Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 5 |
Since 2016 (last 10 years) | 5 |
Since 2006 (last 20 years) | 8 |
Descriptor
Pattern Recognition | 8 |
Prediction | 8 |
Data Analysis | 7 |
Information Retrieval | 7 |
At Risk Students | 5 |
College Students | 5 |
Models | 5 |
Distance Education | 4 |
Information Technology | 4 |
Academic Achievement | 3 |
Data Processing | 3 |
More ▼ |
Source
Interactive Learning… | 2 |
International Association for… | 2 |
International Educational… | 2 |
Education and Information… | 1 |
Journal of Educators Online | 1 |
Author
Publication Type
Journal Articles | 4 |
Reports - Research | 3 |
Collected Works - Proceedings | 2 |
Reports - Descriptive | 2 |
Speeches/Meeting Papers | 2 |
Information Analyses | 1 |
Reports - Evaluative | 1 |
Education Level
Postsecondary Education | 8 |
Higher Education | 7 |
Elementary Secondary Education | 2 |
High Schools | 2 |
Secondary Education | 1 |
Audience
Location
Brazil | 2 |
Florida | 2 |
Portugal | 2 |
United States | 2 |
Asia | 1 |
Australia | 1 |
Colombia | 1 |
Connecticut | 1 |
Denmark | 1 |
Egypt | 1 |
Estonia | 1 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Gontzis, Andreas F.; Kotsiantis, Sotiris; Panagiotakopoulos, Christos T.; Verykios, Vassilios S. – Interactive Learning Environments, 2022
Attrition is one of the main concerns in distance learning due to the impact on the incomes and institutions reputation. Timely identification of students at risk has high practical value in effective students' retention services. Big Data mining and machine learning methods are applied to manipulate, analyze and predict students' failure,…
Descriptors: Student Attrition, Distance Education, At Risk Students, Achievement
Gkontzis, Andreas F.; Kotsiantis, Sotiris; Panagiotakopoulos, Christos T.; Verykios, Vassilios S. – Interactive Learning Environments, 2022
Attrition is one of the main concerns in distance learning due to the impact on the incomes and institutions reputation. Timely identification of students at risk has high practical value in effective students' retention services. Big Data mining and machine learning methods are applied to manipulate, analyze, and predict students' failure,…
Descriptors: Student Attrition, Distance Education, At Risk Students, Achievement
Xu, Tonghui – Journal of Educators Online, 2023
The early detection of students' academic performance or final grades helps instructors prepare their online courses. In the Open University Learning Analytics Dataset, I found many online students clicked the course materials before the first day of class. This study aims to investigate how data mining models can use this student interaction data…
Descriptors: College Students, Online Courses, Academic Achievement, Data Analysis
Costa, Stella F.; Diniz, Michael M. – Education and Information Technologies, 2022
The large rates of students' failure is a very frequent problem in undergraduate courses, being even more evident in exact sciences. Pointing out the reasons of such problem is a paramount research topic, though not an easy task. An alternative is to use Educational Data Mining techniques (EDM), which enables one to convert data from educational…
Descriptors: Prediction, Undergraduate Students, Mathematics Education, Models
Cohausz, Lea; Tschalzev, Andrej; Bartelt, Christian; Stuckenschmidt, Heiner – International Educational Data Mining Society, 2023
Demographic features are commonly used in Educational Data Mining (EDM) research to predict at-risk students. Yet, the practice of using demographic features has to be considered extremely problematic due to the data's sensitive nature, but also because (historic and representation) biases likely exist in the training data, which leads to strong…
Descriptors: Information Retrieval, Data Processing, Pattern Recognition, Information Technology
International Educational Data Mining Society, 2012
The 5th International Conference on Educational Data Mining (EDM 2012) is held in picturesque Chania on the beautiful Crete island in Greece, under the auspices of the International Educational Data Mining Society (IEDMS). The EDM 2012 conference is a leading international forum for high quality research that mines large data sets of educational…
Descriptors: Information Retrieval, Data, Data Analysis, Pattern Recognition
Niemi, David; Gitin, Elena – International Association for Development of the Information Society, 2012
An underlying theme of this paper is that it can be easier and more efficient to conduct valid and effective research studies in online environments than in traditional classrooms. Taking advantage of the "big data" available in an online university, we conducted a study in which a massive online database was used to predict student…
Descriptors: Higher Education, Online Courses, Academic Persistence, Identification
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers