Seed Funded Projects - Computer Science and Technology
Dr Paula Buttery, 2022
The Cambridge Education Technology Institute
Funds were allocated to support the development an institute for Education Technologies within the University to allow for effective sharing of resources and expertise. At the core of the institute is the established expertise of the Cambridge Institute for Automated language Teaching and Assessment (ALTA), the Ada Project (creators of the technology behind Isaac Computer Science and Isaac Physics) and the Raspberry Pi Institute for Computing Education. The envisioned outcome being that future Ed Tech initiatives can be quickly established, grounded in the shared knowledge and infrastructure of these successful, established and internationally respected enterprises. Through knowledge discovery within the University of Cambridge and beyond, four support strands were identified as required for successful propagation of Ed Tech initiatives: reusable software components, infrastructure for research on learning and cognition, technology knowledge exchange, and ethical considerations. Grant applications have been submitted to raise funds for the institute and the Learning & Human Intelligence (LHI) research group has been established at the Department of Computer Science and Technology: https://www.cst.cam.ac.uk/research/lhi . The aim of the LHI is to provide equitable and effective learning for all by bringing together experts in education, pedagogy, and computer science. With Artificial Intelligence proliferating in many aspects of society, the group’s emphasis on Human Intelligence is purposeful. The focus is on optimising and exploiting technologies including AI to support the acquisition of critical human thinking; the essential skills required to navigate a world overwhelmed with automatically generated and potentially fallacious information. Major research themes of the group include the psychology of learning, longitudinal learning outcomes, human-computer interaction, the application and theoretical underpinning of Large Language Models and the ethics of AI in ed-tech.