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Academic health centers and their universities are increasingly encouraged to engage in more community-based and participatory approaches to research. Yet, traditional ethics guidelines and regulations are inadequate for addressing the dynamics of community-campus research partnerships. In this article, the authors share stories from the Community Research Collaborative (CRC), a collective of community leaders and faculty that published guidelines for community-based research (CBR). The CRC offers a case study in how a collaborative process of developing CBR guidelines can create space for partners to wrestle with the historical and present-day harms carried out in indigenous and minoritized communities in the name of science and to imagine alternative ways of working together collectively. This case study highlights the complex power dynamics inherent in community-campus partnerships and how storytelling can play a role in unearthing and addressing them. It positions the work of the CRC as incomplete and evolving while offering a foundation on which other institutions could carry out similar processes in their localities.

Children who like to read and write tend to be better at it. This association is typically interpreted as enjoyment impacting engagement in literacy activities, which boosts literacy skills. We fitted direction-of-causation models to partial data of 3690 Finnish twins aged 12. Literacy skills were rated by the twins' teachers and literacy enjoyment by the twins themselves. A bivariate twin model showed substantial genetic influences on literacy skills (70%) and literacy enjoyment (35%). In both skills and enjoyment, shared-environmental influences explained about 20% in each. The best-fitting direction-of-causation model showed that skills impacted enjoyment, while the influence in the other direction was zero. The genetic influences on skills influenced enjoyment, likely via the skills[right arrow]enjoyment path. This indicates an active gene-environment correlation: children with an aptitude for good literacy skills are more likely to enjoy reading and seek out literacy activities. To a lesser extent, it was also the shared-environmental influences on children's skills that propagated to influence children's literacy enjoyment. Environmental influences that foster children's literacy skills (e.g., families and schools), also foster children's love for reading and writing. These findings underline the importance of nurturing children's literacy skills.

The goal of the present study was to create a brief reliable scale for measuring reading anxiety in college students, a time when reading demands are particularly high. Results revealed individual differences in reading anxiety in a sample of 402 university students, showing reliable measurements from a 10-item scale and replicated in a sample of 198 undergraduates. Reading anxiety related to reading fluency, reading self-concept, self-perception of reading ability compared to others, reading enjoyment, and reading for pleasure frequency. Furthermore, higher reading anxiety was observed in students with a known learning disability compared to those without. How well each of the 10 items differentiated levels of reading anxiety were explored using a graded response model. We provide evidence for the reading-specific nature of reading anxiety by demonstrating a higher correlation between reading anxiety and reading fluency than math fluency and that reading anxiety exists separable from general and social anxiety.

Many research agencies are now requiring that data collected as part of funded projects be shared. However, the practice of data sharing in education sciences has lagged these funder requirements. We assert that this is likely because researchers generally have not been made aware of these requirements and of the benefits of data sharing. Furthermore, data sharing is usually not a part of formal training, so many researchers may be unaware of how to properly share their data. Finally, the research culture in education science is often filled with concerns regarding the sharing of data. In this article, we address each of these areas, discussing the wide range of benefits of data sharing, the many ways by which data can be shared; provide a step by step guide to start sharing data; and respond to common concerns.

In the US, undeniable evidence shows that socioeconomic inequities explain a high proportion of individual differences in school achievement. Although not all countries show this same effect due to socioeconomic status, it is consistently found that social inequities lead to achievement gaps. These achievement gaps then manifest into trajectories that set some individuals on a path of lower incomes, poorer health and higher mortality, lower wellbeing, and other poor adult outcomes. Like James Flynn so handily reminded the scientific literature that achievement gaps are explainable by environmental factors, the inequities we see around the world are based on environments some children are exposed to. In his work, Flynn stated his belief that the suppression of scientific work on intelligence would continue to lead to social inequities. We wish to take this idea and move it forward. We believe that the scientific construct of intelligence plays a key role in helping create a more equitable society through science. We also believe that the poor perception of intelligence, rooted in historical realities, means that it will continue to be misunderstood, feared, and misused, limiting how effective it could be in helping to close gaps in achievement and in creating a more equitable society.

