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Kumar, Bimal Aklesh; Goundar, Munil Shiva – Education and Information Technologies, 2023
Mobile language learning (MLL) is an emerging field of research, and many MLL applications have been developed over the years. In this paper, a systematic literature review (SLR) was conducted to establish a body of knowledge on the development of MLL applications. The SLR analyzed forty seven papers from seven different digital libraries…
Descriptors: Second Language Learning, Second Language Instruction, Telecommunications, Handheld Devices
Sukavatee, Pornpimol; Khlaisang, Jintavee – rEFLections, 2023
One of the greatest advantages of mobile language learning is its ease of access, especially to learners in the 21st century who have the option of selecting any learning content that matches their preferences or language development goals, anywhere and at any time. Mobile-assisted language learning or MALL takes learning beyond the classroom,…
Descriptors: Second Language Learning, Second Language Instruction, Computer Assisted Instruction, Handheld Devices
Iskrenovic-Momcilovic, Olivera – Interactive Learning Environments, 2023
The aim of the research is to examine the contribution of mobile application using in botanical fieldwork to the quality and durability of knowledge of the subject Nature and society compared to multimedia teaching in the fourth grade of primary school. The study involved 120 students, divided into two groups: control group, which taught on the…
Descriptors: Elementary School Students, Control Groups, Grade 4, Handheld Devices
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
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
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
Bin Zou; Qinglang Lyu; Yining Han; Zijing Li; Weilei Zhang – Computer Assisted Language Learning, 2025
Adapted from the Technology Acceptance Model (TAM), the Integrated Model of Technology Acceptance (IMTA) has been used to examine the perceptions and acceptance of computer-assisted language learning (CALL), such as online learning, mobile learning, and learning management systems. However, whether IMTA can be applied to empirical research on…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Artificial Intelligence
Li, Yuhao; Chang, Mengyi; Zhao, Hanxuan; Jiang, Caihong; Xu, Sihua – Journal of Computer Assisted Learning, 2023
Background: Mobile devices facilitate learning activities in a self-paced way. However, the current understanding of learning participation and its consequence are minimal when learners take advantage of opportunities provided by mobile technologies worldwide. Aims: The primary purpose of this study is to examine the effectiveness of environmental…
Descriptors: Anxiety, Computer Software, Computer Assisted Instruction, Learning Processes
Romadiah, Hikmah; Dayurni, Popi; Fajari, Laksmi Evasufi Widi – Online Submission, 2022
This research is motivated by the increasing number of users of android-based learning media it impacts the learning outcomes obtained. This study aims to determine the effect of android-based learning media on improving student learning outcomes. This research is a meta-analysis study. Data collection techniques are taken from indexing databases…
Descriptors: Meta Analysis, Handheld Devices, Telecommunications, Computer Assisted Instruction
Barghamadi, Maryam; Rogers, James; Muller, Amanda – Australian Journal of Applied Linguistics, 2022
Knowledge of multi-word units (MWUs) helps facilitate communicative fluency, and research on them has gained more and more attention in recent years concerning teaching methods and designing materials for second language (L2) acquisition. Incidental and intentional vocabulary learning are two dominant approaches to acquiring MWUs. In lexical…
Descriptors: Instructional Materials, Phrase Structure, Vocabulary Development, Teaching Methods
Hsu, Hui-Tzu; Lin, Chih-Cheng – Educational Technology & Society, 2022
Mobile technology is regarded as a helpful tool facilitating language learning. However, the success of mobile technology largely depends on learners' acceptance. This study explored the factors that may affect students' intention formation regarding mobile-assisted language learning (MALL) in the context of higher education through the lens of…
Descriptors: Computer Assisted Instruction, Telecommunications, Handheld Devices, Teaching Styles
Panagiotis Arvanitis; Penelope Krystalli – European Journal of Education (EJED), 2021
Throughout the decade of 2010-2020, the widespread use of mobile devices of any type (smartphones, tablets) has encouraged and strengthened their use in different learning processes and in different ways. Latest improvements in devices' processing power, in storage capacity, in memory allocation, in wireless connectivity, in GPS and in Bluetooth…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Telecommunications
Himel Mondal; Juhu Kiran Krushna Karri; Swaminathan Ramasubramanian; Shaikat Mondal; Ayesha Juhi; Pratima Gupta – Advances in Physiology Education, 2025
Large language models (LLMs)-based chatbots use natural language processing and are a type of generative artificial intelligence (AI) that is capable of comprehending user input and generating output in various formats. They offer potential benefits in medical education. This study explored the student's feedback on the utilization of LLMs in…
Descriptors: Computational Linguistics, Physiology, Teaching Methods, Artificial Intelligence
Smith, Bryan; González-Lloret, Marta – Language Teaching, 2021
This paper discusses key concepts in the emerging field of technology-mediated task-based language teaching (TMTBLT) and provides a research agenda for moving this sub-field forward in a theoretically sound and data-driven way. We first define TMTBLT and discuss the importance of considering technological affordances and specific learning contexts…
Descriptors: Task Analysis, Second Language Learning, Second Language Instruction, Teaching Methods
Younmi Jeon – ProQuest LLC, 2023
A number of studies in mobile learning research have shown that the use of computer-assisted language learning (CALL) and many different types of technology within language learning contexts can potentially influence learning of students, particularly the younger generation. In the current study, two participant groups -- EFL teachers and parents…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Computer Assisted Instruction

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