Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
April 24, 2024Journal of Educational MeasurementOpen Access

A One‐Parameter Diagnostic Classification Model with Familiar Measurement Properties

View Full Paper
Ask AI
Bookmark
Share

Authors

MMMatthew J. MadisonSWStefanie A. WindLMLientje Maas

Discussion

Loading...

Member takes

Overview

Psychometric evaluation reveals invariant ordering and sum score sufficiency in student mathematics assessments, suggesting improved diagnostic feedback.

Key Points

  • A one-parameter diagnostic classification model achieves sum score sufficiency and invariant item ordering, matching the core measurement properties of standard Rasch models.
  • Analysis of empirical records from a large-scale mathematics education research study confirms that the functional form accurately classifies latent characteristics.
  • These findings support the use of item response theory principles in classroom formative assessment, enabling targeted diagnostic feedback with simplified scoring.

Cite This Study

Madison et al. (2024) studied this question.

synapsesocial.com/papers/68e6dc34b6db6435876587d8https://doi.org/10.1111/jedm.12390
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A Comparison of Mixed and Partial Membership Diagnostic Classification Models with Multidimensional Item Response Models2024 · 5 citations
  2. 2Improving Instructional Decision‐Making Using Diagnostic Classification Models2024 · 2 citations
  3. 3Improving Instructional Decision-Making Using Diagnostic Classification Models2024
  4. 4A Sequential General Nonparametric Classification Method for Polytomous Responses2025
  5. 5Optimizing Large‐Scale Mathematical Assessments: Leveraging Hierarchical Attribute Structures and Diagnostic Classification Models for Enhanced Student Diagnostics2026