Math anxiety (MA) and math performance are generally negatively correlated (Barroso et al., 2021; Namkung et al., 2019). However, the mechanisms underlying this negative association remain unclear. According to the attentional control theory (ACT; Eysenck et al., 2007), anxious individuals experience impaired attentional control during problem solving, which compromises their performance on cognitive tasks. In a sample of 168 elementary and middle school students, the current study used an eye-tracking approach to investigate whether math-anxious students exhibit deficits in their attentional control during a math problem solving task and whether such attentional control deficits account for the negative association between MA and performance on this math task. Consistent with the ACT, we found that students with higher MA were more likely to engage attention to both task-relevant and task-irrelevant distractors during problem solving, and their enhanced attention to these distractors was associated with their impaired performance on the math task. These findings suggest that the MA-related math performance deficit is partly mediated by impaired attentional control, which is indicated by the maladaptive attentional bias toward distracting information during math problem solving.

Noncognitive factors have gained attention in recent years as potential intervention targets for academic achievement improvement in students. Two notable facets, intelligence mindset and grit, have been of particular interest. Both have been shown to consistently improve educational outcomes, although little work has focused on reading ability. As such, we examined the relation between both grit and mindset on current, future, and change in reading comprehension ability in a twin sample. We used data from 422 twin pairs (171 monozygotic pairs, 251 dizygotic pairs) drawn from the Florida Twin Project on Reading, Behavior and Environment (Taylor et al., 2019). The racial composition of the sample included 1.00% American Indian or Alaska Native, 2.25% Asian, 13.25% Black or African American, 22.63% Hispanic, 1.00% Native Hawaiian or Other Pacific Islander, 56.13% White, and 3.75% more than 1 race. The household income of the sample at time 1 was 16.15% below $25,000, 18.06% $25,000-49,999, 36.34% $50,000-99,999, and 29.45% $100,000 or more and closely align with the overall composition reported for the state of Florida (United States Census Bureau, 2021). Twins were on average 13 years old when the questionnaire and first reading ability measure were collected, and on average 15 years old when the second reading ability measure was collected. Weak and moderate positive correlations were found between both mindset and grit and with each reading ability score and neither were significantly related to change in reading ability. Twin modeling suggested little to no common genetic or environmental influences between mindset and grit to reading ability. In total, our results do not lend support to the notion of mindset or grit being a mechanism of change for reading ability.

Open-science reforms, which aim to increase credibility and access of research, have the potential to benefit the research base in special education, as well as practice and policy informed by that research base. Awareness of open science is increasing among special education researchers. However, relatively few researchers in the field have experience using multiple open-science practices, and few practical guidelines or resources have been tailored to special education researchers to support their exploration and adoption of open science. In this article, we described and provided guidelines and resources for applying five core open-science practices--preregistration, registered reports, data sharing, materials sharing, and open-access publishing--in special education research.

Complex research questions often need large samples to obtain accurate estimates of parameters and adequate power. Combining extant data sets into a large, pooled data set is one way this can be accomplished without expending resources. Measurement invariance (MI) modeling is an established approach to ensure participant scores are on the same scale. There are two major problems when combining independent data sets through MI. First, sample sizes will often be large leading to small differences becoming noninvariant. Second, not all data sets may include the same combination of measures. In this article, we present a method that can deal with both these problems and is user friendly. It is a combination of generating random normal deviates for variables missing completely in combination with assessing model fit using the root mean square error of approximation "good enough principle," based on the hypothesis that the difference between groups is not zero but small. We demonstrate the method by examining MI across eight independent data sets and compare the MI decisions of the traditional and "good enough" approach. Our results show the approach has potential in combining educational data.

Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in organizational management that makes such insights possible. Unlike models alluded to above, DEA does not explain variance. Instead, it explains how efficiently an individual utilizes their inputs to produce outputs, and identifies which input is not being utilized optimally. This paper provides a history and usages of DEA from fields outside of education, and describes the math and processes behind it. This paper then extends DEA's usage into the educational field using a study on child reading ability. Using students from the Project KIDS dataset (n = 1987), DEA is demonstrated using a simple view of reading framework, identifying individual efficiency levels in using reading-based skills to achieve reading comprehension, determining which skills are being underutilized, and classifying new subsets of readers. New subsets of readers were identified using this method, with implications for more targeted interventions.

This manuscript provides information on datasets pertaining to Project KIDS. Datasets include behavioral and achievement data for over 4,000 students between five and twelve years old participating in nine randomized control trials of reading instruction and intervention between 2005-2011, and information on home environments of a subset of 442 students collected via parent survey in 2013. All data is currently stored on an online data repository and freely available. Data might be of interest to researchers interested in individual differences in reading development and response to instruction and intervention, as well as to instructors of data analytic methods such as hierarchical linear modeling and psychometrics.

