Promoting Students’ Data Literacy through the Creation of Interactive Multimodal Representations of Biometric Data
This project will explore the potential for building students’ data literacy through tools that allow creative, multimodal data representation of biometric data.
This work is funded by an ITEST award (2241751) from the National Science Foundation, and is a partnership with Suzanne Dikker and Xavier Ochoa.
Abstract
This project will promote data literacy in high school students by engaging them in learning about the Quantified Self — the practice of using technology to track and reflect on one?s own biological, behavioral, physical, and/or emotional data. Learning activities will be designed to spark a broad interest in science and to help develop students? informed opinions about the role of human-generated data in public life. To achieve this goal, the project will develop and test software tools as well as lesson and professional development materials with which students and teachers can explore, analyze, and create novel, multimodal, and interactive representations of data, recorded by wearable biosensing devices. Students will learn about how data from their bodies can be captured and interpreted through hands-on STEM activities that include the creation of interactive data representations. Students will design and execute small exploration projects to answer their own questions and create offline and online artifacts to communicate their findings. Students will engage in discussions that consider the privacy implications of using data-fueled services, applications, and technologies and critically evaluate how their personal data is being used. During and after the project, instructors and students will have opportunities to connect with industry partners who work with biosensing and wearable technologies, and to access career and college readiness resources relevant to these and related data technology fields.
This project will study how interactive and multimodal data engagement tools, grounded in relatable Quantified Self experiences, can support students? learning and engagement with and about data, (neuro)biology, and bioinformatics. To achieve this, the project will design tools and materials in collaboration with teachers using a culturally responsive, participatory design approach, to ensure that the project activities will appeal to a range of students’ interests and that it will promote equity of participation in STEM education. The project will also examine how industry/mentor partnerships and an online platform can help learners contextualize their own cognition and behavior within population-wide patterns and build awareness of careers in data science, biology, and bioinformatics. Data will be collected through surveys, interviews, and student work artifacts. The analysis approach will include both qualitative and quantitative approaches to understand the impact of the project on student learning and engagement. This project addresses the pervasive challenges of building data and science literacy, increasing participation in STEM/ICT fields, and promoting equity in STEM/ICT workforce and career preparation. By engaging students in creating novel, multimodal data representations and evaluating their own data, the project aims to empower them to use data and science as tools for generating knowledge about issues that concern them and to consider careers in data-related fields. The project anticipates reaching 25 teachers, 15 mentors, and 400-600 students within the project term, and more via an open-source software and curriculum. This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students’ knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers.