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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
Kaliisa, Rogers; Dolonen, Jan Arild – Technology, Knowledge and Learning, 2023
Despite the potential of learning analytics (LA) to support teachers' everyday practice, its adoption has not been fully embraced due to the limited involvement of teachers as co-designers of LA systems and interventions. This is the focus of the study described in this paper. Following a design-based research (DBR) approach and guided by concepts…
Descriptors: College Faculty, Student Participation, Discourse Analysis, Behavior Patterns
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
Zhao, Fuzheng; Hwang, Gwo-Jen; Yin, Chengjiu – Educational Technology & Society, 2021
Educational data mining and learning analytics have become a very important topic in the field of education technology. Many frameworks have been proposed for learning analytics which make it possible to identify learning behavior patterns or strategies. However, it is difficult to understand the reason why behavior patterns occur and why certain…
Descriptors: Behavior Patterns, Reading, Textbooks, Electronic Learning
Milat, Iness Nedji; Seridi, Hassina; Moudjari, Abdelkader – International Journal of Distance Education Technologies, 2020
Recently, discovering learner behaviour has taken more attention in the field of e-learning. It aims to gain useful insights into the learning process of students despite the absence of direct interaction with teachers. In fact, the only available source of information in such environments is the log file that represents all possible interactions…
Descriptors: Student Behavior, Behavior Patterns, Electronic Learning, Learning Analytics
Hsu, Ting-Chia; Abelson, Hal; Patton, Evan; Chen, Shih-Chu; Chang, Hsuan-Ning – International Journal of Computer-Supported Collaborative Learning, 2021
In order to promote the practice of co-creation, a real-time collaboration (RTC) version of the popular block-based programming (BBP) learning environment, MIT App Inventor (MAI), was proposed and implemented. RTC overcomes challenges related to non-collocated group work, thus lowering barriers to cross-region and multi-user collaborative software…
Descriptors: Self Efficacy, Behavior Patterns, Student Behavior, Programming
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)
Kokoç, Mehmet; Akçapinar, Gökhan; Hasnine, Mohammad Nehal – Educational Technology & Society, 2021
This study analyzed students' online assignment submission behaviors from the perspectives of temporal learning analytics. This study aimed to model the time-dependent changes in the assignment submission behavior of university students by employing various machine learning methods. Precisely, clustering, Markov Chains, and association rule mining…
Descriptors: Electronic Learning, Assignments, Behavior Patterns, Learning Analytics
Demetrios G. Sampson, Editor; Dirk Ifenthaler, Editor; Pedro Isaías, Editor – Cognition and Exploratory Learning in the Digital Age, 2024
This edited volume presents the latest research focussing on current challenges on the deployment of smart technologies and pedagogies for supporting teaching and learning in the post-covid19 era. This is at the core of studying the evolution of the learning process, the role of technology-supported pedagogical approaches, and the progress of…
Descriptors: Teaching Methods, Influence of Technology, Educational Technology, Professional Development
Çebi, Ayça; Güyer, Tolga – Education and Information Technologies, 2020
In this study, students' interactions with different learning activities are examined and the relation among learning performance with different interaction patterns, learning performance, self-regulated learning (SRL) strategies and motivation is presented. Learning materials including different kinds of activities are prepared and presented to…
Descriptors: Interaction, Behavior Patterns, Learning Analytics, Electronic Learning
Tzafilkou, Katerina; Protogeros, Nicolaos – European Educational Researcher, 2020
This study investigates students' mouse behavior during their interaction with a web-based experiential learning environment for Computer Science courses. The research focuses on the detection of correlations between the monitored mouse metrics and students' technology acceptance items of perceived usefulness and ease of use. Findings reveal…
Descriptors: Electronic Learning, Learning Analytics, Student Attitudes, Usability
Chen, Zhongzhou; Xu, Mengyu; Garrido, Geoffrey; Gunthrie, Matthew W. – Physical Review Physics Education Research, 2020
This study examines whether including more contextual information in data analysis could improve our ability to identify the relation between students' online learning behavior and overall performance in an introductory physics course. We created four linear regression models correlating students' pass-fail events in a sequence of online learning…
Descriptors: Correlation, Electronic Learning, Performance Factors, Learning Analytics
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
Dollinger, Mollie; Cox, Sarah; Eaton, Rebecca; Vanderlelie, Jessica; Ridsdale, Sam – Journal of Interactive Media in Education, 2020
This article will explore usage patterns and perceptions of online learning support among university students. As higher education expands to include increasingly diverse student cohorts, alternative online-supported learning services have gained attention as a mechanism to support student success. However, there is a paucity of research regarding…
Descriptors: Student Diversity, Electronic Learning, Academic Support Services, College Students
Mtebe, Joel S.; Kondoro, Aron W. – Journal of Learning for Development, 2019
The adoption and use of various eLearning systems to enhance the quality of education in secondary schools in Tanzania is becoming common. However, there is little evidence to suggest that students actually use them. Existing studies tend to focus on investigating students' attitude towards using these systems through surveys. Nonetheless, data…
Descriptors: Behavior Patterns, Electronic Learning, Secondary School Students, Student Behavior
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