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Testing the association of growth mindset and grades across a challenging transition: Is growth mindset associated with grades?

Yue Li and Timothy C. Bates

Intelligence, 2020, vol. 81, issue C

Abstract: Mindset theory predicts that whether students believe basic ability is greatly malleable exerts a major influence on their own educational attainment (Blackwell, Trzesniewski, & Dweck, 2007). We tested this prediction in two near-replication studies (total n = 832). In study 1 we tested the association of mindset with university grades in a cross-sectional design involving self-reported grades for 246 undergraduates. Growth mindset showed no association with grades (β = −0.02 CI95 [−0.16, 0.12], t = −0.26, p = .792). In study 2, we implemented a longitudinal design, testing the association of mindset with grade transcript scores across a series of challenging transitions: from high school to university entry, and then across all years of an undergraduate degree (n = 586). Contrary to prediction, mindset was not associated with grades across the challenging transition from high-school to the first year of university (β = −0.05 CI95 [−0.14, 0.05], t = −0.95, p = .345). In addition, mindset was unrelated to entry grades (p = .808). And no support was found for a predicted interaction of mindset with academic disadvantage across the transition (β = −0.03 CI95 [−0.12, 0.07], t = −0.54, p = .592). Follow-up analyses showed no association of mindset with improvement in grades at any subsequent year of the degree (minimum p-value 0.591). Jointly, these two near-replication studies suggest that, even across challenging transitions, growth mindset is either unrelated to educational attainment or has a very small negative influence.

Keywords: Intelligence-mindset; Educational attainment; Growth mindset; Challenging transitions (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intell:v:81:y:2020:i:c:s0160289620300490

DOI: 10.1016/j.intell.2020.101471

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