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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
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
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
Abdullah, Siti Intan Nurdiana Wong; Arokiyasamy, Klara; Goh, Sock Leng; Culas, Andrea Joveena; Manaf, Nor Masheera Abdul – Smart Learning Environments, 2022
Technology has enabled the higher education ecosystem to tailor to the students who have diverse needs and to engage with them remotely, especially when face-to-face interaction is not possible. This research contributes knowledge in forced remote learning during the unprecedented global pandemic situation of COVID-19. Using a cross-sectional…
Descriptors: Student Satisfaction, COVID-19, Pandemics, College Students
Yiannis Koumpouros – Smart Learning Environments, 2024
Augmented Reality (AR) technology is one of the latest developments and is receiving ever-increasing attention. Many researches are conducted on an international scale in order to study the effectiveness of its use in education. The purpose of this work was to record the characteristics of AR applications, in order to determine the extent to which…
Descriptors: Computer Simulation, Educational Technology, College Students, Computer Oriented Programs
Alvi, Irum – Smart Learning Environments, 2021
The term Social Networking Tools is used for social media applications accessible via mobile devices/smartphones; their use has become ubiquitous among college students, especially after the COVID 19 Pandemic, due to which the institutes of Higher education were shut down. A research gap was identified as the students' acceptance of these learning…
Descriptors: Foreign Countries, Social Media, Telecommunications, Handheld Devices
Competency Levels and Influential Factors of College Students' Mobile Learning Readiness in Thailand
Diteeyont, Watsatree; Heng-Yu, Ku – Smart Learning Environments, 2023
One of the key successes of learning through mobile technology comes from the competencies of learners. This study aimed to investigate the overall competency levels of mobile learning readiness and four influential factors (connectivist learners, technology readiness, self-directed learning, and netiquette) that may impact college students'…
Descriptors: Telecommunications, Handheld Devices, Educational Technology, Readiness
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
John Kwame Eduafo Edumadze; Desmond Welsey Govender – Smart Learning Environments, 2024
While massive open online courses (MOOCs) promise to democratise access to education, the literature reveals a nuanced understanding of engagement in these settings, especially in resource-constrained environments. Blended MOOCs combine MOOCs and physical classroom settings of contents and instructions. This study extends this discourse by…
Descriptors: MOOCs, Educational Technology, In Person Learning, Blended Learning
Portugal, David; Faria, José N.; Belk, Marios; Martins, Pedro; Constantinides, Argyris; Pietron, Anna; Pitsillides, Andreas; Avouris, Nikolaos; Fidas, Christos A. – Smart Learning Environments, 2023
The worldwide shift to distance learning at Higher Education Institutions (HEIs) during the COVID-19 global pandemic has raised several concerns about the credibility of online academic activities, especially regarding student identity management. Traditional online frameworks cannot guarantee the authenticity of the enrolled student, which…
Descriptors: Identification, Distance Education, College Students, COVID-19
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
Gurjinder Singh; Faizan Ahmad – Smart Learning Environments, 2024
Augmented reality (AR) stands as a widely embraced technology that significantly enhances learning experiences for students. AR offers an instructional approach supported by technological design, thereby fostering enriched learning interactions. This research proposes an interactive AR framework, intended to create an augmented reality learning…
Descriptors: Electronics, Engineering Education, College Students, Computer Simulation
Federico De Lorenzis; Alessandro Visconti; Simone Restivo; Francesca Mazzini; Serena Esposito; Silvia Fraterrigo Garofalo; Luca Marmo; Debora Fino; Fabrizio Lamberti – Smart Learning Environments, 2024
The use of Virtual Reality (VR) in education is getting more and more common, especially when hands-on learning experiences have to be delivered. With VR it becomes possible, e.g., to simulate dangerous or costly procedures that could hardly be implemented in real settings. However, engaging large classes in immersive laboratory activities may be…
Descriptors: Computer Simulation, Cooperative Learning, Chemistry, Science Education
Kaplan-Rakowski, Regina; Johnson, Karen R.; Wojdynski, Tomasz – Smart Learning Environments, 2021
Advocates of meditation claim that it can improve various aspects of life, including health, attention, thinking, and learning. The purpose of this empirical, quantitative, between-subject study was twofold. First, it compared the effectiveness of meditation delivered through virtual reality versus video, as measured by students' test scores.…
Descriptors: College Students, Computer Simulation, Relaxation Training, Metacognition
Elvira G. Rincon-Flores; Leticia Castano; Sadie Lissette Guerrero Solis; Omar Olmos Lopez; Carlos Felipe Rodríguez Hernández; Laura Angélica Castillo Lara; Laura Patricia Aldape Valdés – Smart Learning Environments, 2024
Much has been written about Adaptive Learning, but does its implementation alone guarantee success? We have found that integrating an Adaptive Learning Strategy with diverse didactic techniques gives better results. The objectives of this exploratory study were to know the impact of the Adaptive Learning Strategy on students' learning and…
Descriptors: Learning Strategies, Academic Achievement, Computation, Thinking Skills
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