66.055 - Using National and International Data Sets to Explore Young Adult Outcomes

Session Type: Paper Session

Abstract

The four papers in this session illustrate how data from national and international datasets may be used to explore young adult outcomes. Researchers use these data to examine how characteristics of assigned homework were related to advanced mathematics achievement and attitudes toward advanced mathematics among 12th grade students in the United States; to explore factors affecting the career development process of American youth; to explore how workplace reading, writing, and numeracy-based activities differ among youth aged 16 to 24 in Canada; and to describe post-education experiences for young adults with disabilities who are successful at meeting initial education goals. The papers use a variety of analytic approaches, including multivariate and multinomial logistic regression and latent class analysis.

Sub Unit

• SIG-Advanced Studies of National Databases

Papers

• Homework Characteristics as Predictors of Advanced Math Achievement and Attitude Among U.S. 12th-Grade Students - Thomas J. Smith, Northern Illinois University; Cornelius McKenna, Kishwaukee College; David A. Walker, Northern Illinois University

• Change/Stability in American Youth Occupational Expectations - Maria Adamuti-Trache, The University of Texas - Arlington; Yi Leaf Zhang, University of Texas at Arlington

• Varieties of Youth Employment: A Typology of Everyday Skill-Based Activities at Work - Michelle Yue Chen, Paragon Testing Enterprises / The University of British Columbia; Ashley Pullman, The University of British Columbia

• Young Adults With Disabilities Along Career Pathways: Findings From the Education Longitudinal Study (2002) - Margaret B. Patterson, Research Allies for Lifelong Learning

Discussant

• Daniel Losen, University of California - Los Angeles