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Standard-Setting Procedures for Counts Data.

Rianne Janssen1, Jorge Gonzalez, Ernesto San Martin

  • 1Rianne Janssen, Centre of Educational Effectiveness and Evaluation, KU Leuven, Belgium, rianne.janssen@kuleuven.be.

Journal of Applied Measurement
|May 24, 2019
PubMed
Summary

Two new methods, examinee- and item-centered, set cut scores for count data using the Rasch Poisson Counts Model (RPCM). These procedures were demonstrated in a study on mental arithmetic for primary students.

Area of Science:

  • Educational Measurement
  • Psychometrics
  • Statistical Modeling

Background:

  • Setting accurate cut scores is crucial for educational assessment.
  • Existing methods may not fully capture nuances in count data.
  • The Rasch Poisson Counts Model (RPCM) offers a robust framework for analyzing count data.

Purpose of the Study:

  • To propose and evaluate two novel procedures for setting cut scores for count data.
  • To apply these methods within the framework of the Rasch Poisson Counts Model (RPCM).
  • To illustrate the practical application of these procedures in a real-world educational setting.

Main Methods:

  • An examinee-centered procedure, adapting Longford's (1996) approach, links contrasting-groups judgments to the RPCM ability scale via random logistic regression.

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  • An item-centered procedure involves judges specifying the minimum performance level (minimum correct responses or maximum errors) for a minimally competent student.
  • Both methods utilize the RPCM to model the counts data and estimate the position of the minimally competent student on the ability scale.

    • Main Results:

    • The study successfully illustrated both the examinee-centered and item-centered procedures.
    • The application demonstrated the feasibility of using these RPCM-based methods for standard-setting.
    • The methods provide a structured approach to defining performance standards based on count data.

    Conclusions:

    • The proposed examinee- and item-centered procedures offer effective approaches for setting cut scores with count data.
    • These methods, grounded in the Rasch Poisson Counts Model, enhance the precision and interpretability of educational assessments.
    • The study highlights the utility of these novel techniques in practical standard-setting scenarios, particularly in areas like mental arithmetic assessment.