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) | 2 |
Descriptor
| Data Collection | 2 |
| Item Analysis | 2 |
| Multiple Choice Tests | 2 |
| Test Items | 2 |
| Academic Achievement | 1 |
| Achievement Tests | 1 |
| Advanced Placement | 1 |
| Alignment (Education) | 1 |
| Calculus | 1 |
| Comparative Analysis | 1 |
| Difficulty Level | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 1 |
| Non-Print Media | 1 |
| Reference Materials - General | 1 |
| Reports - Evaluative | 1 |
Education Level
| High Schools | 1 |
| Secondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Download full textKaliski, Pamela; Huff, Kristen; Barry, Carol – College Board, 2011
For educational achievement tests that employ multiple-choice (MC) items and aim to reliably classify students into performance categories, it is critical to design MC items that are capable of discriminating student performance according to the stated achievement levels. This is accomplished, in part, by clearly understanding how item design…
Descriptors: Alignment (Education), Academic Achievement, Expertise, Evaluative Thinking
Peer reviewed
Direct linkvon Davier, Alina A.; Wilson, Christine – Educational and Psychological Measurement, 2007
This article discusses the assumptions required by the item response theory (IRT) true-score equating method (with Stocking & Lord, 1983; scaling approach), which is commonly used in the nonequivalent groups with an anchor data-collection design. More precisely, this article investigates the assumptions made at each step by the IRT approach to…
Descriptors: Calculus, Item Response Theory, Scores, Data Collection
