Enhancing Formative Feedback at Scale with the Intelligent Feedback Assistant

Abstract

Formative feedback spans various domains, from education to businesses and creative endeavours. In educational contexts, feedback enriches students' learning and work quality through reflection. However, providing effective feedback at scale is challenging. Students struggle to engage with feedback, often due to lack of feedback literacy. Recent advancements in Natural Language Processing, a branch of Artificial Intelligence, provides opportunities to evaluate how we can support feedback providers in its quality and scale. This poster paper presents an overview of key feedback challenges, attributes of high quality feedback, and introduces the Intelligent Feedback Assistant (IFA), an innovative NLP-based system designed to assist educators in delivering high-quality feedback. IFA operates as an ensemble of machine learning models and non-AI systems to guide educators in refining their feedback, ensuring it embodies attributes of effective feedback - actionable, specific, justified, and positive. IFA is supportive, not generative, ensuring the feedback provider remains central to the feedback provision process. The tool design, and outcomes of IFA offers a promising path for scaleable, high-quality formative feedback in education and beyond.