Student Learning Common Data Model: A New Approach for Solving the Learning Data Puzzle
As the use of educational technology proliferates, there are opportunities for educators, students, administrators, and product providers to utilize digital data to enable student success. Interoperability of data on student learning from edtech products has come a long way over the last several years with the wide adoption of open standards. However, understanding the meaning of the data and the ability to take action on the data is still in its infancy. To address this growing challenge, the Student Learning Data Model initiative was formed as a collaboration between IMS, Unizin, Microsoft, Google, and other key suppliers and institutions to develop a global core data model for student learning that will enable universities and their product provider partners to better understand the use, effectiveness, and efficiency of educational technology products. This workshop will provide an overview of the Student Learning Data Model initiative, dive into a comparison of existing and emerging models (including the Unizin CDM) to identify commonalities and gaps, and engage in a brainstorming session to explore the use cases on your campus that might be facilitated by a common model for learning data, as well as investigate issues of privacy, security, and identity that such a model raises.
Speaker: Cary Brown, Higher Education Programs Director, IMS Global Learning Consortium