This study evaluates Beacon, a course-specific AI system (RAG) designed to provide private, immediate, and module-aligned academic support, aiming to reduce common barriers to help-seeking in higher education.

In plain terms

Students often face barriers like anxiety or fear when seeking academic help, leading to unequal access to support, especially in complex subjects like programming. While general AI tools exist, they can be inaccurate or not specific to a course. To address this, researchers developed "Beacon," a specialized AI system using Retrieval-Augmented Generation (RAG). RAG is an AI technique that grounds its responses in specific, approved teaching materials from the course, ensuring accuracy and relevance. Beacon was designed to lower the hurdles students face when seeking help and to encourage independent learning. Through surveys and interviews with students and staff, they found that students considered Beacon's responses closely aligned with module content and more trustworthy than unrestricted AI, valuing its scaffolded explanations. Participants viewed Beacon as a valuable first point of support before consulting lecturers or official resources.