Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 5 |
| Since 2007 (last 20 years) | 8 |
Descriptor
| Bayesian Statistics | 9 |
| Prediction | 9 |
| Student Behavior | 9 |
| Models | 6 |
| Artificial Intelligence | 4 |
| Classification | 4 |
| College Students | 4 |
| Data Analysis | 4 |
| Intelligent Tutoring Systems | 4 |
| Tests | 4 |
| Academic Achievement | 3 |
| More ▼ | |
Source
| International Educational… | 2 |
| Computers and Education | 1 |
| Grantee Submission | 1 |
| International Journal of… | 1 |
| International Working Group… | 1 |
| Journal of Educational Data… | 1 |
| Journal of Learning Analytics | 1 |
| Measurement:… | 1 |
Author
Publication Type
| Journal Articles | 5 |
| Reports - Research | 5 |
| Collected Works - Proceedings | 3 |
| Reports - Descriptive | 1 |
Education Level
| Higher Education | 5 |
| Secondary Education | 5 |
| High Schools | 4 |
| Junior High Schools | 4 |
| Middle Schools | 4 |
| Postsecondary Education | 4 |
| Elementary Education | 2 |
| Elementary Secondary Education | 2 |
| Grade 8 | 2 |
| Grade 9 | 2 |
| Adult Education | 1 |
| More ▼ | |
Audience
Location
| Massachusetts | 2 |
| North Carolina | 2 |
| Australia | 1 |
| Brazil | 1 |
| China | 1 |
| Czech Republic | 1 |
| Israel | 1 |
| Netherlands | 1 |
| Pennsylvania | 1 |
| Slovakia | 1 |
| Spain | 1 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
| Massachusetts Comprehensive… | 1 |
What Works Clearinghouse Rating
Sinharay, Sandip – Measurement: Interdisciplinary Research and Perspectives, 2018
Producers and consumers of test scores are increasingly concerned about fraudulent behavior before and during the test. There exist several statistical or psychometric methods for detecting fraudulent behavior on tests. This paper provides a review of the Bayesian approaches among them. Four hitherto-unpublished real data examples are provided to…
Descriptors: Ethics, Cheating, Student Behavior, Bayesian Statistics
Sinharay, Sandip – Grantee Submission, 2018
Producers and consumers of test scores are increasingly concerned about fraudulent behavior before and during the test. There exist several statistical or psychometric methods for detecting fraudulent behavior on tests. This paper provides a review of the Bayesian approaches among them. Four hitherto-unpublished real data examples are provided to…
Descriptors: Ethics, Cheating, Student Behavior, Bayesian Statistics
Rodrigues, Rodrigo Lins; Ramos, Jorge Luis Cavalcanti; Silva, João Carlos Sedraz; Dourado, Raphael A.; Gomes, Alex Sandro – International Journal of Distance Education Technologies, 2019
The increasing use of the Learning Management Systems (LMSs) is making available an ever-growing, volume of data from interactions between teachers and students. This study aimed to develop a model capable of predicting students' academic performance based on indicators of their self-regulated behavior in LMSs. To accomplish this goal, the authors…
Descriptors: Management Systems, Teacher Student Relationship, Distance Education, College Students
Lang, Charles – Journal of Learning Analytics, 2014
This article proposes a coherent framework for the use of Inverse Bayesian estimation to summarize and make predictions about student behaviour in adaptive educational settings. The Inverse Bayes Filter utilizes Bayes theorem to estimate the relative impact of contextual factors and internal student factors on student performance using time series…
Descriptors: Bayesian Statistics, Academic Achievement, Prediction, Student Behavior
Sabourin, Jennifer L.; Rowe, Jonathan P.; Mott, Bradford W.; Lester, James C. – Journal of Educational Data Mining, 2013
Over the past decade, there has been growing interest in real-time assessment of student engagement and motivation during interactions with educational software. Detecting symptoms of disengagement, such as off-task behavior, has shown considerable promise for understanding students' motivational characteristics during learning. In this paper, we…
Descriptors: Student Behavior, Classification, Learner Engagement, Data Analysis
Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
Xenos, Michalis – Computers and Education, 2004
This paper presents a methodological approach based on Bayesian Networks for modelling the behaviour of the students of a bachelor course in computers in an Open University that deploys distance educational methods. It describes the structure of the model, its application for modelling the behaviour of student groups in the Informatics Course of…
Descriptors: Prediction, Student Behavior, Open Education, Distance Education
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries

Peer reviewed
Direct link
