Open AccessA TREE‐BASED APPROACH TO PROFICIENCY SCALING & DIAGNOSTIC ASSESSMENT
Author(s) -
Sheehan Kathleen M.
Publication year - 1997
Publication title -
ets research report series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.235
H-Index - 5
ISSN - 2330-8516
DOI - 10.1002/j.2333-8504.1997.tb01730.x
Subject(s) - statistic , variation (astronomy) , item response theory , wright , language proficiency , test (biology) , diagnostic test , equating , mathematics education , statistics , psychology , computer science , psychometrics , mathematics , medicine , paleontology , emergency medicine , physics , astrophysics , rasch model , biology , programming language
A new procedure for generating instructionally‐relevant diagnostic feedback is proposed. The approach involves first constructing a strong model of student proficiency and then testing whether individual students' observed item response vectors are consistent with that model. Diagnoses are specified in terms of the combinations of skills needed to score at increasingly higher levels on a tests's reported score scale. The approach is applied to the problem of developing diagnostic feedback for the SAT I Verbal Reasoning Test. Using a variation of Wright's (1977) person‐fit statistic, it is shown that the estimated proficiency model accounts for 91% of the “explainable” variation is students' observed item response vectors.