Publication Date
In 2025 | 1 |
Since 2024 | 2 |
Since 2021 (last 5 years) | 3 |
Descriptor
Author
Bernard P. Veldkamp | 1 |
Coletta, Vincent P. | 1 |
Giada Spaccapanico Proietti | 1 |
Liqun Yin | 1 |
Mariagiulia Matteucci | 1 |
Matthias von Davier | 1 |
Stefania Mignani | 1 |
Ummugul Bezirhan | 1 |
Publication Type
Journal Articles | 3 |
Reports - Research | 2 |
Reports - Evaluative | 1 |
Education Level
Elementary Secondary Education | 2 |
Elementary Education | 1 |
Grade 4 | 1 |
High Schools | 1 |
Higher Education | 1 |
Intermediate Grades | 1 |
Postsecondary Education | 1 |
Secondary Education | 1 |
Audience
Location
Europe | 1 |
United States | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Trends in International… | 2 |
National Assessment of… | 1 |
Progress in International… | 1 |
SAT (College Admission Test) | 1 |
What Works Clearinghouse Rating
Coletta, Vincent P. – Physical Review Physics Education Research, 2023
Recently Burkholder "et al." argued that class normalized gains over the entire population of courses is approximated by a Cauchy distribution, not by a normal distribution, and therefore should not be used to compare different classes because means and standard deviations cannot be calculated. They argued that multiple linear regression…
Descriptors: Physics, Science Instruction, Scientific Concepts, Concept Formation
Liqun Yin; Ummugul Bezirhan; Matthias von Davier – International Electronic Journal of Elementary Education, 2025
This paper introduces an approach that uses latent class analysis to identify cut scores (LCA-CS) and categorize respondents based on context scales derived from largescale assessments like PIRLS, TIMSS, and NAEP. Context scales use Likert scale items to measure latent constructs of interest and classify respondents into meaningful ordered…
Descriptors: Multivariate Analysis, Cutting Scores, Achievement Tests, Foreign Countries
Giada Spaccapanico Proietti; Mariagiulia Matteucci; Stefania Mignani; Bernard P. Veldkamp – Journal of Educational and Behavioral Statistics, 2024
Classical automated test assembly (ATA) methods assume fixed and known coefficients for the constraints and the objective function. This hypothesis is not true for the estimates of item response theory parameters, which are crucial elements in test assembly classical models. To account for uncertainty in ATA, we propose a chance-constrained…
Descriptors: Automation, Computer Assisted Testing, Ambiguity (Context), Item Response Theory