Blog

Usability studies on DAVAI: Making data inquiry accessible

https://concord.org/blog/usability-studies-on-davai-making-data-inquiry-accessible/

To ensure that blind and low-vision (BLV) learners can engage meaningfully in data science education, we’re designing an AI-supported natural language plugin for CODAP called DAVAI (Data Analysis through Voice and Artificial Intelligence). Students use voice or typed input to ask questions about datasets in CODAP, then get dynamically generated descriptions and optional sonification—hearing the […]

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Shared representations for accessible and AI-supported inquiry

Student wearing headphones using screen reader.

As we enhance the accessibility of our inquiry-based STEM simulations and integrate generative AI into our learning platforms, we’re constantly evaluating and leveraging emerging technologies to improve teaching and learning. Recent work has led to an exciting convergence and potentially transformative insight surrounding these two goals. The representations needed for a large language model (LLM) […]

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Inclusive inquiry: Simulation accessibility and VPATs

Example Massachusetts Department of Elementary and Secondary Education 5th grade simulation with "Committed to Accessibility" banner

The Concord Consortium has developed hundreds of STEM simulations to engage students in the NGSS science and engineering practices—from asking questions and defining problems to developing and using models, planning and carrying out investigations, and analyzing and interpreting data. These simulations—covering everything from genetics to plate tectonics, diffusion, protein folding, the underpinnings of AI, and […]

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Giants in the classroom: Developing students’ STEM identities

Graphic of supersized teacher behind three students at lab bench to show the teacher inspiring the students as a "STEM giant"

As part of our YouthQuake project, funded by the National Science Foundation, we developed a five-activity online module that guides students through a series of investigations of earthquake risks and hazards. In addition to investigating the science of earthquakes and how to develop block coding to model land movement, students learn about related careers as […]

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Two Tinker Fellows will develop innovations in AI

2026 Tinker Fellows Amelia McNamara and Yizhu Gao

The Robert F. Tinker Fellows Program aims to promote innovation, creativity, and cross-disciplinary conversations. We’re thrilled to announce that two 2026 Tinker Fellows will focus on innovations in artificial intelligence (AI) to help transform teaching and learning. Amelia McNamara will explore how custom AI models can support teachers’ and students’ critical thinking and data science […]

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Alaskan students use machine learning to investigate seismic activity

Image of Anchorage, Alaska, from the water

The Concord Consortium is proud to announce a new grant from the National Science Foundation, titled Separating the Signal from the Noise (or SeismicML for short). This three-year project with Kent State University, the University of Washington, and the Anchorage School District will design, develop, and test computational tools that enable middle and high school […]

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