Sara A. Hart - US grants

DESCRIPTION (provided by applicant): Reading difficulties have negative consequences that are frequently associated with behavior problems and can adversely impact children's school outcomes, health, and wellbeing. There has been a growing body of work which suggests that the individual traits and history that a child brings into a classroom, and by extension an intervention project, have an interactive effect on literacy learning. Given the call for better understanding and improving the outcomes from literacy intervention paradigms, this project proposes to explore how individual differences in child traits, family environment and familial ris status moderate response to intervention. To do so, this project innovatively proposes to combine three extant intervention projects to create a pooled source of data which is more representative and powerful than any one intervention alone, as well as capitalizing on the knowledge pool of already collected data. The three Aims of this project will serve to meet the general goal of measuring individual differences in response to intervention using the bioecological model. Aim 1 explores child trait characteristics, or cognitive and psychosocial outcomes. Aim 2 explores the family environment, such as home literacy practices and parental beliefs. Aim 3 explores the familial risk status of various learning disabilities and difficulties n response to intervention. By using the novel method of integrative data analysis, the raw data from each project can be combined and heterogeneity across sites controlled for. Additionally, for aspects of child individual differences which are not presently available in the existing intervention projects, we propose to recruit original participants and their families into a questionnaire portion of the present project. This pooling of raw data, as well as the new collection of data through a questionnaire, will allow for the various sources of individual differences, specifically child traits, family environment, and familial risk status, to be enteredas moderators in a multilevel model predicting children's response to intervention defined as post- test status controlled for by pre-test status. This work has the potential to lead to more effectiv literacy interventions, which has great public health implications for school children and future generations of citizens.

This study of the 'shape' of STEM educational assessment data will exploit recent advances in computational topology, machine learning and cognitive science. Applications of computational topology to learning theory are both new and innovative. It is anticipated that these new tools will provide critical insights into student learning of Calculus.

Funded by NSF's Research on Education and Learning (REAL) program, this early concept grant for exploratory research will apply advanced topological, geometric, and Bayesian methods to analyze the shape of data generated by students taking Calculus via a massive open online course (MOOC) system (and other data sources). This project will link data analyses from three leading learning platforms in the service of better understanding student learning of Calculus. One potential high payoff is the deployment of richer analyses of test and performance data to support a recommendation system to support to students reaching their learning goals. Further, the project will seed a new community of researchers across disciplines that typically do not interact. The proposed line of work has the potential to fundamentally change the way we think about assessment data in support of mathematics learning and perhaps other STEM content.

ABSTRACT Engagement Core The Engagement Core, or Core B, serves as the central dissemination and translation, resource sharing, and training component of the proposed FLDRC. To support this broad objective, Core B has three specific aims related to dissemination and translation of research findings (Specific Aim 1), facilitating resource and data sharing (Specific Aim 2), and supporting project-embedded career enhancement efforts (Specific Aim 3).

ABSTRACT Project 4 Reading and math problems represent an important public health issue for children in that they are associated with various negative outcomes including school failure, limited occupational success, and juvenile delinquency (Geary et al., 2012; Reynolds et al., 2002). Of US fourth-grade students, one-fourth fail to reach even partial mastery of grade-level knowledge in reading, and one-fifth fail to reach partial mastery of grade-level knowledge in math (NCES, 2015), highlighting the prevalence of reading and math difficulties in childhood. Given we know that children who struggle in reading often also struggle in math, it is important to identify influences on the development of both reading and math. The overall goal of the proposed research is to uncover salient factors, including genetic and environmental influences, which contribute to the co- development of reading and math performance, at a critical developmental point (elementary school). We will identify the first nationally-representative US twin sample through the proposed National Project on Achievement in Twins (NatPAT). The NatPAT sample will comprise 7,668 pairs of twins located across the US, and will be uniquely situated to address the overall goal of the proposed research through four specific aims (SA). First, we will utilize a large national database of reading and math performance from schools across the country to ascertain the NatPAT twin sample. Using a cohort-sequential design starting in kindergarten, we will examine reading and math performance across elementary school in order to model genetic and environmental influences on reading and math (co-)development (Specific Aim 1). Second, we will model the genetic and environmental influences on the co-occurrence of reading and math difficulties, while also testing for sex differences (Specific Aim 2). Third, we will capitalize on publically available data to characterize the environmental contexts related to the (co-)development of reading and math performance (Specific Aim 3). Finally, we will capture important attitudinal individual differences dimensions and examine how they are associated with the (co-)development of reading and math performance (Specific Aim 4).