In this study, we explore student achievement in a semester-long flipped Calculus II course, combining various predictor measures related to student attitudes (math anxiety, math confidence, math interest, math importance) and cognitive skills (spatial skills, approximate number system), as well as student engagement with the online system (discussion forum interaction, time to submission of workshop assignments, quiz attempts), in predicting final grades. Data from 85 students enrolled in a flipped Calculus II course was used in dominance analysis to determine which predictors emerged as the most important for predicting final grades. Results indicated that feelings of math importance, approximate number system (ANS) ability, total amount of discussion forum posting, and time grading peer workshop submissions was the best combination of predictors of final grade, accounting for 17% of variance in a student's final grade. The point of this work was to determine which predictors are the most important in predicting student grade, with the end goal of building a recommendation system that could be implemented to help students in this traditionally difficult class. The methods used here could be used for any class.

Researchers have identified sources of individual differences in writing across beginning and developing writers. The aim of the present study was to further clarify the sources of this variability by investigating the extent to which there are differences in genetic and environmental factors underlying the associations between lexical diversity, syntactic knowledge, and semantic cohesion knowledge in relation to writing. Differences were examined across two developmental phases of writing: beginning (i.e., elementary school) and developing (i.e., middle school). Participants included 262 twin pairs (M[subscript age]= 10.88 years) in elementary school and 247 twin pairs (M[subscript age] =13.21 years) in middle school. Twins were drawn from the Florida Twin Project on Reading, Behavior, and Environment. Biometric models were conducted separately for subgroups defined by phase of writing development. Results indicated significant etiological differences in writing components across the two phases, such that effects associated with genes and non-shared environment were greater while effects associated with shared environment were lower in developing writers as compared to beginning writers. Furthermore, results showed that child-specific environment was the largest contributor to individual differences in writing components and their covariation for both beginning and developing writers. These results imply that even direct instruction about writing in schools may be having different effects on children based on their unique experiences.

Reading and math attainment develop during elementary grades. Questions remain, though, about the co-developmental nature of the relation between reading and math. This study examined dynamic, longitudinal pathways between reading and math in first through fourth grades. Participants of the study were 554 academically at-risk children (M[subscript] age at the first assessment point = 6.57 years; SD = 0.38) from Texas Project Achieve. Children were assessed utilizing the Woodcock-Johnson--III reading and math measures. Results from dynamic bivariate latent change score models indicated unidirectional longitudinal coupling effects from reading to math. Specifically, average and high levels of reading performance were associated with subsequent gains in math growth, in particular for below average performing children in math. In contrast, low levels of reading performance had negligible or no amplifying influences on change in math growth. The nature of the dynamics was replicated even when controlling for nonverbal cognitive abilities. Results demonstrated that good reading skills pave the way for children to develop their math skills. Such findings underscore the importance of considering reading performance in treating math difficulties.

Openness is a foundational principle in science. Making the tools and products of scientific research openly accessible advances core aims and values of education researchers, such as the credibility, equity, impact, and efficiency of research. The digital revolution has expanded opportunities for providing greater access to research. In this article, we examine three open-science practices--open data and code, open materials, and open access--that education researchers can use to increase accessibility to the tools and products of research in the field. For each open-science practice, we discuss what the practice is and how it works, its primary benefits, some important limitations and challenges, and two thorny issues.

The Open Science movement has gained considerable traction in the last decade. The Open Science movement tries to increase trust in research results and open the access to all elements of a research project to the public. Central to these goals, Open Science has promoted five critical tenets: Open Data, Open Analysis, Open Materials, Preregistration, and Open Access. All Open Science elements can be thought of as extensions to the traditional way of achieving openness in science, which has been scientific publication of research outcomes in journals or books. Open Science in education sciences, however, has the potential to be much more than a safeguard against questionable research. Open Science in education science provides opportunities to (a) increase the transparency and therefore replicability of research and (b) develop and answer research questions about individuals with learning disabilities and learning difficulties that were previously impossible to answer due to complexities in data analysis methods. We will provide overviews of the main tenets of Open Science (i.e., Open Data, Open Analysis, Open Materials, Preregistration, and Open Access), show how they are in line with grant funding agencies' expectations for rigorous research processes, and present resources on best practices for each of the tenets.

