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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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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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Atasoy, Eda; Bozna, Harun; Sönmez, Abdulvahap; Aydin Akkurt, Ayse; Tuna Büyükköse, Gamze; Firat, Mehmet – Asian Association of Open Universities Journal, 2020
Purpose: This study aims to investigate the futuristic visions of PhD students at Distance Education department of Anadolu University on the use of learning analytics (LA) and mobile technologies together. Design/methodology/approach: This qualitative research study, designed in the single cross-section model, aimed to reveal futuristic visions of…
Descriptors: Active Learning, Learning Analytics, Handheld Devices, Student Attitudes
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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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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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Mella-Norambuena, Javier; Cobo-Rendon, Rubia; Lobos, Karla; Sáez-Delgado, Fabiola; Maldonado-Trapp, Alejandra – Education Sciences, 2021
Due to the COVID-19 pandemic, students worldwide have continued their education remotely. One of the challenges of this modality is that students need access to devices such as laptops and smartphones. Among these options, smartphones are the most accessible because of their lower price. This study analyzes the usage patterns of smartphone users…
Descriptors: Telecommunications, Handheld Devices, Undergraduate Students, STEM Education
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Kim, Byungsoo; Yu, Hangyeol; Shin, Dongmin; Choi, Youngduck – International Educational Data Mining Society, 2021
The needs for precisely estimating a student's academic performance have been emphasized with an increasing amount of attention paid to Intelligent Tutoring System (ITS). However, since labels for academic performance, such as test scores, are collected from outside of ITS, obtaining the labels is costly, leading to label-scarcity problem which…
Descriptors: Academic Achievement, Intelligent Tutoring Systems, Prediction, Scores
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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)
René F. Kizilcec; Maximilian Chen; Kaja K. Jasinska; Michael Madaio; Amy Ogan – Grantee Submission, 2021
School closures due to teacher strikes or political unrest in low-resource contexts can adversely affect children's educational outcomes and career opportunities. Phone-based educational technologies could help bridge these gaps in formal schooling, but it is unclear whether or how children and their families will use such systems during periods…
Descriptors: Electronic Learning, Handheld Devices, Telecommunications, Educational Technology
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René F. Kizilcec; Maximillian Chen; Kaja K. Jasinska; Michael Madaio; Amy Ogan – AERA Open, 2021
School closures due to teacher strikes or political unrest in low-resource contexts can adversely affect children's educational outcomes and career opportunities. Phone-based educational technologies could help bridge these gaps in formal schooling, but it is unclear whether or how children and their families will use such systems during periods…
Descriptors: Electronic Learning, Handheld Devices, Telecommunications, Educational Technology
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Hwang, Wu-Yuin; Utami, Ika Qutsiati; Purba, Siska Wati Dewi; Chen, Holly S. L. – IEEE Transactions on Learning Technologies, 2020
This paper aimed to investigate the effect of a mobile app on mathematics learning in authentic contexts. Authentic contexts contain rich resources wherein students can use authentic objects as aid in advanced educational technology-assisted mathematics learning. We designed Ubiquitous-Fraction (U-Fraction), a mobile application that helps…
Descriptors: Instructional Effectiveness, Mathematics Instruction, Mathematics Achievement, Web Based Instruction
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West, Deborah; Luzeckyj, Ann; Searle, Bill; Toohey, Danny; Vanderlelie, Jessica; Bell, Kevin R. – Australasian Journal of Educational Technology, 2020
This article reports on a study exploring student perspectives on the collection and use of student data for learning analytics. With data collected via a mixed methods approach from 2,051 students across six Australian universities, it provides critical insights from students as a key stakeholder group. Findings indicate that while students are…
Descriptors: Stakeholders, Undergraduate Students, Graduate Students, Student Attitudes
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Sugden, Nicole; Brunton, Robyn; MacDonald, Jasmine; Yeo, Michelle; Hicks, Ben – Australasian Journal of Educational Technology, 2021
There is growing demand for online learning activities that offer flexibility for students to study anywhere, anytime, as online students fit study around work and family commitments. We designed a series of online activities and evaluated how, where, and with what devices students used the activities, as well as their levels of engagement and…
Descriptors: Learning Activities, Learner Engagement, Online Courses, Handheld Devices
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