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Related Experiment Video

Updated: Sep 17, 2025

Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective
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A cognitive diagnosis model for disengaged behaviors.

Benjamin Lugu1, Wenjing Guo2, Wenchao Ma3

  • 1Department of Educational Studies in Psychology, Research Methodology, and Counseling, The University of Alabama, Tuscaloosa, AL, 35401, USA. bklugu@crimson.ua.edu.

Behavior Research Methods
|July 1, 2025
PubMed
Summary

This study introduces a new cognitive diagnosis model that accounts for student disengagement, improving accuracy in assessing skills. The disengaged behavior cognitive diagnosis model (DB-CDM) effectively identifies disengaged students and their true proficiencies.

Keywords:
Cognitive diagnosis modelDisengaged behaviorsMissing responsesRapid guessingSolution behavior

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Area of Science:

  • Educational Measurement
  • Psychometrics
  • Cognitive Psychology

Background:

  • Cognitive diagnosis assessments are vital for formative evaluation.
  • Student disengagement, including guessing and omissions, can bias results.
  • Existing models often overlook engagement, assuming responses solely reflect proficiency.

Purpose of the Study:

  • To propose a novel disengaged behavior cognitive diagnosis model (DB-CDM).
  • To simultaneously model both engaged and disengaged student behaviors.
  • To evaluate the DB-CDM's performance in accurately assessing student proficiencies.

Main Methods:

  • Developed the disengaged behavior cognitive diagnosis model (DB-CDM).
  • Conducted simulation studies to assess parameter recovery and student identification.
  • Analyzed empirical data to compare DB-CDM with existing models and validate findings.

Main Results:

  • DB-CDM demonstrated good item parameter recovery, particularly with larger sample sizes.
  • The model accurately identified disengaged students, even under challenging conditions.
  • Engaged students showed lower rates of guessing/omission and higher solution behavior compared to disengaged students.

Conclusions:

  • The DB-CDM effectively accounts for disengaged behaviors in cognitive diagnosis.
  • This model offers improved attribute classification accuracy compared to traditional methods.
  • DB-CDM provides valuable insights for educational measurement when disengagement is present.