Scale Evaluation and Eligibility Determination of a Field-Test Version of the Assessment, Evaluation, and Programming System Third Edition

Author:

Toland Michael D.1,Grisham Jennifer2,Waddell Misti3,Crawford Rebecca4,Dueber David M.2

Affiliation:

1. University of Toledo, OH, USA

2. University of Kentucky, Lexington, USA

3. University of Oregon, Eugene, USA

4. Eastern Kentucky University, Richmond, USA

Abstract

Rasch and classification analyses on a field-test version of the Assessment, Evaluation, and Programming System Test—Third Edition (AEPS-3), a curriculum-based assessment used to assess young children birth to age 6 years, were conducted. First, an evaluation of the psychometric properties of data from each developmental area of an AEPS-3 field-test version was conducted. Next, cutoff scores at 6-month age intervals were created and then the validity of the cutoff scores was evaluated. Results using Rasch modeling indicated acceptable model fit statistics with reasonable reliability estimates within each developmental area. Classification results showed cutoff scores accurately classified a high percentage of eligible children. Findings suggest that scores from a field-test version of the AEPS-3 are reliable within developmental areas. To the extent allowed by state criteria, early childhood interventionists could possibly use a new field-test version of the AEPS-3 to determine or corroborate eligibility for special education services.

Funder

Early Intervention Management and Research Group

Publisher

SAGE Publications

Subject

Public Health, Environmental and Occupational Health,Education

Reference11 articles.

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1. Evaluation Model of Art Design Intelligent Education System Based on Grey Relational Analysis;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2024

2. Establishing performance standards for child development: learnings from the ECDI2030;Journal of Health, Population and Nutrition;2023-12-12

3. An Evaluation of the Online Social Learning Environment Instrument (OSLEI) Using Rasch Model Analysis;SAGE Open;2022-04

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