Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 3 |
Since 2006 (last 20 years) | 4 |
Descriptor
Bayesian Statistics | 4 |
Classification | 4 |
Research Methodology | 4 |
Educational Research | 2 |
Models | 2 |
Research Design | 2 |
Alternative Assessment | 1 |
Benchmarking | 1 |
Bias | 1 |
Correlation | 1 |
Data Analysis | 1 |
More ▼ |
Source
Cognitive Science | 1 |
Digital Education Review | 1 |
Review of Educational Research | 1 |
Sociological Methods &… | 1 |
Author
Publication Type
Journal Articles | 4 |
Reports - Research | 3 |
Information Analyses | 1 |
Reports - Descriptive | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Barrenechea, Rodrigo; Mahoney, James – Sociological Methods & Research, 2019
This article develops a set-theoretic approach to Bayes's theorem and Bayesian process tracing. In the approach, hypothesis testing is the procedure whereby one updates beliefs by narrowing the range of states of the world that are regarded as possible, thus diminishing the domain in which the actual world can reside. By explicitly connecting…
Descriptors: Bayesian Statistics, Hypothesis Testing, Qualitative Research, Research Methodology
Villanueva Manjarres, Andrés; Moreno Sandoval, Luis Gabriel; Salinas Suárez, Martha Janneth – Digital Education Review, 2018
Educational Data Mining is an emerging discipline which seeks to develop methods to explore large amounts of data from educational settings, in order to understand students' behavior, interests and results in a better way. In recent years there have been various works related to this specialty and multiple data mining techniques derived from this…
Descriptors: Information Retrieval, Data Analysis, Educational Environment, Research Methodology
McNeish, Daniel – Review of Educational Research, 2017
In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…
Descriptors: Models, Statistical Analysis, Sampling, Sample Size
Griffiths, Thomas L.; Christian, Brian R.; Kalish, Michael L. – Cognitive Science, 2008
Many of the problems studied in cognitive science are inductive problems, requiring people to evaluate hypotheses in the light of data. The key to solving these problems successfully is having the right inductive biases--assumptions about the world that make it possible to choose between hypotheses that are equally consistent with the observed…
Descriptors: Logical Thinking, Bias, Identification, Research Methodology