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| Συγκλίνουσα Εγκυρότητα για Ηλεκτρονικά Προσαρμοστικά Τεστ× | Συγκλίνουσα Εγκυρότητα× | |
|---|---|---|
| Πεδίο | Ψυχομετρία | Ψυχομετρία |
| Οικογένεια | Latent structure | Latent structure |
| Έτος προέλευσης≠ | 1989–2000 | 1959 |
| Δημιουργός≠ | Samuel Messick (validity framework); Wainer and colleagues (CAT context) | Donald T. Campbell & Donald W. Fiske |
| Τύπος | Validity evidence / construct validation | Validity evidence / construct validation |
| Θεμελιώδης πηγή≠ | Wainer, H. (Ed.). (2000). Computerized Adaptive Testing: A Primer (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805835113 | Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105. DOI ↗ |
| Εναλλακτικές ονομασίες≠ | CAT convergent validity, adaptive test construct validation, CAT validity evidence, convergent validity in CAT | convergent construct validity, convergence validity, AVE-based convergent validity |
| Συναφείς≠ | 5 | 4 |
| Σύνοψη≠ | Convergent validity assessment for computerized adaptive tests (CATs) examines whether the ability or trait estimates produced by an adaptive algorithm correlate substantially with scores from other measures of the same construct. Because each examinee receives a different subset of items in a CAT, demonstrating that the resulting scores still converge with theoretically related external measures is a critical step in establishing construct validity evidence. | Convergent validity is the degree to which multiple indicators that are theoretically expected to measure the same construct actually correlate with one another. It is one of the two complementary forms of construct validity identified by Campbell and Fiske (1959) and is now routinely assessed via factor loadings and the Average Variance Extracted (AVE) statistic in SEM-based scale validation. |
| ScholarGateΣύνολο δεδομένων ↗ |
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