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Mia Carapina; Klaudio Pap – International Association for Development of the Information Society, 2024
This paper introduces CoCo, a system designed to support and encourage collaborative learning among colocated students sharing a single mobile device. It provides teachers with the possibility to create digital lessons, configure parameters for collaborative activities such as the number of students and tablets, and monitor students' progress. On…
Descriptors: Cooperative Learning, Handheld Devices, Teaching Methods, Learning Management Systems
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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
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Cheng, Ching-I. – Journal of Computer Assisted Learning, 2023
Background: Taiwan's higher education institutions prioritize interdisciplinary knowledge and cultural competence in cultural design, emphasizing the value of immersion in the local environment to develop cultural competence. However, challenges arise from the disappearance of traditional local lifestyles and limitations of traditional outdoor…
Descriptors: Foreign Countries, Learning Analytics, Handheld Devices, Computer Oriented Programs
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Piet Kommers Ed.; Inmaculada Arnedillo Sánchez Ed.; Pedro Isaías Ed. – International Association for Development of the Information Society, 2023
These proceedings contain the papers and posters of the 21st International Conference on e-Society (ES 2023) and 19th International Conference on Mobile Learning (ML 2023), organised by the International Association for Development of the Information Society (IADIS) in Lisbon, Portugal, during March 11-13, 2023. The e-Society 2023 conference aims…
Descriptors: Electronic Learning, Educational Technology, Telecommunications, Handheld Devices
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Akturk, Ahmet Oguz – Journal of Computer Assisted Learning, 2022
Background: "Journal of Computer Assisted Learning" ("JCAL"), which started its publication life in 1985, is a leading international journal in the field of computer and instructional technologies and celebrated its 35th anniversary in 2020. Objectives: This study aims to provide a bibliometric overview of leading publication…
Descriptors: Periodicals, Bibliometrics, Citations (References), Educational Technology
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Sher, Varshita; Hatala, Marek; Gaševic, Dragan – Journal of Learning Analytics, 2022
Recent advances in smart devices and online technologies have facilitated the emergence of ubiquitous learning environments for participating in different learning activities. This poses an interesting question about modality access, i.e., what students are using each platform for and at what time of day. In this paper, we present a log-based…
Descriptors: Time Factors (Learning), Use Studies, Learning Management Systems, Handheld Devices
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Jiang, Shiyan; Huang, Xudong; Sung, Shannon H.; Xie, Charles – Research in Science Education, 2023
Learning analytics, referring to the measurement, collection, analysis, and reporting of data about learners and their contexts in order to optimize learning and the environments in which it occurs, is proving to be a powerful approach for understanding and improving science learning. However, few studies focused on leveraging learning analytics…
Descriptors: Learning Analytics, Hands on Science, Science Education, Laboratory Safety
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Silvia García-Méndez; Francisco de Arriba-Pérez; Francisco J. González-Castaño – International Association for Development of the Information Society, 2023
Mobile learning or mLearning has become an essential tool in many fields in this digital era, among the ones educational training deserves special attention, that is, applied to both basic and higher education towards active, flexible, effective high-quality and continuous learning. However, despite the advances in Natural Language Processing…
Descriptors: Higher Education, Artificial Intelligence, Computer Software, Usability
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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
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Kay, Ellie; Bostock, Paul – Student Success, 2023
Providing timely nudges to students has been shown to improve engagement and persistence in tertiary education. However, many studies focus on small-scale pilots rather than institution-wide initiatives. This article assesses the impact of a pan-institution Early Alert System at the University of Canterbury that utilises nudging when students are…
Descriptors: At Risk Students, Learner Engagement, Undergraduate Students, Handheld Devices
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Pishtari, Gerti; Prieto, Luis P.; Rodriguez-Triana, Maria Jesus; Martinez-Maldonado, Roberto – Journal of Learning Analytics, 2022
This research was triggered by the identified need in literature for large-scale studies about the kinds of designs that teachers create for mobile learning (m-learning). These studies require analyses of large datasets of learning designs. The common approach followed by researchers when analyzing designs has been to manually classify them…
Descriptors: Scaling, Classification, Context Effect, Telecommunications
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Viberg, Olga; Kukulska-Hulme, Agnes; Peeters, Ward – International Journal of Mobile and Blended Learning, 2023
Mobile-assisted language learning (MALL) research includes examination and development of second language learners' cognitive and metacognitive self-regulated learning skills, but the affective learning component of self-regulation in this context remains largely unexplored. Support for affective learning, which is defined by learners' beliefs,…
Descriptors: Metacognition, Computer Assisted Instruction, Second Language Learning, Second Language Instruction
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Cheng, Ching-Hsue; Chen, Chung-Hsi – Computer Assisted Language Learning, 2022
Many scholars have highlighted the importance of motivation and anxiety in language learning. They have also indicated the advantages of integrating learning content into a mobile-assisted English learning system environment. Meanwhile, a few studies have explored the impacts of a mobile-assisted English learning system on the motivation and…
Descriptors: Second Language Learning, Second Language Instruction, English (Second Language), Student Attitudes
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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)
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Santiago Berrezueta Ed. – Lecture Notes in Educational Technology, 2023
The proceedings of the 18th edition of Latin American Conference on Learning Technologies (LACLO) demonstrates the developments in the research of learning science, learning resources, challenges and solutions. This Proceedings book showcases a collection of quality articles that explores and discusses trending topics in education in the upcoming…
Descriptors: Educational Technology, Active Learning, Design, Telecommunications
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