Children’s storybooks are a ubiquitous learning resource, and one with huge potential to support STEM learning. They also continue to be a primary way that children learn about the world and engage in conversations with family members, even as the use of other media and technology increases. Especially before children learn to read, storybooks create the context for in-depth learning conversations with parents and other adults, which are the central drivers of STEM learning and development more broadly at this age. Although there is a body of literature highlighting the benefits of storybooks
The goals of this proposal are: 1) to provide opportunities for underrepresented students to consider careers in basic or clinical research by exciting them through an educational Citizen Science research project; 2) to provide teachers with professional development in science content and teaching skills using research projects as the infrastructure; and 3) to improve the environments and behaviors in early childcare and education settings related to healthy lifestyles across the state through HSTA students Citizen Science projects. The project will complement or enhance the training of a workforce to meet the nation’s biomedical, behavioral and clinical research needs. It will encourage interactive partnerships between biomedical and clinical researchers,in-service teachers and early childcare and education facilities to prevent obesity.
Specific Aim I is the Biomedical Summer Institute for Teachers led by university faculty. This component is a one week university based component. The focus is to enhance teacher knowledge of biomedical characteristics and problems associated with childhood obesity, simple statistics, ethics and HIPAA compliance, and the principles of Citizen Science using Community Based Participatory Research (CBPR). The teachers, together with the university faculty and staff, will develop the curriculum and activities for Specific Aim II.
Specific Aim II is the Biomedical Summer Institute for Students, led by HSTA teachers guided by university faculty. This experience will expose 11th grade HSTA students to the biomedical characteristics and problems associated with obesity with a focus on early childhood. Students will be trained on Key 2 a Healthy Start, which aims to improve nutrition and physical activity best practices, policies and environments in West Virginia’s early child care and education programs. The students will develop a meaningful project related to childhood obesity and an aspect of its prevention so that the summer institute bridges seamlessly into Specific Aim III.
Specific Aim III is the Community Based After School Club Experiences. The students and teachers from the summer experience will lead additional interested 9th–12th grade students in their clubs to examine their communities and to engage community members in conducting public health intervention research in topics surrounding childhood obesity prevention through Citizen Science. Students and teachers will work collaboratively with the Key 2 a Healthy Start team on community projects that will be focused on providing on-going technical assistance that will ultimately move the early childcare settings towards achieving best practices related to nutrition and physical activity in young children.
Research that seeks to understand classroom interactions often relies on video recordings of classrooms so that researchers can document and analyze what teachers and students are doing in the learning environment. When studies are large scale, this analysis is challenging in part because it is time-consuming to review and code large quantities of video. For example, hundreds of hours of videotaped interaction between students working in an after-school program for advancing computational thinking and engineering learning for Latino/a students. This project is exploring the use of computer-assisted methods for video analysis to support manual coding by researchers. The project is adapting procedures used for computer-aided diagnosis systems for medical systems. The computer-assisted process creates summaries that can then be used by researchers to identify critical events and to describe patterns of activities in the classroom such as students talking to each other or writing during a small group project. Creating the summaries requires analyzing video for facial recognition, motion, color and object identification. The project will investigate what parts of student participation and teaching can be analyzed using computer-assisted video analysis. This project is supported by NSF's EHR Core Research (ECR) program, the STEM+C program and the AISL program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. The project is funded by the STEM+Computing program, which seeks to address emerging challenges in computational STEM areas through the applied integration of computational thinking and computing activities within disciplinary STEM teaching and learning in early childhood education through high school (preK-12). As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants.
The video analysis systems will provide video summarizations for specific activities which will allow researchers to use these results to quantify student participation and document teaching practices that support student learning. This will support the analysis of large volumes of video data that are often time-consuming to analyze. The video analysis system will identify objects in the scene and then use measures of distances between objects and other tracking methods to code different activities (e.g., typing, talking, interaction between the student and a facilitator). The two groups of research questions are as follows. (1) How can human review of digital videos benefit from computer-assisted video analysis methods? Which aspects of video summarization (e.g., detected activities) can help reduce the time it takes to review the videos? Beyond audio analytics, what types of future research in video summarization can help reduce the time that it takes to review videos? (2) How can we quantify student participation using computer-assisted video analysis methods? What aspects of student participation can be accurately measures by computer-assisted video analysis methods? The video to be used for this study is drawn from a project focused on engineering and computational thinking learning for Latino/a students in an after-school setting. Hundreds of hours of video are available to be reviewed and analyzed to design and refine the system. The resulting coding will also help document patterns of engagement in the learning environment.
This project is funded by the National Science Foundation's (NSF's) Advancing Informal STEM Learning (AISL) program, which supports innovative research, approaches, and resources for use in a variety of learning settings.
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TEAM MEMBERS:
Marios PattichisSylvia Celedon-PattichisCarlos LopezLeiva