The purpose of this invited paper is to show the learning disabilities field what LDbase is, why it's important for the field, what it offers the field, and examples of how you can leverage LDbase in your own work. [ABSTRACT FROM AUTHOR]

According to the hybrid model (van Bergen, van der Leij, & de Jong, 2014), the significant association among executive functioning (EF), reading, and math may be partially explained by parent-reported EF's role as a common risk and/or protective factor in reading and math (dis)abilities. The current study used a sample of 434 twin pairs (M[subscript age] = 12.12) from Florida to conduct genetically sensitive modeling on children's parent-reported EF, reading, and math skills to determine the common and unique etiological influences among the three domains. EF was measured through parent report and reading and math were measured with standardized test scores drawn from Florida's Progress Monitoring and Reporting Network as well as standardized parent-administered assessments collected by mail. Our trivariate Cholesky modeling showed that no matter which parent-reported EF component was modeled, the overlap of parent-reported EF with reading and math was explained by common genetic influences. Supplemental analysis suggested that this might in part be due to general parent report of problem behaviors. Additionally, significant environmental influences, with higher shared environmental overlap than previous work, were also found for reading and math. Findings indicate that poor parent-reported EF is a common cognitive risk factor for reading and math disabilities, which is driven by a shared genetic basis among all three domains.

The science of reading should be informed by an evolving evidence base built on the scientific method. Decades of basic research and randomized controlled trials of interventions and instructional routines have formed a substantial evidence base to guide best practices in reading instruction, reading intervention, and the early identification of at-risk readers. The recent resurfacing of questions about what constitutes the science of reading is leading to misinformation in the public space that may be viewed by educational stakeholders as merely differences of opinion among scientists. The authors' goals in this article were to revisit the science of reading through an epistemological lens to clarify what constitutes evidence in the science of reading, and to offer a critical evaluation of the evidence provided by the science of reading. To this end, the authors summarize those things that they believe have compelling evidence, promising evidence, or a lack of compelling evidence. The authors conclude with a discussion of areas of focus that they believe will advance the science of reading to meet the needs of all students in the 21st century.

According to the Multiple Deficit Model, comorbidity results when the genetic and environmental risk factors that increase the liability for a disorder are domain-general. In order to explore the role of domain-general etiological risk factors in the co-occurrence of learning-related difficulties, the current meta-analysis compiled 38 studies of third- through ninth-grade children to estimate the average genetic, shared environmental, and nonshared environmental correlations between reading and attention-deficit/hyperactivity disorder (ADHD) symptoms, and reading and math, as well as their potential moderators. Results revealed average genetic, shared and nonshared environmental correlations between reading and ADHD symptoms of 0.42, 0.64, and 0.20, and reading and math of 0.71, 0.90, and 0.56, suggesting that reading and math may have more domain-general risk factors than reading and ADHD symptoms. A number of significant sources of heterogeneity were also found and discussed. These results have important implications for both intervention and classification of learning disabilities.

This study aimed to describe 1-year changes in students' vocabulary in written narratives. Secondary aims included examination of accuracy and the relationship between lexical diversity and achievement. Participants included 749 students in first through eighth grades. Within-subjects 1-year change in diversity, productivity, and accuracy was examined across time points by grades. Findings indicated there was significant change in lexical diversity in early elementary grades with decreases in the proportion of spelling errors. There was significant change in the proportion of different words to total words in upper grades. Students' lexical diversity was moderately related to performance on standardized measures of achievement. Findings support the use of lexical measures as a tool to examine and describe written language growth.

The purpose of this study was to test the directionality of influence between reading comprehension (RC) and print exposure (PE), thereby estimating genetic and environmental effects of this relation. The sample consisted of 910 twins in fourth through ninth grades (M[subscript age] = 12.33 years, SD = 1.41) from the Florida Twin Project on Reading, Behavior, and Environment. Using direction-of-causation model in a twin design, results supported a direction of influence running from RC to PE. This relation was underpinned by genetic and environmental factors of RC as well as PE. Implications for reading education are discussed.

