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Showing 1 to 15 of 17 results Save | Export
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López-Zambrano, Javier; Lara, Juan A.; Romero, Cristóbal – Journal of Computing in Higher Education, 2022
One of the main current challenges in Educational Data Mining and Learning Analytics is the portability or transferability of predictive models obtained for a particular course so that they can be applied to other different courses. To handle this challenge, one of the foremost problems is the models' excessive dependence on the low-level…
Descriptors: Learning Analytics, Prediction, Models, Semantics
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Keskin, Sinan; Yurdugül, Halil – Journal of Educational Technology and Online Learning, 2022
This study aims to examine e-learning experiences of the learners by using learner system interaction metrics. In this context, an e-learning environment has been structured within the scope of a course. Learners interacted with learning activities and leave various traces when they interact with others, contents, and assessment tasks. Log data…
Descriptors: Electronic Learning, Learning Experience, Models, Learning Activities
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Siew, Cynthia S. Q. – Journal of Learning Analytics, 2022
This commentary discusses how research approaches from Cognitive Network Science can be of relevance to research in the field of Learning Analytics, with a focus on modelling the knowledge representations of learners and students as a network of interrelated concepts. After providing a brief overview of research in Cognitive Network Science, I…
Descriptors: Network Analysis, Learning Analytics, Cognitive Processes, Knowledge Level
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Ghallabi, Sameh; Essalmi, Fathi; Jemni, Mohamed; Kinshuk – Education and Information Technologies, 2020
With the emergence of technology, the personalization of e-learning systems is enhanced. These systems use a set of parameters for personalizing courses. However, in literature, these parameters are not based on classification and optimization algorithms to implement them in the cloud. Cloud computing is a new model of computing where standard and…
Descriptors: Electronic Learning, Internet, Information Storage, Models
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Zhang, Jiayi; Andres, Juliana Ma. Alexandra L.; Hutt, Stephen; Baker, Ryan S.; Ocumpaugh, Jaclyn; Mills, Caitlin; Brooks, Jamiella; Sethuraman, Sheela; Young, Tyron – International Educational Data Mining Society, 2022
Self-regulated learning (SRL) is a critical component of mathematics problem solving. Students skilled in SRL are more likely to effectively set goals, search for information, and direct their attention and cognitive process so that they align their efforts with their objectives. An influential framework for SRL, the SMART model, proposes that…
Descriptors: Mathematics Instruction, Teaching Methods, Problem Solving, Metacognition
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Gurcan, Fatih; Ozyurt, Ozcan; Cagiltay, Nergiz Ercil – International Review of Research in Open and Distributed Learning, 2021
E-learning studies are becoming very important today as they provide alternatives and support to all types of teaching and learning programs. The effect of the COVID-19 pandemic on educational systems has further increased the significance of e-learning. Accordingly, gaining a full understanding of the general topics and trends in e-learning…
Descriptors: Educational Trends, Electronic Learning, Models, Learning Analytics
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Ramos, David Brito; Ramos, Ilmara Monteverde Martins; Gasparini, Isabela; Teixeira de Oliveira, Elaine Harada – International Journal of Distance Education Technologies, 2021
This work presents a new approach to the learning path model in e-learning systems. The model uses data from the database records from an e-learning system and uses graphs as representation. In this work, the authors show how the model can be used to represent visually the learning paths, behavior analysis, help to suggest group formation for…
Descriptors: Electronic Learning, Models, Graphs, Integrated Learning Systems
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Ivanova, Malinka – Informatics in Education, 2020
eLearning is fast progressing scientific field proposing novel and specific approaches in a range of domains. It is well established practice in universities, schools and organizations for delivering interactive, adaptive and flexible training, taking advantage of contemporary and emerging technologies. Informatics is a continuously evolving…
Descriptors: Electronic Learning, Learning Analytics, Automation, Information Systems
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Sha, Lele; Rakovic, Mladen; Li, Yuheng; Whitelock-Wainwright, Alexander; Carroll, David; Gaševic, Dragan; Chen, Guanliang – International Educational Data Mining Society, 2021
Classifying educational forum posts is a longstanding task in the research of Learning Analytics and Educational Data Mining. Though this task has been tackled by applying both traditional Machine Learning (ML) approaches (e.g., Logistics Regression and Random Forest) and up-to-date Deep Learning (DL) approaches, there lacks a systematic…
Descriptors: Classification, Computer Mediated Communication, Learning Analytics, Data Analysis
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Mansouri, Taha; ZareRavasan, Ahad; Ashrafi, Amir – Journal of Information Technology Education: Research, 2021
Aim/Purpose: This research aims to present a brand-new approach for student performance prediction using the Learning Fuzzy Cognitive Map (LFCM) approach. Background: Predicting student academic performance has long been an important research topic in many academic disciplines. Different mathematical models have been employed to predict student…
Descriptors: Cognitive Mapping, Models, Prediction, Performance Factors
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Shabbir, Shahzad; Ayub, Muhammad Adnan; Khan, Farman Ali; Davis, Jeffrey – Interactive Technology and Smart Education, 2021
Purpose: Short-term motivation encompasses specific, challenging and attainable goals that develop in the limited timespan. On the other hand, long-term motivation indicates a sort of continuing commitment that is required to complete assigned task. As short-term motivational problems span for a limited period of time, such as a session,…
Descriptors: Learning Motivation, Electronic Learning, Time Factors (Learning), Learning Processes
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Aguilar, J.; Buendia, O.; Pinto, A.; Gutiérrez, J. – Interactive Learning Environments, 2022
Social Learning Analytics (SLA) seeks to obtain hidden information in large amounts of data, usually of an educational nature. SLA focuses mainly on the analysis of social networks (Social Network Analysis, SNA) and the Web, to discover patterns of interaction and behavior of educational social actors. This paper incorporates the SLA in a smart…
Descriptors: Learning Analytics, Cognitive Style, Socialization, Social Networks
Chenglu Li; Wanli Xing; Walter Leite – Grantee Submission, 2022
A discussion forum is a valuable tool to support student learning in online contexts. However, interactions in online discussion forums are sparse, leading to other issues such as low engagement and dropping out. Recent educational studies have examined the affordances of conversational agents (CA) powered by artificial intelligence (AI) to…
Descriptors: Social Responsibility, Computer Mediated Communication, Group Discussion, Artificial Intelligence
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Mandalapu, Varun; Chen, Lujie Karen; Chen, Zhiyuan; Gong, Jiaqi – International Educational Data Mining Society, 2021
With the increasing adoption of Learning Management Systems (LMS) in colleges and universities, research in exploring the interaction data captured by these systems is promising in developing a better learning environment and improving teaching practice. Most of these research efforts focused on course-level variables to predict student…
Descriptors: Integrated Learning Systems, Interaction, Undergraduate Students, Minority Group Students
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Georgakopoulos, Ioannis; Chalikias, Miltiadis; Zakopoulos, Vassilis; Kossieri, Evangelia – Education Sciences, 2020
Our modern era has brought about radical changes in the way courses are delivered and various teaching methods are being introduced to answer the purpose of meeting the modern learning challenges. On that account, the conventional way of teaching is giving place to a teaching method which combines conventional instructional strategies with…
Descriptors: Academic Failure, Blended Learning, Learner Engagement, Student Participation
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