Project Profile

Data literacy plays a pivotal role in understanding real-world problems, making it an increasingly important topic in mathematics education. Preparing young learners to use data to answer questions and solve problems empowers them to participate in society as informed citizens and opens doors to 21st-century career opportunities. For many learners underrepresented in STEM, developing data literacy through innovative technologies requires personally meaningful experiences working with data. The Framework for Integrating Technology for Equity (FIT for Equity) is a Developing and Testing Innovations (DTI) project that will engage 24 teachers in co-designing technology-enhanced data literacy lessons and including students and community members as co-authors. This inclusive lesson study approach advances equity in math classes by supporting the critical data literacies necessary to participate in today’s workforce as informed citizens. FIT for Equity will cultivate design principles that bring together teachers, students, and community members in this innovative capacity building effort that may lead to more equitable learning opportunities. The project team will also produce a collection of data literacy mathematics lessons featuring transformative technologies to address community-based challenges, co-authored by elementary teachers, students, and community members in four distinct geographic locales in Virginia, Ohio, Tennessee, and Michigan.

Through equity frameworks in mathematics education, this project will develop and test design principles for planning, observing, and reflecting on technology-integrated mathematics lessons. Researchers will use a design-based research approach to answer three research questions: 1. How do technology-enhanced data literacy lessons develop students' data literacy, understanding of community issues, and attitudes towards STEM? 2. How do the project’s design principles for technology-enhanced data literacy lessons promote teachers’ practices for culturally responsive mathematics teaching? 3. What are the affordances and constraints of Inclusive Lesson Study in expanding the integration of technology for data literacy towards equity? Iterative implementation cycles will be used to develop and test the inclusive lesson study cycles. Data will be collected through inventories and document analysis of lesson study artifacts, including student work, annotated classroom lessons, and lesson study meeting recordings. Additionally, data will be gathered using the Culturally Relevant Mathematics Teaching (CRMT2) Classroom Observation Tool, the Equity-centered Transformative Technology Lesson Analysis Tool, and interviews with participating teachers, students, and community members. Pre- and post-surveys will be administered to measure changes in students' STEM self-efficacy and career interests. Deliverables will include a repository of research lessons and video vignettes highlighting FIT for Equity lessons. Research findings will be disseminated through a project website, conference presentations, and journal publications. All program materials will be made free and publicly accessible, allowing other educators, designers, and researchers to replicate or modify them to foster innovative approaches to promoting inquiry topics that are both meaningful and applicable to underrepresented learners’ real-world contexts.

This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that increase students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers.

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.