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A transition evaluation model with probability-based effectiveness indicators-a new measurement model for

Pujue Wang1, Yuting Han2,3,4, Hongyun Liu5,6

  • 1Beijing Key Laboratory of Learning and Cognition, School of Psychology, Capital Normal University, Beijing, China.

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Summary
This summary is machine-generated.

This study introduces new probability-based effectiveness indicators and the Transition Evaluation Model (TEM) for analyzing complex problem-solving data. TEM offers improved accuracy and interpretability in assessing problem-solving abilities from action sequences.

Keywords:
Probability-based effectiveness indicatorsProblem-solving assessmentProcess dataState and transition effectivenessTransition evaluation model

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Area of Science:

  • Educational Measurement
  • Psychometrics
  • Cognitive Science

Background:

  • Computer-based tasks generate rich process data on problem-solving behaviors.
  • Process-based measurement models analyzing action sequences are emerging for ability estimation.
  • Existing effectiveness indicators in these models have limitations in range and flexibility.

Purpose of the Study:

  • To introduce novel probability-based effectiveness indicators: state effectiveness (ps) and transition effectiveness (Δps→s').
  • To develop and validate the Transition Evaluation Model (TEM) using these indicators.
  • To enhance the analysis of complex problem-solving assessments.

Main Methods:

  • Developed probability-based state (ps) and transition (Δps→s') effectiveness indicators.
  • Validated indicators using PISA 2012 problem-solving assessment data.
  • Constructed and tested the Transition Evaluation Model (TEM) through simulations and empirical data.

Main Results:

  • Probability-based indicators offer a broader numerical range for finer discrimination.
  • TEM demonstrated robust parameter estimation, good model-data fit, and high accuracy.
  • TEM outperformed existing models (SRM, SRMM, SRM-PEI) in model-data fit and interpretability.

Conclusions:

  • Probability-based effectiveness indicators enhance process-based measurement models.
  • TEM provides a more nuanced and interpretable approach to analyzing problem-solving data.
  • These advancements offer valuable tools for complex assessment analysis.