Are Students on Track? Comparing the Predictive Validity of Administrative and Survey Measures of Cognitive and Noncognitive Skills for Long-Term Outcomes
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| Title: | Are Students on Track? Comparing the Predictive Validity of Administrative and Survey Measures of Cognitive and Noncognitive Skills for Long-Term Outcomes |
|---|---|
| Language: | English |
| Authors: | Christopher Cleveland (ORCID |
| Source: | Educational Researcher. 2025 54(4):213-225. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 13 |
| Publication Date: | 2025 |
| Sponsoring Agency: | Institute of Education Sciences (ED) |
| Contract Number: | R305B150010 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Junior High Schools Middle Schools Secondary Education Elementary Education Grade 8 Higher Education Postsecondary Education |
| Descriptors: | Middle School Students, Grade 8, Student Surveys, Self Evaluation (Individuals), Predictive Validity, Thinking Skills, Soft Skills, Long Term Memory, Graduation Rate, Cognitive Development, Longitudinal Studies, College Enrollment, Time to Degree, Academic Persistence, Strategic Planning, Educational Policy |
| DOI: | 10.3102/0013189X251321422 |
| ISSN: | 0013-189X 1935-102X |
| Abstract: | Education leaders need valid metrics to predict students' long-term success. We use a unique data set with cognitive skills, self-regulation, behavior, course performance, and test scores for eighth-grade students from a Northeast school district. We link these data to students' high school outcomes, college enrollment, persistence, and on-time degree completion. Survey-based cognitive and self-regulation measures predict high school and college outcomes. However, these relationships become small and lose statistical significance when test scores, grade point average, and an absences-suspensions index are included in the predictive models. For leaders hoping to identify the best on-track indicators for college completion, the information collected in student longitudinal data systems better predicts both short- and long-term educational outcomes than the survey-based self-regulation and cognitive measures. |
| Abstractor: | As Provided |
| IES Funded: | Yes |
| Entry Date: | 2025 |
| Accession Number: | EJ1468379 |
| Database: | ERIC |
| Abstract: | Education leaders need valid metrics to predict students' long-term success. We use a unique data set with cognitive skills, self-regulation, behavior, course performance, and test scores for eighth-grade students from a Northeast school district. We link these data to students' high school outcomes, college enrollment, persistence, and on-time degree completion. Survey-based cognitive and self-regulation measures predict high school and college outcomes. However, these relationships become small and lose statistical significance when test scores, grade point average, and an absences-suspensions index are included in the predictive models. For leaders hoping to identify the best on-track indicators for college completion, the information collected in student longitudinal data systems better predicts both short- and long-term educational outcomes than the survey-based self-regulation and cognitive measures. |
|---|---|
| ISSN: | 0013-189X 1935-102X |
| DOI: | 10.3102/0013189X251321422 |
