Math Attitudes, Engagement, and Performance of High School Students on High and Low-stakes Tests of Statistics Knowledge

Understanding the extent engagement and math attitudes predict performance in statistics courses could inform educational interventions in this subject area, which has growing demand. We examined direct and indirect associations between course engagement-related constructs, math attitudes, and learn...

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Bibliographic Details
Published inJournal for STEM education research. Vol. 5; no. 3; pp. 402 - 438
Main Authors Ober, Teresa M., Brodersen, Alex S., Rebouças-Ju, Daniella, Hong, Maxwell R., Carter, Matthew F., Liu, Cheng, Cheng, Ying
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 01.12.2022
Springer Nature B.V
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Summary:Understanding the extent engagement and math attitudes predict performance in statistics courses could inform educational interventions in this subject area, which has growing demand. We examined direct and indirect associations between course engagement-related constructs, math attitudes, and learning outcomes. Confirmatory factor analysis was used to validate scores from measures of these constructs with a sample of high school students enrolled in Advanced Placement (AP) statistics ( N  = 720, mean age = 16.8 years, SD = 0.82). Structural equation models were fitted to the data to examine relations between these constructs on a subsample ( N  = 220). A greater proportion of variation was explained in a high-stakes learning outcome ( R 2  = 0.54) than a low-stakes learning outcome ( R 2  = 0.24). We found some evidence of indirect effects of academic procrastination and course engagement on the learning outcome by way of math attitudes. The findings shed light on opportunities for intervention on academic maladaptive behaviors, such as procrastination, which could lessen negative effects on math attitudes and learning. These findings highlight the importance of testing stakes when examining associations between engagement, math attitudes, and learning, particularly in the context of high school statistics, a growing and yet understudied STEM learning context.
ISSN:2520-8705
2520-8713
DOI:10.1007/s41979-022-00076-4