Recent achievement research suggests that executive function (EF), a set of regulatory processes that control both thought and action necessary for goal-directed behavior, is related to typical and atypical reading performance. This project examines the relation of EF, as measured by its components, Inhibition, Updating Working Memory, and Shifting, with a hybrid model of reading disability (RD). Our sample included 420 children who participated in a broader intervention project when they were in KG-third grade (age M = 6.63 years, SD = 1.04 years, range = 4.79-10.40 years). At the time their EF was assessed, using a parent-report Behavior Rating Inventory of Executive Function (BRIEF), they had a mean age of 13.21 years (SD = 1.54 years; range = 10.47-16.63 years). The hybrid model of RD was operationalized as a composite consisting of four symptoms, and set so that any child could have any one, any two, any three, any four, or none of the symptoms included in the hybrid model. The four symptoms include low word reading achievement, unexpected low word reading achievement, poorer reading comprehension compared to listening comprehension, and dual-discrepancy response-to-intervention, requiring both low achievement and low growth in word reading. The results of our multilevel ordinal logistic regression analyses showed a significant relation between all three components of EF (Inhibition, Updating Working Memory, and Shifting) and the hybrid model of RD, and that the strength of EF's predictive power for RD classification was the highest when RD was modeled as having at least one or more symptoms. Importantly, the chances of being classified as having RD increased as EF performance worsened and decreased as EF performance improved. The question of whether any one EF component would emerge as a superior predictor was also examined and results showed that Inhibition, Updating Working Memory, and Shifting were equally valuable as predictors of the hybrid model of RD. In total, all EF components were significant and equally effective predictors of RD when RD was operationalized using the hybrid model.

Background: The number line task assesses the ability to estimate numerical magnitudes. People vary greatly in this ability, and this variability has been previously associated with mathematical skills. However, the sources of individual differences in number line estimation and its association with mathematics are not fully understood. Aims: This large-scale genetically sensitive study uses a twin design to estimate the magnitude of the effects of genes and environments on: (1) individual variation in number line estimation and (2) the covariation of number line estimation with mathematics. Samples: We used over 3,000 8- to 16-year-old twins from the United States, Canada, the United Kingdom, and Russia, and a sample of 1,456 8- to 18-year-old singleton Russian students. Methods: Twins were assessed on: (1) estimation of numerical magnitudes using a number line task and (2) two mathematics components: fluency and problem-solving. Results: Results suggest that environments largely drive individual differences in number line estimation. Both genes and environments contribute to different extents to the number line estimation and mathematics correlation, depending on the sample and mathematics component. Conclusions: Taken together, the results suggest that in more heterogeneous school settings, environments may be more important in driving variation in number line estimation and its association with mathematics, whereas in more homogeneous school settings, genetic effects drive the covariation between number line estimation and mathematics. These results are discussed in the light of development and educational settings.

The purpose of this study was to examine construct validity of methods of calculating lexical diversity in written narrative samples relative to children's performance on a reading vocabulary measure. For 234 children in first to fifth grade, written narratives were examined and compared between grades for number of different words (NDW), total number of words (TNW), NDW in a truncated 50 word sample, and type token ratio (TTR). The relationship between lexical diversity in written narratives and a standardized reading vocabulary measure ("Gates-McGinitie Reading Test--Fourth Edition" [GMRT-4]) was analyzed by comparing correlations. Grade differences were observed in measures of lexical diversity and productivity. Lexical diversity showed a significant moderate correlation with the GMRT-4. NDW had a stronger relationship to GMRT-4 scores than TTR for participants in first and second grade. Considering length (TNW, NDW constrained to 50 words, or TTR) did not result in a stronger relationship with reading vocabulary. Following additional study establishing probe equivalence, NDW in written narratives may be an efficient, educationally relevant, marker of language maturity, and a good predictor of performance on a standardized reading vocabulary measure.

A risk to develop a learning disability has been shown to run in families. Having a positive family history of learning disability seems to account for mean differences in achievement outcomes (reading, math) in that children with a positive family history score significantly lower compared to their peers with no such family history. However, the role of family history status in explaining etiological (genetic and environmental) differences among these subgroups of children has yet to be established. The present study of 872 twins (M[subscript age] = 13.30, SD[subscript age] = 1.40) from the Florida Twin Project on Reading, Behavior, and Environment utilized a multigroup approach to examine etiological differences on reading, spelling, and math among two subgroups defined by family history status. Results showed significant mean differences on all achievement outcomes, aside from math; however, no significant etiological differences on any achievement outcome were found among the two subgroups. Results support previous literature that the risk for developing a learning disability is transmitted through a family, but this is seemingly not manifested by differential etiology.

Based on research identifying relations between math and music, we aimed to identify the group of cognitive and affective factors related to math and music theory that best explained undergraduate music theory achievement. Using dominance analysis, we predicted the music theory course grades of 230 undergraduate music majors. Potential predictors were narrowed from measures of knowledge, aptitude, experience, confidence, and anxiety in both music theory and math as well as spatial skills and reading test scores. Results suggested that ACT math scores and music theory confidence were important predictors for Music Theories I and II grades. Music Theory I was also predicted by aptitude-based music theory skills, and Music Theory II was also predicted by math course experience. These findings provide evidence for a relation between math and music theory and support the use of several readily available measures for college-level music instructors to identify students who may struggle in music theory.

