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An Item Response Model for True-False Exams Based on Signal Detection Theory.

Lawrence T DeCarlo¹

¹Columbia University, New York, NY, USA.

Applied Psychological Measurement

|April 29, 2020

Summary

This summary is machine-generated.

Signal detection theory (SDT) models true-false exams as a task of detecting true signals from false noise. This approach uniquely incorporates examinee perceptions into test analysis, offering a new perspective on item difficulty and bias.

Keywords:

grade of membership item bias item difficulty item guessing item response models signal detection theory true–false exams

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Area of Science:

Educational Measurement
Psychometrics
Cognitive Psychology

Background:

True-false exams are common assessment tools.
Traditional models like Item Response Theory (IRT) do not fully capture the cognitive processes involved.
Signal Detection Theory (SDT) offers a framework for understanding decision-making under uncertainty.

Purpose of the Study:

To conceptualize true-false exams as a signal detection task.
To develop an SDT-based model for analyzing true-false test performance.
To compare the SDT model with existing Item Response Theory (IRT) and Grade of Membership (GOM) models.

Main Methods:

Framing the true-false exam as a signal detection task.
Utilizing SDT principles to model examinee response processes.
Comparing the proposed SDT model with IRT and GOM models using an algebra exam dataset.

Main Results:

The SDT model explicitly incorporates examinees' perceptions and decision thresholds.
SDT offers a distinct perspective on item characteristics like difficulty and guessing, viewing them as manifestations of item bias.
The application to an algebra exam demonstrates the model's utility and provides comparative insights.

Conclusions:

Signal Detection Theory provides a valuable alternative framework for analyzing true-false exams.
SDT's emphasis on perceptual and decision components offers a more nuanced understanding of examinee responses.
The SDT approach can potentially refine psychometric analyses by accounting for subjective examinee perceptions.