Colleague: Using “Big Data” Analytics to Empower K-12 Teachers for Instructional Improvement

Collaborative Learning and Analytics for Global Education (Colleague), an online project funded by NSF PFI-TT, uses the latest developments in educational “big data” and machine learning techniques to streamline lesson planning for K-12 teachers and empower them for instructional improvement. Teachers easily spend over two hours daily on planning, most of which is outside of their regular workday. Moreover, K-12 school systems have become the latest frontier in big data, as accelerated by the digital transformation of teacher and student learning with artificial intelligence playing a key role. Despite a great societal need and a billion-dollar market, K-12 systems remain one of the fields least transformed by technology. Teachers lack the right kind of technological tools that can effectively support their lesson plans, reflections, and collaboration. This student team worked to co-design a platform “with” and “for” teachers, and conducted initial user experience research. The solution includes libraries of high-quality instructional materials that teachers can adapt and incorporate into their own lesson plans. The platform leverages machine learning analytics to allow teachers to efficiently conduct self-learning and collaborate with other peers.

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