Research
Many everyday skills such as writing a budget, altering a recipe, taking medication, deciding on health insurance or understanding ones' bills require a basic proficiency in mathematics. Indeed, demonstrating this basic proficiency is linked to overall quality of life. Unfortunately, in the U.S. many school districts struggle to get students to proficiency in math by the time of their high school graduation. Thus, it is crucial to understand why some students struggle more than others in math and science, how we might provide students with meaningful learning opportunities, and evaluate how these opportunities help students excel.
I am broadly interested in how students learn math and how we can use psychological science to improve students' educational outcomes. To do this, I employ the Opportunity  Propensity model (Byrnes & MillerCotto, 2016) to examine variables, or opportunities (e.g. books at home, exposure to math games, reformed instruction) and propensities (e.g., prior knowledge, executive functions, or motivation), that explain success and struggle in mathematics. I use aspects of this theoretical framework to systematically test how opportunities and propensities interact in classrooms to better refine this model through experimental designs and evaluating interventions. In this way, I view my research program as an iterative process: first building and testing theory, then zooming in to empirically test aspects of the theory in isolation, and zooming back out to refine the theory.
Through my research I have identified two important propensity factors related to learning and performance in math: students' prior knowledge and their executive function (the ability to regulate and control actions and cognitions). As such, I am particularly interested in the codevelopment of these two constructs and how they promote or inhibit learning. With this in mind, I hope to answer two specific questions:
Papers associated with these lines of work are listed below, with links to these papers in the Publications tab above.
I am broadly interested in how students learn math and how we can use psychological science to improve students' educational outcomes. To do this, I employ the Opportunity  Propensity model (Byrnes & MillerCotto, 2016) to examine variables, or opportunities (e.g. books at home, exposure to math games, reformed instruction) and propensities (e.g., prior knowledge, executive functions, or motivation), that explain success and struggle in mathematics. I use aspects of this theoretical framework to systematically test how opportunities and propensities interact in classrooms to better refine this model through experimental designs and evaluating interventions. In this way, I view my research program as an iterative process: first building and testing theory, then zooming in to empirically test aspects of the theory in isolation, and zooming back out to refine the theory.
Through my research I have identified two important propensity factors related to learning and performance in math: students' prior knowledge and their executive function (the ability to regulate and control actions and cognitions). As such, I am particularly interested in the codevelopment of these two constructs and how they promote or inhibit learning. With this in mind, I hope to answer two specific questions:
 What educational or home opportunities promote students' learning or executive function development as it relates to math?
 How do these experiences differ by race/ethnicity and family income?
 How do these experiences differ by race/ethnicity and family income?
 What is the nature and the relationship of math ability and executive functions?
Papers associated with these lines of work are listed below, with links to these papers in the Publications tab above.
What educational or home opportunities promote students' math or science learning or executive function development?
 MillerCotto, D., & Auxter, A. E. (2019). Testing the ecological validity of faded worked examples in algebra. Educational Psychology.
 Byrnes, J.P., Wang, A. H., & MillerCotto, D. (2019). Children as mediators of their own cognitive development in kindergarten. Cognitive Development, 50, 8097.
 Barbieri, C. A., MillerCotto, D., & Booth, J. L. (2019). Lessening the load of misconceptions: Designbased principles for algebra learning. Journal of the Learning Sciences.
 Byrnes, J. P., MillerCotto, D., & Wang, A. H. (2018). Children as mediators of their own development: The case of learning science in kindergarten and first grade. Journal of Cognition and Development, 19, 248 – 277.
 Byrnes, J. P., & MillerCotto, D. (2016). The growth of mathematics and reading skills in segregated and diverse schools: An opportunitypropensity analysis of a national database. Contemporary Educational Psychology, 46, 3451.
What is the nature and the relationship of math ability and executive functions?
 MillerCotto, D., & Byrnes, J. P. (2020). What’s the best way to characterize the relationship between working memory and achievement?: An initial examination of competing theories. Journal of Educational Psychology.
Methodological Interest: MetaAnalyses
As a third related research area, I am interested in using metaanalytic methods to advance transparency and reproducibility in the developmental and education sciences. I have received additional training in metaanalytic methods through the Institute for Education Sciences' (IES) MetaAnalytical Training Institute. I continue to publish work and refine my methodological skills in this area.

 Wang, M.T., Smith, L.V., MillerCotto, D., & Huguley, J.P. (2020). Parent racialethnic socialization practices and and children of color's academic outcomes. Child Development. [here].
 MillerCotto, D. (2019). Working memory: A reliability analysis of measures within mathematics in grade school children in the United States. Presented at the Mathematical Cognition and Learning Society (MCLS) Second Annual Meeting, Ottawa, ON.
 MillerCotto, D., & Byrnes, J. P. (2016). Ethnic/racial identity and academic achievement: A metaanalytic review. Developmental Review, 41, 5170.