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Kanwal Zahoor; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Courseware, Learning Processes
Hendra Hidayat; Dani Harmanto; Mohd Rizal Mohd Isa; Jem Cloyd M. Tanucan; Ahmad Istiqlal Ahlunnazak; Ifdil Ifdil; Zadrian Ardi – Journal of Social Studies Education Research, 2024
This study explores eight key themes: Self-control, personalized learning, smartphone habits, future-time perspective, information overload, digital literacy, meaningful learning, and metacognitive awareness. The primary objective is to investigate the correlations among these factors. Virtual presence serves as a moderating variable, influencing…
Descriptors: Metacognition, Engineering Education, Learning Processes, Telecommunications
Marilyn Campbell; Elizabeth J. Edwards; Donna Pennell; Shiralee Poed; Victoria Lister; Jenna Gillett-Swan; Adrian Kelly; Dajana Zec; Thuy-Anh Nguyen – Journal of Psychologists and Counsellors in Schools, 2024
Public opinions are divided on the relative benefits versus harms of allowing mobile phones in schools. When debating the consequences of mobile phones in schools, politicians often argue that students' use of mobile phones distract from their learning, increase cyberbullying and lead to poor mental health outcomes. We conducted a scoping review…
Descriptors: Telecommunications, Handheld Devices, School Policy, Student Rights
Mohammed A. E. Suliman; Wenlan Zhang; Rehab A. I. Suluman; Kamal Abubker Abrahim Sleiman – Education and Information Technologies, 2025
This study contributes to the knowledge about mobile learning among medical students in the context of developing countries. This research used the Technology Acceptance Model (TAM) to study the preconditions for m-learning among medical students. A twenty-item self-reported survey was used to gather data from 387 medical students, and structural…
Descriptors: Medical Students, Student Attitudes, Information Technology, Technology Integration
Suzannie K. Y. Leung; Kimburley W. Y. Choi – European Early Childhood Education Research Journal, 2024
This study aimed at exploring kindergarten teachers' perceptions and usage of digital devices in their classrooms. A multiple case study (n = 4) was conducted to investigate how in-service experienced (n = 22) and novice (n = 24) kindergarten teachers interpreted the functional significance of digital devices, including the needs and challenges…
Descriptors: Visual Arts, Art Education, Films, Teacher Attitudes
Liangyong Xue; Abdullah Mat Rashid; Sha Ouyang – SAGE Open, 2024
This systematic review evaluates the application of the Unified Theory of Acceptance and Use of Technology (UTAUT) model in higher education, analyzing 162 SSCI/SCI-E articles from 2008 to 2022. It reveals a predominant focus on student participants from Asia and North America. Mobile learning tools are the most studied technologies. Surveys…
Descriptors: Research Reports, Technology Uses in Education, Structural Equation Models, Foreign Countries
Isaac Lozano-Osorio; Sonia Ruiz-Olmedilla; Diana Perez-Marin; Maximiliano Paredes-Velasco – IEEE Transactions on Education, 2024
Contribution: A methodology based on the learning by teaching approach facilitated by a mobile learning tool for creating tutorials. A study of the impact this methodology has had on the emotional well-being of students and its correlation with academic performance has also been carried out. Background: Insufficient resources and the absence of…
Descriptors: Tutorial Programs, Vocational Education, Learning Processes, Outcomes of Education
Julia Milner; Sharleen L. O'Reilly – Innovations in Education and Teaching International, 2025
We explored the usage of smartphones in university classrooms across three different countries from the instructor's perspective. Using a qualitative, cross-cultural approach, we interviewed 30 instructors via semi-structured interviews to understand their viewpoints and experience with student smartphone usage in class. Instructors reported…
Descriptors: Teacher Attitudes, Critical Thinking, Telecommunications, Handheld Devices
Adnan Shehadeh – Anatolian Journal of Education, 2024
This study aimed to investigate students' reflections on using smartphones to enhance vocabulary learning. The sample consisted of 64 college students enrolled in required English as a Foreign Language (EFL) reading course. A twenty-two-item questionnaire was developed to elicit students' reflections on their experiences in terms of three aspects;…
Descriptors: Telecommunications, Handheld Devices, English (Second Language), Second Language Instruction
Wahyu Dilla Abdullah; Adilah Afikah; Ezi Apino; Supahar Supahar; Jumadi Jumadi – Journal of Baltic Science Education, 2024
The use of mobile technology in physics education has become more prevalent, but more data about its effect on student academic performance needs to be collected. This meta-analysis examines the effects of mobile learning on student achievement in physics and any moderating factors. The study collected 36 primary studies from various scientific…
Descriptors: Meta Analysis, Science Education, Science Achievement, Physics
Mubarak M. Aldawsari; Abdullah D. Alenezi; John I. Liontas – Reading Matrix: An International Online Journal, 2025
Artificial Intelligence (AI) has rapidly become a pivotal force in education, offering personalized learning pathways and dynamic solutions to longstanding instructional challenges. In English as a Foreign Language (EFL) contexts, idiomatic competence remains a challenging aspect of language development, often eluding effective coverage through…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Technology Integration
Fatimah H. Aldeeb; Omar M. Sallabi; Monther M. Elaish; Gwo-Jen Hwang – Journal of Computer Assisted Learning, 2024
Background: This paper examines the use of augmented reality (AR) as a concept-association tool in schools, with the aim of enhancing primary school students' learning outcomes and engagement. Conflicting findings exist in previous studies regarding the cognitive load of AR-enriched learning, with some reporting reduced load and others indicating…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
Agnes Kukulska-Hulme; Tom Power; Saraswati Dawadi; S. M. Hafizur Rahman; Tauhida Parvin – Journal of Technology and Teacher Education, 2024
The paper presents findings from a research study of 318 mathematics teachers' experiences of access to, and use of, digital technology in their professional development in marginalised communities in ten districts across Bangladesh. The innovative two-cycle qualitative study design involved early career researchers collaborating with…
Descriptors: Faculty Development, Mathematics Teachers, Mathematics Instruction, Online Courses
Mai Thi Truc Le; Khue Van Tran – International Society for Technology, Education, and Science, 2024
Multitasking which has been reported to occur more frequently in online learning classes compared to traditional face-to-face settings has been found to have negative effects on students' learning. Albeit extensive research has been carried out on the effect of multitasking in education, there is scant research that sheds light on multitasking…
Descriptors: Foreign Countries, Educational Theories, Online Courses, Human Body
Claudia De Barros Camargo; Antonio Hernández Fernández – Educational Process: International Journal, 2024
Background/Purpose: This study investigates the integration of neuropedagogy, neuroimaging, artificial intelligence (AI), and deep learning in educational systems. The research aims to elucidate how these technologies can be synergistically applied to optimize learning processes based on individual neurocognitive profiles, thereby enhancing…
Descriptors: Artificial Intelligence, Educational Practices, Intelligent Tutoring Systems, Neurosciences
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