OAD in Ed Community
The Open Authentic Data (OAD) in Education Community focuses on creating open infrastructure, adapters for anonymization of data, establishing large open datasets for use by third parties, and an interest in applying our specifications to create realistic simulated data.
Since 2019, a growing group of DXtera members have been engaged in a community of practice exploring the opportunities and barriers to support better Artificial Intelligence (AI) tools in the education market. The original informal discussions focused on the barriers to exchange data from systems at the institutions, data and privacy issues, and lack of realistic datasets to train AI and Machine Learning (ML) tools, which are all areas where DXtera has specialized talents. The members have been focused on how we can support safe and fair AI tools to enter the market and ameliorate the equity gaps that are far too prevalent in education around the world.
The community meets monthly with sub-teams meeting offline to move each component of the community forward. As the activities, membership and projects emerge these sub-team may evolve into separate communities of practice.
DXtera’s OAD in Education Community was formed and we focused our efforts on how to enable open infrastructure, adapters for anonymization of data, data management capabilities to host large open datasets for use by third parties, and an interest in applying our specifications to create realistic simulated data. Since the start of 2021, we have grown to include a long-term collaboration with Riiid Labs to support these priorities, expand our open challenges to shift the market, pursue funding to support our priorities, and have become increasingly engaged in a discussion on how to ensure safety in AI tools.
DXtera and the OAD in ED Community recently responded to an RFI on the existence and use of large datasets to address education research questions. You can reach the full RFI here.
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