Integrating Multimodal Learning Analytics with LLM-Based Agents to Address Educational Disadvantage

Start year: 2024

Summary: This project proposes the innovative use of multimodal learning analytics combined with an large language model (LLM)-based agent to tackle educational disadvantages among primary and secondary school students in Australia. By analyzing a wide array of engagement indicators, including facial expressions [3], body language, and eye metrics to interactions with technology [2], this project will construct detailed student profiles highlighting specific areas of disadvantage and implement an LLM-based agent for targeted support. Students’ profile includes the visualization of students' learning journeys, enabling the analysis of challenges and prediction of outcomes. Through the integration of detailed learning analytics and an LLM-based agent, the project aims to inform policy decisions and enhance educational equity, ensuring that every student, regardless of background, has access to quality education and the opportunity to succeed

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.