ERIC Number: EJ1455868
Record Type: Journal
Publication Date: 2024-Dec
Pages: 11
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0731-1745
EISSN: EISSN-1745-3992
Improving Instructional Decision-Making Using Diagnostic Classification Models
W. Jake Thompson; Amy K. Clark
Educational Measurement: Issues and Practice, v43 n4 p146-156 2024
In recent years, educators, administrators, policymakers, and measurement experts have called for assessments that support educators in making better instructional decisions. One promising approach to measurement to support instructional decision-making is diagnostic classification models (DCMs). DCMs are flexible psychometric models that facilitate fine-grained reporting on skills that students have mastered. In this article, we describe how DCMs can be leveraged to support better decision-making. We first provide a high-level overview of DCMs. We then describe different methods for reporting results from DCM-based assessments that support decision-making for different stakeholder groups. We close with a discussion of considerations for implementing DCMs in an operational setting, including how they can inform decision-making at state and local levels, and share future directions for research.
Descriptors: Decision Making, Instructional Improvement, Evaluation Methods, Models, Classification, Teaching Methods, Diagnostic Tests, Stakeholders
Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://bibliotheek.ehb.be:2191/en-us
Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A