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Narjes Rohani; Behnam Rohani; Areti Manataki – Journal of Educational Data Mining, 2024
The prediction of student performance and the analysis of students' learning behaviour play an important role in enhancing online courses. By analysing a massive amount of clickstream data that captures student behaviour, educators can gain valuable insights into the factors that influence students' academic outcomes and identify areas of…
Descriptors: Mathematics Education, Models, Prediction, Knowledge Level
Albreiki, Balqis; Zaki, Nazar; Alashwal, Hany – Education Sciences, 2021
Educational Data Mining plays a critical role in advancing the learning environment by contributing state-of-the-art methods, techniques, and applications. The recent development provides valuable tools for understanding the student learning environment by exploring and utilizing educational data using machine learning and data mining techniques.…
Descriptors: Literature Reviews, Grade Prediction, Artificial Intelligence, Educational Environment
Ricker, Gina M.; Koziarski, Mathew; Walters, Alyssa M. – Journal of Online Learning Research, 2020
The relationship between student activity data and performance in the online classroom is well-documented, yet the parameters of this relationship and their implications for K-12 online schools are not yet well understood. This study examined the role of student chronotype (defined here as the time of day a student is most active in an online…
Descriptors: Electronic Learning, Online Courses, Student Behavior, Data Collection
Xing, Wanli – Distance Education, 2019
Massive open online courses (MOOCs) face persistent challenges related to student performance, including high rates of attrition and low student achievement scores. Previous studies that have examined the performance of students in MOOCs have done so using qualitative analysis and the quantitative analysis of small samples. This study is the first…
Descriptors: Large Group Instruction, Online Courses, Educational Technology, Technology Uses in Education
Weiand, Augusto; Manssour, Isabel Harb; Silveira, Milene Selbach – International Journal of Distance Education Technologies, 2019
With technological advances, distance education has been frequently discussed in recent years. The learning environments used in this course usually generates a great deal of data because of the large number of students and the various tasks involving their interaction. In order to facilitate the analysis of the data, the authors researched to…
Descriptors: Foreign Countries, Distance Education, Online Courses, Visualization
Kostopoulos, Georgios; Karlos, Stamatis; Kotsiantis, Sotiris – IEEE Transactions on Learning Technologies, 2019
Educational data mining has gained a lot of attention among scientists in recent years and constitutes an efficient tool for unraveling the concealed knowledge in educational data. Recently, semisupervised learning methods have been gradually implemented in the educational process demonstrating their usability and effectiveness. Cotraining is a…
Descriptors: Academic Achievement, Case Studies, Usability, Data Analysis
Chaker, Rawad; Bachelet, Rémi – International Review of Research in Open and Distributed Learning, 2020
This paper uses data mining from a French project management MOOC to study learners' performance (i.e., grades and persistence) based on a series of variables: age, educational background, socio-professional status, geographical area, gender, self- versus mandatory-enrollment, and learning intentions. Unlike most studies in this area, we focus on…
Descriptors: Foreign Countries, Large Group Instruction, Online Courses, Grades (Scholastic)
Jimenez, Laura – Center for American Progress, 2020
Schools face enormous challenges regarding how to operate efficiently and safely for the 2020-21 school year. As part of that response, some state leaders are asking the U.S. Department of Education to waive the annual federal testing and accountability requirements for 2021, which are key to understanding and addressing gaps in education among…
Descriptors: COVID-19, Pandemics, Disease Control, Well Being
Barbara Woods McElroy; Bruce H. Lubich – Sage Research Methods Cases, 2017
This case describes the research process followed by two professors who chose to study student outcomes in our online accounting classrooms. Motivated by the discovery of a possible anomaly in classroom outcomes, we decided to look further. We thought the anomaly might be explained by student procrastination. If our perception proved true, the…
Descriptors: College Students, Accounting, Distance Education, Online Courses
Beemer, Joshua; Spoon, Kelly; Fan, Juanjuan; Stronach, Jeanne; Frazee, James P.; Bohonak, Andrew J.; Levine, Richard A. – Journal of Statistics Education, 2018
Estimating the efficacy of different instructional modalities, techniques, and interventions is challenging because teaching style covaries with instructor, and the typical student only takes a course once. We introduce the individualized treatment effect (ITE) from analyses of personalized medicine as a means to quantify individual student…
Descriptors: Learning Modalities, Academic Achievement, Intervention, Educational Research
Nugent, Gwen; Guru, Ashu; Namuth-Covert, Deana M. – Interdisciplinary Journal of e-Skills and Lifelong Learning, 2018
Aim/Purpose: This study examines differences in credit and noncredit users' learning and usage of the Plant Sciences E-Library (PASSEL, http://passel.unl.edu), a large international, open-source multidisciplinary learning object repository. Background: Advances in online education are helping educators to meet the needs of formal academic credit…
Descriptors: Academic Libraries, Electronic Libraries, Research Libraries, Electronic Learning
National Forum on Education Statistics, 2018
The purpose of this document is to recommend practices that will help education agencies collect, report, and use attendance data to improve student and school outcomes. This publication substantively revises and expands the information included in "Every School Day Counts: The Forum Guide to Collecting and Using Attendance Data,"…
Descriptors: Attendance, Data Collection, Elementary Secondary Education, Correlation
Martin, Florence; Ndoye, Abdou – Journal of University Teaching and Learning Practice, 2016
Learning analytics can be used to enhance student engagement and performance in online courses. Using learning analytics, instructors can collect and analyze data about students and improve the design and delivery of instruction to make it more meaningful for them. In this paper, the authors review different categories of online assessments and…
Descriptors: Educational Research, Data Collection, Data Analysis, Academic Achievement
Kahan, Tali; Soffer, Tal; Nachmias, Rafi – International Review of Research in Open and Distributed Learning, 2017
In recent years there has been a proliferation of massive open online courses (MOOCs), which provide unprecedented opportunities for lifelong learning. Registrants approach these courses with a variety of motivations for participation. Characterizing the different types of participation in MOOCs is fundamental in order to be able to better…
Descriptors: College Students, Student Behavior, Online Courses, Large Group Instruction
Zhang, Jia-Hua; Zhang, Ye-Xing; Zou, Qin; Huang, Sen – Educational Technology & Society, 2018
The practice and application of education data mining and learning analytics has become the focus of educational researchers. However, it is still a difficult task to explore the law of group learning and the characteristics of individual learning. In this study, the online learning logs of 1,088 students from 22 classes were analyzed from the…
Descriptors: Data Collection, Data Analysis, Educational Research, Diaries