Abstract
In this tutorial workshop, we will introduce The Learning Observer. This is a project whose goal is to set up an open, transparently-governed consortium to manage student data in student interest and public interest. The open-source platform we are develo** under this umbrella is at a work-in-progress stage, and is ready for community feedback. It is a modular platform designed to enable (1) the integration of diverse learning data, (2) the use of sophisticated machine learning techniques over that data, and (3) the presentation of real-time teacher dashboards. We are further extending it to support open-science and SEER-aligned [1] research methodology, as well as family rights. This workshop will be split into two closely related [2] components, one focused on policy and one on technology. Participants may come to either or both.
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Acknowledgment
This work is funded under Institute of Education Sciences award R305A210297, and initial work on this project was supported Schmidt Futures, as well as by the Educational Testing Service. This workshop presents a work-in-progress, and has not been reviewed or endorsed by ETS, IES, or Schmidt Futures, and does not represent their views.
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Mitros, P., Deane, P., Lynch, C., Erickson, B. (2024). The Learning Observer: A Prototype System for the Integration of Learning Data. In: Olney, A.M., Chounta, IA., Liu, Z., Santos, O.C., Bittencourt, I.I. (eds) Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky. AIED 2024. Communications in Computer and Information Science, vol 2151. Springer, Cham. https://doi.org/10.1007/978-3-031-64312-5_54
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