive survey design were adopted for the study. A sample of 1061 was…
Descriptors: Distance Education, Online Courses, COVID-19, Pandemics
Maria Efstratopoulou; Maxwell Peprah Opoku; Aizhan Shomotova; Christina Davison; Abdulrafi Jaffarul; Aalya Mesmar – Smart Learning Environments, 2024
A smart learning environment (SLE) encompasses the use of advanced technology and smart pedagogical teaching skills tailored to suit students with diverse learning needs. In recent years, some countries, such as the United Arab Emirates (UAE), have formulated policies to implement SLE in their education systems. Since students are the intended…
Descriptors: Foreign Countries, Secondary School Students, Grade 7, Grade 12
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