This study examined the heterogeneity of literacy profiles for adolescents with and without a specific learning disability (SLD) in the U.S. state of Florida Student subgroups displaying common patterns of performance in word-level skills and reading comprehension were identified through latent profile analysis. Results indicate most of the total sample demonstrated below-average performance in one or both areas with word-level skill difficulties being more common than difficulties in reading comprehension alone. Changes in reading performance by profile over time (Grades 6–8) were examined through a latent transition analysis revealing consistent patterns in the SLD sample and variable patterns in the typically developing sample. Resulting profiles were utilized to predict performance on an end-of-year broad reading comprehension measure indicating very little change in performance over time. Findings suggest large numbers of adolescents with concurrent word-level and reading comprehension difficulties likely need sustained intervention in word-level skills to support their reading comprehension. [ABSTRACT FROM AUTHOR]

Core reading instruction and interventions have differential effects based on student characteristics such as cognitive ability and pre-intervention skill level. Evidence for differential effect based on affective characteristics is scant and ambiguous; however, students with problem behavior are more often non-responsive to core reading instruction and intensive reading interventions. In this study, we estimated the range of students' behavior ratings in which a core reading instruction intervention was effective using a data set including 3,024 students in K-3. Data came from seven independent studies evaluating the Individualized Student Instruction (ISI) Tier 1 reading intervention and were pooled using integrative data analysis. We estimated Johnson–Neyman intervals of student behavior ratings that showed a treatment effect both at the within and between classroom level. ISI was effective in improving reading scores (b = 0.51, p =.020, d = 0.08). However, students with very low or very high behavior ratings did not benefit from the approaches (range of behavior rating factor scores: −0.95–2.87). At the classroom level, students in classrooms with a higher average of problem behaviors did not benefit from ISI (average classroom behavior rating factor score: 0.05–4.25). Results suggest differentiating instruction alone is not enough for students with behavior problems to grow in reading ability. [ABSTRACT FROM AUTHOR]

A fairly recent definition of reading disability (RD) is that in the form of a hybrid model. The model views RD as a latent construct that is manifested through various observable unexpected impairments in reading-related skills and through inadequate response to intervention. The current report evaluated this new conceptualization of RD from an etiological perspective. The sample consisted of 2,737 twin pairs in 1st through 4th grade (M[subscript age] = 8.52) from the Florida Twin Project on Reading. Using twin analyses, results showed that a substantial proportion of genetic variance, a small proportion of shared environmental, and a small proportion of nonshared environmental variance was attributed to the RD factor. Findings suggest that the etiological architecture of RD closely mirrors the structure of the hybrid model of RD.

Background: The way in which socioeconomic status (SES) moderates the etiology of reading attainment has been explored many times, with past work often finding that genetic influences are suppressed under conditions of socioeconomic deprivation and more fully realized under conditions of socioeconomic advantage: a gene–SES interaction. Additionally, past work has pointed toward the presence of gene–location interactions, with the relative influence of genes and environment varying across geographic regions of the same country/state. Method: This study investigates the extent to which SES and geographical location interact to moderate the genetic and environmental components of reading attainment. Utilizing data from 2,135 twin pairs in Florida (mean age 13.82 years, range 10.71–17.77), the study operationalized reading attainment as reading comprehension scores from a statewide test and SES as household income. We applied a spatial twin analysis procedure to investigate how twin genetic and environmental estimates vary by geographic location. We then expanded this analysis to explore how the moderating role of SES on said genetic and environmental influences also varied by geographic location. Results: A gene–SES interaction was found, with heritability of reading being suppressed in lower‐ (23%) versus higher‐SES homes (78%). The magnitude of the moderating parameters were not consistent by location, however, and ranged from −0.10 to 0.10 for the moderating effect on genetic influences, and from −0.30 to 0.05 for the moderating effect on environmental influences. For smaller areas and those with less socioeconomic variability, the magnitude of the genetic moderating parameter was high, giving rise to more fully realized genetic influences on reading there. Conclusions: SES significantly influences reading variability. However, a child's home location matters in both the overall etiology and how strongly SES moderates said etiologies. These results point toward the presence of multiple significant environmental factors that simultaneously, and inseparably, influence the underlying etiology of reading attainment. [ABSTRACT FROM AUTHOR]