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A Big Five-Based Multimethod Social and Emotional Skills Assessment: The Mosaic™ by ACT® Social Emotional Learning Assessment

Authors :
Kate E. Walton
Jeremy Burrus
Dana Murano
Cristina Anguiano-Carrasco
Jason Way
Richard D. Roberts
Source :
Journal of Intelligence, Vol 10, Iss 4, p 72 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

A focus on implementing social and emotional (SE) learning into curricula continues to gain popularity in K-12 educational contexts at the policy and practitioner levels. As it continues to be elevated in educational discourse, it becomes increasingly clear that it is important to have reliable, validated measures of students’ SE skills. Here we argue that framework and design are additional important considerations for the development and selection of SE skill assessments. We report the reliability and validity evidence for The Mosaic™ by ACT® Social Emotional Learning Assessment, an assessment designed to measure SE skills in middle and high school students that makes use of a research-based framework (the Big Five) and a multi-method approach (three item types including Likert, forced choice, and situational judgment tests). Here, we provide the results from data collected from more than 33,000 students who completed the assessment and for whom we have data on various outcome measures. We examined the validity evidence for the individual item types and the aggregate scores based on those three. Our findings support the contribution of multi-method assessment and an aggregate score. We discuss the ways the field can benefit from this or similarly designed assessments and discuss how the assessment results can be used by practitioners to promote programs aimed at stimulating students’ personal growth.

Details

Language :
English
ISSN :
10040072 and 20793200
Volume :
10
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Journal of Intelligence
Publication Type :
Academic Journal
Accession number :
edsdoj.0ca230027d304a5683f77a4cdcb40cf4
Document Type :
article
Full Text :
https://doi.org/10.3390/jintelligence10040072