방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| Wright Map Analysis× | 문항 반응 이론 (IRT)× | |
|---|---|---|
| 분야≠ | Education | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 2005 | 1952–1968 |
| 창시자≠ | Benjamin Wright (Rasch measurement); construct-mapping framing by Mark Wilson | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| 유형≠ | Graphical display aligning person abilities and item difficulties on one scale | Probabilistic measurement model |
| 원전≠ | Wilson, M. (2005). Constructing Measures: An Item Response Modeling Approach. Lawrence Erlbaum Associates. ISBN: 9780805847857 | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| 별칭 | Item-Person Map, Item Map, Construct Map (Rasch), Variable Map | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| 관련≠ | 4 | 5 |
| 요약≠ | A Wright map (item-person map) is the signature graphical output of Rasch measurement: it places persons and items on the same vertical scale, with examinee abilities on one side and item difficulties on the other, both in logits. Because a person succeeds on an item with probability one-half when their ability equals the item's difficulty, this shared scaling lets analysts see at a glance how well a test is targeted to its examinees, what the items reveal about the construct's order, and where measurement is sparse. Named for Benjamin Wright and central to Mark Wilson's construct-mapping approach, it is a primary tool for interpreting and validating measures. | Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons. |
| ScholarGate데이터셋 ↗ |
|
|