About

SAGE-RAI Project

Can responsible Generative AI (GenAI) lead to improved student outcomes? In SAGE-RAI, we utilise partner-applied education-oriented GenAI tools to explore this. Inspired by Bloom’s 1984 study on 1-to-1 teaching’s efficacy and the potential for cost-effective, scalable personalised education, we aim to unlock this potential. Human based tutoring will always have limits to how far it can scale and we are thus investigating how responsible GenAI can enhance scalability, offer highly personalised learning experiences, and generate student feedback. Our goal is to create a platform supporting assessment and student guidance while responsibly applying GenAI, addressing challenges of misinformation, copyright, and bias. The journey embodies educational innovation for better outcomes.

News

Recent Project Related News

Alexander Mikroyannidis 17 Jun 2024

Alexander Mikroyannidis presents SAGE-RAI at the 2024 Intelligent Tutoring Systems conference

Nancy Pontika 14 May 2024

Adaptive Education – Harnessing AI for Academic Progress

Nancy Pontika 16 Apr 2024

KMi’s Generative AI mini-Scotland Tour

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Research and Development

Related Projects

Our projects span a diverse range of fields, each designed to address pressing challenges and harness opportunities in their respective domains.

GenAI-OU

This project brings together Research and Innovation at the OU associated with Learning, Teaching and Generative AI (GenAI). The OU has a long tradition in using the latest technology to enhance the learning experience; beginning with radio, television, personal computers, the internet and mobile devices, GenAI has the potential to become even more transformative than these examples.

ShiftingPower

In this project, we are seeking a new paradigm for thinking about what can and should be done with AI Technology, which cannot be reduced to cultural complexity and which takes into account the reality of world forces (such as power and wealth) that help to predict what is likely to happen.

CORE-GPT

CORE-GPT is a step change in academic question answering. Our key development is that the provided answer is not just drawn from the model itself, as is done with ChatGPT and others, but is based on, and backed by, CORE’s vast corpus of 34 million open access scientific articles.

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People

The Team

The project team consists of the following members from The Open University (OU) and The Open Data Institute (ODI):

John Domingue

Prof John Domingue serves as the overall PI and Main Contact. John Domingue is a full Professor of Computer Science at the Knowledge Media Institute (KMi), the Open University’s technology Research and Innovation centre in the STEM Faculty, and the President of STI International, which runs the ESWC conference series.

Alexander Mikroyannidis

Dr Alexander Mikroyannidis leads the OpenLearn deployment of the AI Digital Assistant. Dr Mikroyannidis is a Senior Research Fellow in KMi. His research expertise is in the field of Technology-Enhanced Learning, investigating the use of novel educational technologies for enhancing personalised, self-regulated, and lifelong learning, as well as open education.

Aisling Third

Dr Aisling Third leads the technical work on the AI Digital Assistant with a strong EDI perspective. She is a Research Fellow in KMi, where she specialises in self-sovereignty in AI and the Web. She investigates technical and social solutions to major global concerns about equality, exploitation, and misuse of personal data.

Joseph Kwarteng

Dr Joseph Kwarteng is a Research Associate at the Knowledge Media Institute (KMi) of The Open University.
He specialises in the intersection of responsible artificial intelligence (AI), social justice, and education, pioneering initiatives that integrate these critical areas.

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