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Showing 46 to 60 of 305 results Save | Export
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David P. Reid; Timothy D. Drysdale – IEEE Transactions on Learning Technologies, 2024
The designs of many student-facing learning analytics (SFLA) dashboards are insufficiently informed by educational research and lack rigorous evaluation in authentic learning contexts, including during remote laboratory practical work. In this article, we present and evaluate an SFLA dashboard designed using the principles of formative assessment…
Descriptors: Learning Analytics, Laboratory Experiments, Electronic Learning, Feedback (Response)
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Tal Soffer; Anat Cohen – Australasian Journal of Educational Technology, 2024
The rapid recent use of learning analytics (LA) in higher education, specifically during the COVID-19 pandemic, allows the monitoring of users' behavior while learning. Using LA may promote students' learning outcomes but also intrude into their privacy. This study aimed to explore students' behaviour and perceptions towards privacy and data…
Descriptors: Privacy, Educational Practices, College Students, Student Attitudes
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Baker, Ryan S.; Nasiar, Nidhi; Gong, Weiyi; Porter, Chelsea – International Journal of STEM Education, 2022
Background: In recent years, research on online learning platforms has exploded in quantity. More and more researchers are using these platforms to conduct A/B tests on the impact of different designs, and multiple scientific communities have emerged around studying the big data becoming available from these platforms. However, it is not yet fully…
Descriptors: Learning Analytics, Electronic Learning, Educational Research, STEM Education
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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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Olga Agatova; Alexander Popov; Suad Abdalkareem Alwaely – Interactive Learning Environments, 2024
The paper examines the special aspects of using Big Data technology in education. The population was made up of 356 third-year university students. To study Big Data technology, a questionnaire was used where respondents rated: cloud technology; apps; Massive Open Online Courses (MOOCs) and digital learning platforms. The study suggested that the…
Descriptors: Data Use, Learning Processes, Technology Uses in Education, Information Storage
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Shihui Feng; David Gibson; Dragan Gaševic – Journal of Learning Analytics, 2025
Understanding students' emerging roles in computer-supported collaborative learning (CSCL) is critical for promoting regulated learning processes and supporting learning at both individual and group levels. However, it has been challenging to disentangle individual performance from group-based deliverables. This study introduces new learning…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Student Role, Learning Analytics
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Tamra Ross; Rachel Sondergaard; Cindy Ives; Andrew Han; Sabine Graf – Technology, Knowledge and Learning, 2025
To meet student demand for responsive, adaptable, and up-to-date online courses, educators and learning designers need tools to analyse student interactions with their peers, educators and learning resources. Learning Management Systems (LMSs) store large volumes of detailed user data, but offer only limited, pre-set reports and visualizations to…
Descriptors: Access to Information, Learning Analytics, Instructional Design, Evaluation Methods
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Xing, Wanli; Du, Dongping; Bakhshi, Ali; Chiu, Kuo-Chun; Du, Hanxiang – IEEE Transactions on Learning Technologies, 2021
Predictive modeling in online education is a popular topic in learning analytics research and practice. This study proposes a novel predictive modeling method to improve model transferability over time within the same course and across different courses. The research gaps addressed are limited evidence showing whether a predictive model built on…
Descriptors: Electronic Learning, Bayesian Statistics, Prediction, Models
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García-Tudela, Pedro Antonio; Prendes-Espinosa, Paz; Solano-Fernández, Isabel María – Smart Learning Environments, 2021
This paper is basic research focused on the analysis of scientific advances related to Smart Learning Environments (SLE). Our main objective is to single out the common aspects to propose a new definition which will constitute the starting point to design an innovative model which we can apply to the analysis of real cases and good practices. For…
Descriptors: Electronic Learning, Educational Technology, Human Factors Engineering, Learning Analytics
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Mangaroska, Katerina; Vesin, Boban; Kostakos, Vassilis; Brusilovsky, Peter; Giannakos, Michail N. – IEEE Transactions on Learning Technologies, 2021
With the wide expansion of distributed learning environments the way we learn became more diverse than ever. This poses an opportunity to incorporate different data sources of learning traces that can offer broader insights into learner behavior and the intricacies of the learning process. We argue that combining analytics across different…
Descriptors: Learning Analytics, Electronic Learning, Educational Technology, Instructional Design
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Davies, Randall; Allen, Gove; Albrecht, Conan; Bakir, Nesrin; Ball, Nick – Education Sciences, 2021
Analyzing the learning analytics from a course provides insights that can impact instructional design decisions. This study used educational data mining techniques, specifically a longitudinal k-means cluster analysis, to identify the strategies students used when completing the online portion of an online flipped spreadsheet course. An analysis…
Descriptors: Data Analysis, Identification, Learning Strategies, Electronic Learning
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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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Saqr, Mohammed; Peeters, Ward – British Journal of Educational Technology, 2022
Social Network Analysis (SNA) has enabled researchers to understand and optimize the key dimensions of collaborative learning. A majority of SNA research has so far used static networks, i.e., aggregated networks that compile interactions without considering "when" certain activities or relationships occurred. Compressing a temporal…
Descriptors: Social Networks, Network Analysis, Cooperative Learning, Electronic Learning
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West, Paige; Paige, Frederick; Lee, Walter; Watts, Natasha; Scales, Glenda – Journal of Civil Engineering Education, 2022
The expansion of online learning in higher education has both contributed to researchers exploring innovative ways to develop learning environments and created challenges in identifying student interactions with course material. Learning analytics is an emerging field that can identify student interactions and help make data-informed course design…
Descriptors: Learning Analytics, Student Attitudes, Electronic Learning, Construction Management
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