Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 2 |
Since 2006 (last 20 years) | 2 |
Descriptor
Comparative Analysis | 2 |
Item Response Theory | 2 |
Nonparametric Statistics | 2 |
Research Methodology | 2 |
Statistical Significance | 2 |
Test Items | 2 |
Achievement Tests | 1 |
Alternative Assessment | 1 |
Difficulty Level | 1 |
Educational Research | 1 |
Evaluation Methods | 1 |
More ▼ |
Author
Anthony Petrosino | 1 |
Corey Brady | 1 |
Golino, Hudson F. | 1 |
Gomes, Cristiano M. A. | 1 |
Karen Duseau | 1 |
Walter M. Stroup | 1 |
Publication Type
Reports - Research | 2 |
Journal Articles | 1 |
Speeches/Meeting Papers | 1 |
Education Level
Audience
Laws, Policies, & Programs
Assessments and Surveys
State of Texas Assessments of… | 1 |
What Works Clearinghouse Rating
Walter M. Stroup; Anthony Petrosino; Corey Brady; Karen Duseau – North American Chapter of the International Group for the Psychology of Mathematics Education, 2023
Tests of statistical significance often play a decisive role in establishing the empirical warrant of evidence-based research in education. The results from pattern-based assessment items, as introduced in this paper, are categorical and multimodal and do not immediately support the use of measures of central tendency as typically related to…
Descriptors: Statistical Significance, Comparative Analysis, Research Methodology, Evaluation Methods
Golino, Hudson F.; Gomes, Cristiano M. A. – International Journal of Research & Method in Education, 2016
This paper presents a non-parametric imputation technique, named random forest, from the machine learning field. The random forest procedure has two main tuning parameters: the number of trees grown in the prediction and the number of predictors used. Fifty experimental conditions were created in the imputation procedure, with different…
Descriptors: Item Response Theory, Regression (Statistics), Difficulty Level, Goodness of Fit