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Rotelli, Daniela; Monreale, Anna – Journal of Learning Analytics, 2023
The increased adoption of online learning environments has resulted in the availability of vast amounts of educational log data, which raises questions that could be answered by a thorough and accurate examination of students' online learning behaviours. Event logs describe something that occurred on a platform and provide multiple dimensions that…
Descriptors: Learning Analytics, Learning Management Systems, Time on Task, Student Behavior
Abdullahi Yusuf; Norah Md Noor; Shamsudeen Bello – Education and Information Technologies, 2024
Studies examining students' learning behavior predominantly employed rich video data as their main source of information due to the limited knowledge of computer vision and deep learning algorithms. However, one of the challenges faced during such observation is the strenuous task of coding large amounts of video data through repeated viewings. In…
Descriptors: Learning Analytics, Student Behavior, Video Technology, Classification
Elmoazen, Ramy; Saqr, Mohammed; Khalil, Mohammad; Wasson, Barbara – Smart Learning Environments, 2023
Remote learning has advanced from the theoretical to the practical sciences with the advent of virtual labs. Although virtual labs allow students to conduct their experiments remotely, it is a challenge to evaluate student progress and collaboration using learning analytics. So far, a study that systematically synthesizes the status of research on…
Descriptors: Learning Analytics, Higher Education, Medical Education, Student Behavior
Daoudi, Ibtissem – Education and Information Technologies, 2022
In recent years, the interest in the use of serious games as teaching and learning tools in traditional educational processes has increased significantly. Serious Educational Games (SEG) and Learning Analytics (LA) are gaining increasing attention from teachers and researchers, since they both can improve the learning quality. In this article, we…
Descriptors: Learning Analytics, Usability, Educational Games, Educational Benefits
Xiaona Xia; Wanxue Qi – European Journal of Education, 2025
Massive Open Online Courses (MOOCs) effectively support online learning behaviour; while constructing a sustainable learning process, MOOCs have also formed the social network. In addition, learners' burnout state has become a serious obstacle to the development and promotion of MOOCs. This study analyzes the potential social behaviour associated…
Descriptors: MOOCs, Burnout, Social Behavior, Feedback (Response)
El Aouifi, Houssam; El Hajji, Mohamed; Es-Saady, Youssef; Douzi, Hassan – Education and Information Technologies, 2021
This paper analyzes how learners interact with the pedagogical sequences of educational videos, and its effect on their performance. In this study, the suggested video courses are segmented on several pedagogical sequences. In fact, we're not focusing on the type of clicks made by learners, but we're concentrating on the pedagogical sequences in…
Descriptors: Video Technology, Student Behavior, Prediction, Learning Analytics
Tong, Yao; Zhan, Zehui – Interactive Technology and Smart Education, 2023
Purpose: The purpose of this study is to set up an evaluation model to predict massive open online courses (MOOC) learning performance by analyzing MOOC learners' online learning behaviors, and comparing three algorithms -- multiple linear regression (MLR), multilayer perceptron (MLP) and classification and regression tree (CART).…
Descriptors: MOOCs, Online Courses, Learning Analytics, Prediction
Yang, Tzu-Chi; Chen, Sherry Y. – Interactive Learning Environments, 2023
Individual differences exist among learners. Among various individual differences, cognitive styles can strongly predict learners' learning behavior. Therefore, cognitive styles are essential for the design of online learning. There are a variety of cognitive style dimensions and overlaps exist among these dimensions. In particular, Witkin's field…
Descriptors: Student Behavior, Educational Technology, Electronic Learning, Cognitive Style
Li Chen; Xuewang Geng; Min Lu; Atsushi Shimada; Masanori Yamada – SAGE Open, 2023
Developed to maximize learning performance, learning analytics dashboards (LAD) are becoming increasingly commonplace in education. An LAD's effectiveness depends on how it is used and varies according to users' academic levels. In this study, two LADs and a learning support system were used in a higher education course to support students'…
Descriptors: Learning Analytics, Learning Management Systems, Cognitive Processes, Learning Strategies
Sonsoles López-Pernas; Mohammed Saqr; Aldo Gordillo; Enrique Barra – Interactive Learning Environments, 2023
Learning analytics methods have proven useful in providing insights from the increasingly available digital data about students in a variety of learning environments, including serious games. However, such methods have not been applied to the specific context of educational escape rooms and therefore little is known about students' behavior while…
Descriptors: Learning Analytics, Educational Games, Student Behavior, Computer Uses in Education
Mubarak, Ahmed Ali; Cao, Han; Ahmed, Salah A. M. – Education and Information Technologies, 2021
Analysis of learning behavior of MOOC enthusiasts has become a posed challenge in the Learning Analytics field, which is especially related to video lecture data, since most learners watch the same online lecture videos. It helps to conduct a comprehensive analysis of such behaviors and explore various learning patterns for learners and predict…
Descriptors: Learning Analytics, Online Courses, Video Technology, Artificial Intelligence
Priya Sharma; Mahir Akgun; Qiyuan Li – Educational Technology Research and Development, 2024
Networked and digital technologies are increasingly being used for learning in formal and informal contexts, and participant engagement occurs primarily via online discussions. In this paper, we describe an ongoing research project that focuses on examining and understanding student engagement in collaborative online discussions within a formal…
Descriptors: Social Networks, Network Analysis, Discourse Analysis, Classification
Emma R. Dear; Bryce D. McLeod; Nicole M. Peterson; Kevin S. Sutherland; Michael D. Broda; Alex R. Dopp; Aaron R. Lyon – Grantee Submission, 2024
Introduction: Due to usability, feasibility, and acceptability concerns, observational treatment fidelity measures are often challenging to deploy in schools. Teacher self-report fidelity measures with specific design features might address some of these barriers. This case study outlines a community-engaged, iterative process to adapt the…
Descriptors: Measures (Individuals), Data Collection, Observation, Learning Analytics
Du, Xiaoming; Ge, Shilun; Wang, Nianxin – International Journal of Information and Communication Technology Education, 2022
In the context of education big data, it uses data mining and learning analysis technology to accurately predict and effectively intervene in learning. It is helpful to realize individualized teaching and individualized teaching. This research analyzes student life behavior data and learning behavior data. A model of student behavior…
Descriptors: Prediction, Data, Student Behavior, Academic Achievement
Li, Liang-Yi; Huang, Wen-Lung – Educational Technology & Society, 2023
With the increasing bandwidth, videos have been gradually used as submissions for online peer assessment activities. However, their transient nature imposes a high cognitive load on students, particularly lowability students. Therefore, reviewers' ability is a key factor that may affect the reviewing process and performance in an online video peer…
Descriptors: Peer Evaluation, Undergraduate Students, Video Technology, Evaluation Methods

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