Campus Units

Psychology

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

1-1-2020

Journal or Book Title

Learning and Individual Differences

Volume

77

First Page

101815

DOI

10.1016/j.lindif.2019.101815

Abstract

Claiming that high levels of an independent variable represent a necessary-but-not-sufficient condition for an outcome suggests that the outcome is only possible – but not guaranteed – with high levels of that variable. Necessary condition analysis (NCA) allows researchers to determine if an observed relation between an independent variable and a dependent variable is consistent with such a necessary-but-not-sufficient relation. Using both archival and primary data, we apply Dul's (2016) necessary condition analysis techniques to common correlates of academic success in college. We find data patterns that are consistent with necessary-but-not-sufficient conditions for academic success for a variety of variables including class attendance, grit-perseverance, growth mindset, prior achievement, and admissions test scores. Our findings imply that some individual characteristics and behaviors may constrain the level of grades possible in college and that researchers may benefit from considering necessity models of academic performance. We discuss further applications of necessary condition analysis in educational research as a supplement to traditional data analysis.

Comments

This accepted article is published as Tynan, M.C., Crede, M., Harms, P.D., Are individual characteristics and behaviors necessary-but-not-sufficient conditions for academic success?: A demonstration of Dul's (2016) necessary condition analysis. Learning and Individual Differences. 77(2020); 101815. DOI: 10.1016/j.lindif.2019.101815. Posted with permission.

Copyright Owner

Elsevier

Language

en

File Format

application/pdf

Available for download on Friday, January 01, 2021

Published Version

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