Parents’ use of early math talk with young children is important for later math outcomes. Existing research focuses on monolingual English-speaking populations and provides limited data on Dual Language Learners (DLLs). As the DLL population continues to grow, outcomes are important to investigate due to a possibly higher risk for academic disadvantage in comparison to their monolingual peers. The purpose of this project was to evaluate early maternal math language during mother-child play-based interactions in a primarily Spanish-speaking sample of low-income Mexican-American families. Specifically, this study investigated: (1) the type of math talk mothers used with their 3.5-year-old children in the context of semi-naturalistic play (2) how early math talk in Spanish predicted kindergarten math skills measured with standardized assessments. Mothers and children (3.5 years) played with toys (a bug-building kit and a pizza-making kit) for 15 minutes. Conversations between the mother and child were recorded and transcribed using Systematic Analysis of Language Transcripts (SALT) software. Transcripts were coded for instances of math talk, including numeracy, cardinality, quantity, spatial terms, and sequencing terms. We expected that preschool-aged children who were exposed to a greater quantity and diversity of numerical language during play would demonstrate more robust math skills in kindergarten measured with standardized academic assessments. We conducted descriptive analyses of mothers’ math talk and children’s language development (e.g., vocabulary and grammar) and used correlational analyses to see if mothers’ math talk was related to children’s language development. Predictive analyses assessed whether math talk predicted children's math outcomes in kindergarten. Findings from this work may have implications for parents, educators, and Speech-Language Pathologists in understanding how to support learning and academic success before entry to Kindergarten for the growing population of DLLs. Further research will help establish a better understanding of socioeconomic impacts on math talk.

Software engineering is a known difficult task that spans a wide variety of problems; as such, an important skill for seasoned software developers is problem solving. Current software engineering research focuses on building tools that support software development processes, but very little research has been done to assist developers with learning programming strategies. Yet, previous research has shown that developers using explicit programming strategies (i.e. procedures in problem solving that were verbally described) were objectively more successful at code design and debugging tasks. In this research project, we extend the previous work in understanding how programming strategies may be used at scale, and whether it is a potentially effective way of improving developer productivity. We propose a novel platform composed of a repository of explicit programming strategies across various programming activities, such as debugging, design, and testing. Developers will be able to search, use, create, and provide feedback on programming strategies on this platform, which will require innovations in defining how explicit programming strategies are searched and indexed. With this explicit strategy sharing platform, we want to understand the experiences of developers who are strategy seekers or givers as well as their motivations using the platform. For strategy seekers, we would like to understand their experience in using strategies, as well as how the feedback process may evolve strategies. For strategy givers, we would like to understand their experience in writing strategies and why they do it. After building the platform, we will deploy the platform in a classroom setting that relates to software engineering, and allow students to use the platform organically. Then, we will perform user interviews and data analysis to evaluate our research question.

Plants respond to environmental changes by changing their growth patterns. For plants to continue to grow throughout their lives, they are constantly undergoing cell fate determination—how the plant determines the specific fate of new cells they are generating. One example of this is the development of roots that emerge from the primary root, called lateral roots. The number and spacing of lateral roots determine the overall root structure, which determines how well the plant takes advantage of resources in its environment. Auxin is a plant hormone involved in many aspects of growth and development, including the regulation of lateral root production. Using data from an experiment where mRNAs were sequenced from single cells isolated from roots, the Nemhauser Lab identified specific genes that may be active during lateral root development. My research question is: are these genes targets of auxin signaling? To test this, I will use quantitative RT-PCR to measure expression of the candidate genes in wild type and in plants that are deficient in the auxin response pathway. Genes that are targets of auxin should show lower expression levels in the mutants relative to wild type. The more we understand about how cell fate determination occurs in lateral roots, the more we can understand the underlying mechanisms by which plants arrive at their final root structure. Our understanding can then guide engineering or breeding projects, allowing optimal root growth that could drastically increase plant survivability and yield.