Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 1 |
Descriptor
| Bayesian Statistics | 2 |
| Models | 2 |
| Student Behavior | 2 |
| College Students | 1 |
| Comparative Analysis | 1 |
| Computation | 1 |
| Computer Science Education | 1 |
| Data Analysis | 1 |
| Distance Education | 1 |
| Grade 8 | 1 |
| Knowledge Level | 1 |
| More ▼ | |
Publication Type
| Reports - Descriptive | 2 |
| Journal Articles | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
| Elementary Education | 1 |
| Grade 8 | 1 |
| Higher Education | 1 |
| Junior High Schools | 1 |
| Middle Schools | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Download full textRai, Dovan; Gong, Yue; Beck, Joseph E. – International Working Group on Educational Data Mining, 2009
Student modeling is a widely used approach to make inference about a student's attributes like knowledge, learning, etc. If we wish to use these models to analyze and better understand student learning there are two problems. First, a model's ability to predict student performance is at best weakly related to the accuracy of any one of its…
Descriptors: Data Analysis, Statistical Analysis, Probability, Models
Peer reviewed
Direct linkXenos, 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
