Teach-GenAI-Connect

Universities are adopting generative Gen AI rapidly, yet academics and students lack the AI literacy, teaching methods, governance arrangements and institutional support required to use it critically and productively. Existing guidance is restricted to regulations (do not do that) rather than pointers and encouragement.

This proposal aims to co-design, pilot and disseminate practical, evidence-based best practices for the use of generative AI in higher education through active learning techniques (problem-based learning, peer review and feedback, simulation and role-play, inclusive multilingual tutoring) .

The contribution is two fold: First to enable students to analyse GenAI outputs (e.g. identify bias/hallucinations ) and create artefacts. Second to transform assessments from a polished final submission to evaluation of reasoning, process evidence and reflection .

The main outcome is envisaged to be a Gen AI Teaching Best-Practice Toolkit with activity patterns for teaching and assessment rubrics and responsible-use policies. It will enable innovation hubs to train, optimise and demonstrate tailored AI solutions with local data and applied research, directly supporting the call’s goal of faster uptake and scalable deployment of locally appropriate AI solutions in low- and middle-income countries.