About Learning Commons

The problem we’re solving

For decades, research has shown us what helps students learn best. Yet translating that science into classroom practice has remained largely out of reach—not because educators don’t want it, but because the infrastructure to deliver it at scale simply hasn’t existed. Learning science is complex. Academic standards vary across states. High-quality curricula are difficult to connect with digital tools. And as artificial intelligence opens unprecedented possibilities for personalized learning, the risk of building on shaky pedagogical ground has never been higher.

The result? Educators are doing the impossible: stitching together disconnected curricula, tools, and technologies, often sacrificing precious time and the ability to differentiate instruction. Students experience fragmented learning experiences that don’t fully respond to how they learn best. And developers—even those deeply committed to educational impact—face steep barriers in accessing the standards alignments, learning progressions, and research-based frameworks needed to build with rigor.

Learning science shouldn’t be this hard to access or apply. The research exists. The expertise exists. What’s been missing is the connective tissue—the open datasets, standards, and shared infrastructure that enables knowledge about effective teaching and learning to be easily integrated.

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Our approach

We’re developing this public foundation through open, machine-readable educational datasets and evaluation methods that improve the rigor of educational technology. We are creating these resources in deep collaboration with the people who matter most: educators using tools in real classrooms, researchers advancing our understanding of how learning happens, school leaders balancing instructional vision with practical constraints, and developers committed to building products that genuinely serve students.