ERIC Number: ED635138
Record Type: Non-Journal
Publication Date: 2023
Pages: 107
Abstractor: As Provided
ISBN: 979-8-3797-0759-0
ISSN: N/A
EISSN: N/A
Available Date: N/A
Student-Group Item Parameter Drift Impact on Individual and Aggregate Observed Scores
Hess, Jessica
ProQuest LLC, Ph.D. Dissertation, University of Kansas
This study was conducted to further research into the impact of student-group item parameter drift (SIPD) --referred to as subpopulation item parameter drift in previous research-- on ability estimates and proficiency classification accuracy when occurring in the discrimination parameter of a 2-PL item response theory (IRT) model. Using Monte Carlo simulation, several factors were manipulated and examined for impact including (1) direction of drift within the discrimination parameter, (2) true ability of student-groups, and (3) relative size of student-groups. ANOVA, including main effects and interaction effects, is used to evaluate bias in individual ability estimates, aggregate ability estimates, bias in percent proficient, and change in percent proficient. Results indicated that SIPD occurring in the discrimination parameter does impact bias in several ways; most substantially in percent proficient classification accuracy but less substantially on individual and aggregate ability estimates. Together, with findings from previous research about the impact of this phenomenon in the difficulty parameter, SIPD should be a concern for state level assessment and accountability decision makers as it has the potential to lead to inaccurate decisions regarding student performance. Suggestions for next steps when SIPD is suspected are provided. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com.bibliotheek.ehb.be/en-US/products/dissertations/individuals.shtml.]
Descriptors: Test Items, Groups, Ability, Item Response Theory, Bias, Classification, Computation, Scores
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Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: N/A
Audience: N/A
Language: English
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