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Reducing Racial and Gender Gaps in Mathematics Attitudes: Investigating the Use of Instructional Strategies in Inclusive STEM High Schools

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Abstract

Inclusive STEM (science, technology, engineering, and mathematics) schools operate with a mission to increase and broaden participation in STEM among all students, particularly girls and students from under-represented ethnic groups (e.g., ethnic/racial minorities). As such, inclusive STEM schools promote various instructional strategies, such as risk-taking, autonomy, and technology use, to help peak diverse students’ interests and achievement in STEM subjects. However, little research has investigated how these instructional strategies are implemented in inclusive STEM school settings, and whether these strategies reduce racial and gender gaps in students’ mathematics attitudes. The current study uses hierarchical linear regression analyses to investigate associations between such strategies (i.e., student autonomy, cooperation and teamwork, technology use, risk taking, and cognitively-demanding work) and students’ attitudes toward mathematics. Results indicate that higher levels of risk-taking in mathematics classes were associated with more positive mathematics attitudes for all students. Girls and African American students reported more positive mathematics attitudes compared to boys and White students when they experienced higher levels of autonomy in their mathematics classes. These findings suggest that some instructional strategies should be examined further for their potential to reduce persistent gaps seen in mathematics attitudes.

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Notes

  1. Please refer to the website: http://outlier.uchicago.edu/s3/findings/roadmap/ for more information regarding the theory of action.

  2. The Elements include (1) problem-based learning (PBL); (2) rigorous learning; (3) personalization of learning; (4) career, technology, and life skills; (5) school community and belonging; (6) external community; (7) staff foundations; and (8) essential factors (LaForce et al. 2016).

  3. For both mathematics intrinsic motivation and mathematics ability beliefs, we reported unstandardized coefficients (B) in the original units of the scales corresponding to each variable, in the text. Standardized coefficients (β) were not reported, yet available from the authors upon request. Moreover, only significant findings were reported in text (please see tables for other non-significant findings).

  4. Coefficients for simple slopes generated by “Interaction!” program were only reported in text, not in tables.

  5. The current study emphasized the use of instructional strategies within the context of inclusive STEM schools in relation to gender and race/ethnicity gaps on students’ mathematics attitudes. Thus, we did not focus on discussing intersectionality theories or provide a thorough discussion of individual and social contexts related to intersectionality. However, we provided additional intersectional analysis for those who are interested.

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Acknowledgements

This research was supported by a grant from the National Science Foundation (1238552).

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  1. Outlier Research & Evaluation, UChicago STEM Education, University of Chicago, 1427 E 60th St., Chicago, IL, 60637, USA

    Huifang Zuo, Kaitlyn A. Ferris & Melanie LaForce

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  1. Huifang Zuo
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Appendix 1

Appendix 1

Intersectional Analyses

An intersectional approach was employed to explore the interactive effect of gender and race/ethnicity in relation to instructional strategies. This investigation was not the primary focus of the present study; however, we believe that it is important to acknowledge the confounding, and overlapping, effects of these demographic characteristics in relation to instructional strategies and mathematics-related outcomes. As such, we have chosen to present these preliminary results here (see Table 5 for model fit indices and Table 6 for all statistics) as we prepare a follow-up manuscript, which will discuss these results in greater detail and be accompanied by supporting theoretical frameworks and empirical evidence (e.g., Else-Quest and Hyde 2016a, b).

Table 5 Model fit indices for students’ mathematics intrinsic motivation and ability beliefs
Full size table
Table 6 Results for mathematics intrinsic motivation and ability beliefs final model (Step 8) considering intersectional analysis between gender and race/ethnicity
Full size table

Hierarchical multiple-regression analyses were used to investigate associations between the five instructional strategies and students’ mathematics attitudes considering intersectionality between gender and race/ethnicity (e.g., Hispanic*Female). Two separate eight-step models were used to investigate mathematics intrinsic motivation and mathematics ability beliefs outcome variables. In both models, variables representing the intersection of gender and race/ethnicity (e.g., Hispanic*Female) were entered at step 1. Variables entered at step 2–8 were replicated from the models described above (see the section of Analytical Strategy section). The current models differed in that the interaction terms between gender identity, or race/ethnicity, and each STEM school instructional strategy (e.g., step 3: autonomy*gender; autonomy*race/ethnicity) were now replaced by interaction terms accounting for intersectionality (e.g., step 3: autonomy*Hispanic*Female). Please contact the authors for a more in-depth discussion of these findings.Footnote 5

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Zuo, H., Ferris, K.A. & LaForce, M. Reducing Racial and Gender Gaps in Mathematics Attitudes: Investigating the Use of Instructional Strategies in Inclusive STEM High Schools. Journal for STEM Educ Res 3, 125–146 (2020). https://doi.org/10.1007/s41979-019-00021-y

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