Proficiency Scaling Based on Conditional Probability Functions for Attributes

Abstract

This study introduces procedures for constructing a proficiency scale for a large-scale test by applying Tatsuoka's Rule Space Model. The SAT mathematics (SAT M), Section II, is used for illustrating the process and the results. A task analysis is summarized in a mapping sentence, and then 14 processess and content attributes are identified for explaining the underlying cognitive aspects of the examinees' performance on the SAT M. Analysis results show that almost 98% of 2,334 examinees are successfully classified into one of 468 cognitive states. The cognitive states are characterized by mastery or non- mastery of the 14 attributes. Attribute Characteristic Curves, which are conditional probability functions defined on the SAT Scale, are introduced and used for interpreting an examinee's proficiency. Prototypes of a student's performance report and a group performance report are given as examples of possible ways for summarizing the analysis results.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1993
Accession Number
ADA273816

Entities

People

  • Charles Lewis
  • Kathleen Sheehan
  • Kikumi Tatsuoka
  • Menucha Birenbaum

Organizations

  • Educational Testing Service

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Cognition
  • Cognitive Science
  • Computer Programs
  • Data Science
  • Databases
  • Factor Analysis
  • Information Processing
  • Information Science
  • Mental Processes
  • Military Research
  • Probability
  • Psychology
  • Regression Analysis
  • Statistical Algorithms
  • Statistical Analysis
  • Students
  • Two Dimensional

Readers

  • Psychometric Testing or Psychological Assessment.
  • Regression Analysis.
  • Systems Analysis and Design

Technology Areas

  • Space