PROJECT SUMMARY There is considerable interest in data sharing, encouraged by funding agencies which are requiring more detailed data-sharing plans, as well as greater attention and support from the scientific community towards rigorous, open, and reproducible science. With this project, we will build a domain-specific data repository, ?LDbase?, containing behavioral data from the field studying learning disabilities that will serve as a powerful resource for our community. We are uniquely qualified to build this repository. Our investigator team combines expertise in learning disabilities, advanced methodology, and research librarian techniques. LDbase will accelerate intellectual discovery by facilitating data reuse and reproducibility, ultimately building an enduring record that represents the richness, diversity, and complexity of the science done by learning disabilities researchers. We will achieve this through three specific aims: (1) Create a data repository representing a vast knowledge database on learning disabilities; (2) Release a powerful open access combined dataset and provide statistical training for combining datasets using integrative data analysis; and (3) Use integrated data to determine the most valid way to classify a reading disability for each child. LDbase will be seeded by data from six large research sites that will contribute large amounts of behavioral data from tens of thousands of participants, and then open to external data depositors and data users. With these high quality ?big data?, we will answer a fundamental question in the field concerning personalized classification of reading disability, showing the powerful applied usefulness of these data. LDbase will advance the sharing of learning disabilities related behavioral data as a powerful new tool to answer research questions not answerable without it, build a community of researchers invested in data sharing and open science practices, and establish a sustainable infrastructure to support the longevity of the project.

Many children, adolescents, and adults experience math anxiety. Research has shown that math-anxious children typically continue to experience math anxiety as they get older. People with math anxiety tend to perform more poorly in math and are less likely to take advanced math courses or pursue science, technology, engineering, and mathematics (STEM) careers. Thus, tackling math anxiety early on is important for mitigating negative impacts later in life. This project will develop and test a school-based intervention to decrease children’s math anxiety. Researchers have suggested that math anxiety leads to lower math achievement because it leads people to avoid math, and because anxious thoughts use the limited cognitive resources in working memory, which are required for solving math problems. Therefore, this project will test whether any reduction in math anxiety from the intervention leads children to avoid math less, have better working memory skills, and perform better in math. This project will produce intervention materials that can be used to alleviate children’s math anxiety and help to better understand long-term effects of math anxiety on math avoidance, working memory, and math achievement.

The first goal of this project is to develop the math anxiety intervention. This intervention will adapt an existing classroom-based intervention and add exposure components from cognitive behavioral therapy interventions, which are effective for children with other anxiety-related disorders. The work will involve developing a child workbook, facilitator session guides, and facilitator training materials. During this process, intervention components will be tested with 24-39 children to inform revisions to the materials. The second goal is to test the effect of the intervention on math anxiety and whether any effect leads to changes in working memory and math avoidance, and subsequently math achievement. Second- and third-grade classrooms will be randomly assigned within schools to have their students with high math anxiety (140 students total) participate in the small-group intervention or be in a business-as-usual control group (140 students total). Children’s math anxiety, avoidance, working memory, and math achievement will be assessed before and after the intervention, as well as 3 and 6 months later. Results will be used to test the theory that intervention-induced changes in math anxiety relate to increased working memory and decreased math avoidance, which relate to improved math achievement. The findings from this project will have implications for understanding the role of math anxiety in math achievement, and have the potential to lead to long-term increases in STEM workforce participation.

This project is supported by NSF's EHR Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. The program supports the accumulation of robust evidence to inform efforts to understand, build theory to explain, and suggest intervention and innovations to address persistent

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.