A number of major foundations in the US support the introduction of personalized learning systems into public education. These systems rely upon the collection of personal data from pupils in and out of the classroom. Algorithms then analyse the data to identify individuals’ learning needs and steer their learning activities. With this panel, we examine how the meaning of learning, the role of learners and teachers, and the interplay of public and private within the educational sphere is constructed. We then analyze how this is affected by personalized learning systems in the US and in Europe.
• How does personalized learning affect the traditional role of education in a liberal democracy?
• What are the strategies that private foundations are adopting to support personalized learning and how successful have they been?
• What impact does personalized learning have on the privacy of students?
• How can the emerging privacy issues be addressed?