Cognitive Validity: Can Multiple-Choice Items Tap Historical Thinking Processes?

2017 ◽  
Vol 54 (6) ◽  
pp. 1256-1287 ◽  
Author(s):  
Mark D. Smith
Keyword(s):  
Multiple Choice ◽  
Historical Thinking ◽  
Cognitive Validity ◽  
Thinking Processes ◽  
Multiple Choice Items

Certainty-Based Marking on Multiple-Choice Items: Psychometrics Meets Decision Theory

Psychometrika ◽  
2021 ◽  
Author(s):  
Qian Wu ◽  
Monique Vanerum ◽  
Anouk Agten ◽  
Andrés Christiansen ◽  
Frank Vandenabeele ◽  
...  
Keyword(s):  
Decision Theory ◽  
Multiple Choice ◽  
Multiple Choice Items

What's Wrong with Three-Option Multiple Choice Items?

1987 ◽  
Vol 47 (2) ◽  
pp. 513-522 ◽  
Author(s):  
Steven V. Owen ◽  
Robin D. Froman
Keyword(s):  
Multiple Choice ◽  
Multiple Choice Items

scholarly journals FREE-RESPONSE AND MULTIPLE-CHOICE ITEMS: MEASURES OF THE SAME ABILITY?

1990 ◽  
Vol 1990 (1) ◽  
pp. i-29 ◽  
Author(s):  
Randy Elliot Bennett ◽  
Donald A. Rock ◽  
Minhwei Wang
Keyword(s):  
Multiple Choice ◽  
Free Response ◽  
Multiple Choice Items

Detecting Rater Biases in Sparse Rater-Mediated Assessment Networks

2021 ◽  
pp. 001316442098810
Author(s):  
Stefanie A. Wind ◽  
Yuan Ge
Keyword(s):  
Multiple Choice ◽  
Complete Data ◽  
Performance Assessments ◽  
Model Estimation ◽  
Different Types ◽  
Multiple Choice Items ◽  
Practical Constraints

Practical constraints in rater-mediated assessments limit the availability of complete data. Instead, most scoring procedures include one or two ratings for each performance, with overlapping performances across raters or linking sets of multiple-choice items to facilitate model estimation. These incomplete scoring designs present challenges for detecting rater biases, or differential rater functioning (DRF). The purpose of this study is to illustrate and explore the sensitivity of DRF indices in realistic sparse rating designs that have been documented in the literature that include different types and levels of connectivity among raters and students. The results indicated that it is possible to detect DRF in sparse rating designs, but the sensitivity of DRF indices varies across designs. We consider the implications of our findings for practice related to monitoring raters in performance assessments.

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