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Hatice Yildiz Durak – Education and Information Technologies, 2025
Feedback is critical in providing personalized information about educational processes and supporting their performance in online collaborative learning environments. However, giving effective feedback and monitoring its effects, which is especially important in online environments, is a complex issue. Although providing feedback by analyzing…
Descriptors: Feedback (Response), Online Systems, Electronic Learning, Learning Analytics
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Zheng, Lanqin; Zhong, Lu; Fan, Yunchao – Education and Information Technologies, 2023
Online collaborative learning (OCL) has been a mainstream pedagogy in the field of higher education. However, learners often produce off-topic information and engage less during online collaborative learning compared to other approaches. In addition, learners often cannot converge in knowledge, and they often do not know how to coregulate with…
Descriptors: Electronic Learning, Cooperative Learning, Undergraduate Students, Learning Analytics
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Muhittin Sahin – Interactive Learning Environments, 2024
Learning analytics aims to improve learning and teaching in digital learning environments by optimizing them. Real-time feedback, suggestions, directions, and interventions are structured in the digital learning environments. In order to structure more effective interventions, it is crucial to ascertain which of these services offered to students…
Descriptors: Learning Analytics, Intervention, Student Attitudes, Preferences
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Lu, Chang; Cutumisu, Maria – International Journal of Educational Technology in Higher Education, 2022
In traditional school-based learning, attendance was regarded as a proxy for engagement and key indicator for performance. However, few studies have explored the effect of in-class attendance in technology-enhanced courses that are increasingly provided by secondary institutions. This study collected n = 367 undergraduate students' log files from…
Descriptors: Learner Engagement, Academic Achievement, Formative Evaluation, Attendance Patterns
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Lee, Hakeoung Hannah; Gargroetzi, Emma C. – Journal of Learning Analytics, 2023
Data-driven learning analytics (LA) exploits artificial intelligence, data-mining, and emerging technologies, rapidly expanding the collection and uses of learner data. Considerations of potential harm and ethical implications have not kept pace, raising concerns about ethical and privacy issues (Holstein & Doroudi, 2019; Prinsloo & Slade,…
Descriptors: Learning Analytics, Mentors, Ethics, Responsibility
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Kew, Si Na; Tasir, Zaidatun – Education and Information Technologies, 2022
The emergence of Learning Analytics has brought benefits to the educational field, as it can be used to analyse authentic data from students to identify the problems encountered in e-learning and to provide intervention to assist students. However, much is still unknown about the development of Learning Analytics intervention in terms of providing…
Descriptors: Learning Analytics, Intervention, Electronic Learning, Educational Technology
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Yang, Christopher C. Y.; Ogata, Hiroaki – Educational Technology & Society, 2023
Blended learning (BL) is regarded as an effective strategy for combining traditional face-to-face classroom activities with various types of online learning tools (e.g., e-books). An effective feature of e-books is the ability to use digital notes. When e-books are used in BL, the strategic adoption of note-taking provides benefits that influence…
Descriptors: Blended Learning, Sequential Approach, Notetaking, Electronic Publishing
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Yang, Christopher C. Y.; Chen, Irene Y. L.; Ogata, Hiroaki – Educational Technology & Society, 2021
Precision education is now recognized as a new challenge of applying artificial intelligence, machine learning, and learning analytics to improve both learning performance and teaching quality. To promote precision education, digital learning platforms have been widely used to collect educational records of students' behavior, performance, and…
Descriptors: Learning Analytics, Individualized Instruction, Instructional Materials, Books
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Richard M. Baylis; Malcolm J. Beynon – Accounting Education, 2024
Lecture Capture (LC) material is accepted to be an available and accessible resource for students in universities across the world. This exploratory study investigates the "when viewing" LC material engagement of accounting undergraduate students. Three categories of engagement are defined, Near-Event-Viewing (NEV), Get-Round-to-Viewing…
Descriptors: Accounting, Lecture Method, Teaching Methods, Undergraduate Students
González, Carlos; López, Dany; Calle-Arango, Lina; Montenegro, Helena; Clasing, Paula – ECNU Review of Education, 2022
Purpose: This study aims to explore Chilean students' digital technology usage patterns and approaches to learning. Design/Approach/Methods: We conducted this study in two stages. We worked with one semester learning management systems (LMS), library, and students' records data in the first one. We performed a k-means cluster analysis to identify…
Descriptors: Foreign Countries, Electronic Learning, Technology Uses in Education, Use Studies
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Amy Goodman; Youngjin Lee; Willard Elieson; Gerald Knezek – Journal of Computers in Mathematics and Science Teaching, 2023
Virtual learning environments give students more autonomy over their learning than traditional face-to-face classes and require that students adapt the ways they consume and assimilate new information. One theory of this process is self-regulated learning, which is illustrated in Efklides' Metacognitive and Affective model of Self-Regulated…
Descriptors: Self Management, Learning Theories, Learning Analytics, Undergraduate Students
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Pozdeeva, Elena; Shipunova, Olga; Popova, Nina; Evseev, Vladimir; Evseeva, Lidiya; Romanenko, Inna; Mureyko, Larisa – Education Sciences, 2021
The article is devoted to learning analytics problems associated with the digital culture development in the university educational space and with the student activity control in the vocational training process. The empirical basis of the study was a series of surveys conducted by the Center for Sociological Research of the Peter the Great…
Descriptors: Learning Analytics, Higher Education, Electronic Learning, Foreign Countries
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Zheng, Lanqin; Zhong, Lu; Niu, Jiayu – Assessment & Evaluation in Higher Education, 2022
Learning analytics has been widely used in the field of education. Most studies have adopted a learning analytics dashboard to present data on learning processes or learning outcomes. However, only presenting learning analytics results was not sufficient and lacked personalised feedback. In response to these gaps, this study proposed a learning…
Descriptors: Electronic Learning, Cooperative Learning, Undergraduate Students, Feedback (Response)
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Danielle S. McNamara; Tracy Arner; Elizabeth Reilley; Paul Alvarado; Chani Clark; Thomas Fikes; Annie Hale; Betheny Weigele – Grantee Submission, 2022
Accounting for complex interactions between contextual variables and learners' individual differences in aptitudes and background requires building the means to connect and access learner data at large scales, across time, and in multiple contexts. This paper describes the ASU Learning@Scale (L@S) project to develop a digital learning network…
Descriptors: Electronic Learning, Educational Technology, Networks, Learning Analytics
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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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