Adaptive Pairwise Comparison for Educational Measurement
Elise A. V. Crompvoets,
Anton A. Béguin and
Klaas Sijtsma
Additional contact information
Elise A. V. Crompvoets: Tilburg University
Anton A. Béguin: Cito
Klaas Sijtsma: Tilburg University
Journal of Educational and Behavioral Statistics, 2020, vol. 45, issue 3, 316-338
Abstract:
Pairwise comparison is becoming increasingly popular as a holistic measurement method in education. Unfortunately, many comparisons are required for reliable measurement. To reduce the number of required comparisons, we developed an adaptive selection algorithm (ASA) that selects the most informative comparisons while taking the uncertainty of the object parameters into account. The results of the simulation study showed that, given the number of comparisons, the ASA resulted in smaller standard errors of object parameter estimates than a random selection algorithm that served as a benchmark. Rank order accuracy and reliability were similar for the two algorithms. Because the scale separation reliability (SSR) may overestimate the benchmark reliability when the ASA is used, caution is required when interpreting the SSR.
Keywords: adaptive measurement; comparative judgment; holistic measurement; pairwise comparison (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/1076998619890589 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:45:y:2020:i:3:p:316-338
DOI: 10.3102/1076998619890589
Access Statistics for this article
More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications (sagediscovery@sagepub.com).