Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 1 |
Since 2006 (last 20 years) | 3 |
Descriptor
Elementary School Students | 3 |
Foreign Countries | 3 |
Verbal Tests | 3 |
Computation | 2 |
Indo European Languages | 2 |
Item Response Theory | 2 |
Spelling | 2 |
Test Bias | 2 |
Academic Language | 1 |
Cognitive Development | 1 |
Grade 4 | 1 |
More ▼ |
Author
Janssen, Rianne | 2 |
Arsaythamby Veloo | 1 |
De Boeck, Paul | 1 |
Kahraman, Nilufer | 1 |
S. Kanageswari Suppiah… | 1 |
Suheysen Revindran | 1 |
Van Nijlen, Daniel | 1 |
Publication Type
Journal Articles | 3 |
Reports - Research | 3 |
Education Level
Elementary Education | 3 |
Grade 4 | 3 |
Grade 3 | 2 |
Intermediate Grades | 2 |
Elementary Secondary Education | 1 |
Grade 5 | 1 |
Grade 6 | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Arsaythamby Veloo; S. Kanageswari Suppiah Shanmugam; Suheysen Revindran – Malaysian Journal of Learning and Instruction, 2024
Purpose: The language load within mathematics test items can lead to inaccuracy in assessing "Orang Asli" pupils' mathematical ability due to their struggle in comprehending the academic language. This study aims to determine the validity of using test accommodations in the form of oral academic language and oral native language when…
Descriptors: Verbal Tests, Foreign Countries, Student Evaluation, Mathematics Tests
Van Nijlen, Daniel; Janssen, Rianne – Applied Measurement in Education, 2011
The distinction between quantitative and qualitative differences in mastery is essential when monitoring student progress and is crucial for instructional interventions to deal with learning difficulties. Mixture item response theory (IRT) models can provide a convenient way to make the distinction between quantitative and qualitative differences…
Descriptors: Spelling, Indo European Languages, Vowels, Verbal Tests
Kahraman, Nilufer; De Boeck, Paul; Janssen, Rianne – International Journal of Testing, 2009
This study introduces an approach for modeling multidimensional response data with construct-relevant group and domain factors. The item level parameter estimation process is extended to incorporate the refined effects of test dimension and group factors. Differences in item performances over groups are evaluated, distinguishing two levels of…
Descriptors: Test Bias, Test Items, Groups, Interaction