The human brain's ability to adapt and change in response to environmental inputs drives nearly all forms of learning throughout the lifespan. The unique plasticity of the human brain allows for the uptake of sociocultural inventions, such as reading and mathematics, through widespread changes across a range of cortical areas and white matter tracts (Dehaene, 2005; Dehaene & Cohen, 2007). As an individual spends more time in educational settings, and in particular, classrooms, they gain repeated exposure to and practice with various cultural artifacts, such as symbolic alphabets and number symbols, which in turn drives the development of the neural circuitry subserving these academic skills. Past developmental cognitive neuroscience research has led to important insights on how the developing brain changes both functionally and structurally to allow academic skills, such as reading or mathematics, to find a "neuronal niche" (Dehaene, 2005; Parkinson & Wheatley, 2015). At a structural level, learning in the brain takes place, in part, through changes in white matter tissue properties (Ekerdt et al., 2020; Sampaio-Baptista & Johansen-Berg, 2017; Wang & Young, 2014). However, the neuronal uptake of academic skills and subsequent modification of the white matter pathways underlying these skills may depend on both neurobiological differences at the individual level (Niogi & McCandliss, 2006; Tsang et al., 2009; van Eimeren et al., 2008a; Yeatman et al., 2011a) and the environmental and educational context of the individual (Huber et al., 2018; Scholz et al., 2009; Thiebaut de Schotten et al., 2014). However, these studies have primarily been conducted using relatively homogenous, convenience samples and therefore it remains unclear how individual-level factors interact with educational context to either constrain or promote both learning and white matter plasticity at a population level. Studying the link between educational experiences and white matter is crucial for understanding how the brain changes as a student progresses through school and acquires cultural abilities, such as reading or mathematics. This dissertation looks to leverage several large-scale neuroimaging and behavioral datasets to take a first step towards understanding the complex interplay between an individual's environment, brain development, and academic learning in largescale, representative samples of participants. White Matter Development and Learning: The cognitive processes underlying academic skills, such as reading and mathematics, requires the coordination of multiple, anatomically distinct brain regions and structures. Collections of long-range axonal projections, known as white matter tracts, allow for information to efficiently travel across these wide-spread brain regions, giving rise to a range of brain networks associated complex behavior. However, the properties of this white matter circuitry are not fixed from birth but rather change dynamically over the course of development. These developmental trends are not linear and in fact typically plateau after a certain age (Lebel et al., 2012) and actually begin to decline after a certain age (Yeatman et al., 2014). Interestingly, the various white matter pathways do not follow the same developmental time courses, with some tracts reaching a developmental plateau between the ages of 8 and 12, while other tracts continue to develop past the age of 20 (Lebel et al., 2019a). This developmental variation across white matter tracts suggests that some major brain networks need to mature and solidify earlier than others and that the cultural artifacts acquired over the course of education may be reflected more clearly in these developmentally slower white matter pathways. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com.bibliotheek.ehb.be/en-US/products/dissertations/individuals.shtml.]