Contextualizing Data Education via Project-Based Learning

This DataPBL project is working to develop, implement, and research the introduction of data experiences and practices into a series of interdisciplinary, middle school project-based learning modules. Data fills all aspects of our lives, and data science has become a vital interdisciplinary endeavor. To succeed in the future, students must see data as a tool they can wield to address relevant issues across disciplines.

Students need opportunities to apply data science practices to appropriately realistic datasets from contexts meaningful to them, and to have opportunities to demonstrate their skills and knowledge authentically. Project-based learning (PBL) approaches have cultivated a growing base of classrooms dedicated to supporting such situations via authentic, interdisciplinary learning experiences.

Co-designing these modules with middle school teachers and piloting them in urban, low-income schools in New York City and Chicago, this project examines how interdisciplinary data education can provide opportunities for students to take more control of their own learning and develop positive identities related to data, through integration with social studies and science topics. Curriculum modules and teaching resources produced by the project serve as guides for subsequent efforts at integrating data science concepts into teaching and learning in various subject areas.

This design-based research project integrates data-focused learning into interdisciplinary PBL in ways that prepare marginalized learners for the future. The project develops descriptive case studies investigating three questions: (1) In implementations of the DataPBL curriculum, what interdisciplinary data practices do students participate in, and under what conditions? (2) Under what conditions do students manifest agency in the course of their data-infused PBL? and (3) How do aspects of the experienced projects contribute to developing positive identities related to data?

Through this case study analysis, the project provides a thick description of how agency and identity develop during DataPBL projects in the participating classes. The project applies Qualitative Comparative Analysis to generate cross-case patterns and illustrate the multiple pathways available to students in reaching the desired outcomes. In combination with the case studies, this work illuminates how the learning environment fosters the aims of the project.

The Discovery Research preK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.

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.