Project team

The FLAIR project team includes: Dr Tiffany Chiu (PI, CHERS), Dr Monika Pazio Rossiter (Co-I, CHERS), Dr Ian Radcliffe (Faculty of Engineering) and Dr Nashwa Ismail (CHERS)

The Feedback and Learning: AI-Assisted & Reimagined (FLAIR) project is a two-year study (2025-2027) funded by the Digital Innovation Fund, part of the Imperial Learning and Teaching Strategy. The project’s overarching aim is to advance our digital education capacity, both in reach and in depth, by exploring the use of novel digital technologies to enhance teaching, learning, assessment and feedback practices.

The wide availability of Generative AI (GenAI) offers transformative potential to improve efficiency, enhance learning experiences, and better prepare students for a technology-driven future. Across the sector, there has been extensive discussion about the usefulness and potential of customised chatbots in enhancing both staff and student experiences. Existing research highlights how GenAI can assist educators in developing tailored lesson plans and generating course and module learning outcomes (Mollick & Mollick, 2023; Sridhar et al., 2023; Su & Yang, 2023). Yet, the development of custom chatbots can be a costly endeavour with its own challenges and have a high environmental impact that often only serves a single programme or module. To maximise the potential benefits, we propose a collaborative approach that involves key stakeholders across the University to develop staff-facing prototype chatbots and enhance the quality assurance process, with the aim of supporting the broader Imperial community.

We will focus on the development of two chatbots to ensure wider impact and practical utility:

  • Chatbot 1: Feedback-focused Bot
    This chatbot will be designed to assist staff in delivering good quality, constructive feedback that aligns with educational principles for effective assessment and feedback. It will also incorporate disciplinary insights to ensure feedback practices are contextually appropriate and relevant.
  • Chatbot 2: Teaching-focused Bot
    This chatbot will provide advice on effective learning, teaching and assessment practices as well as guidance on integrating GenAI into curriculum design, instructional activities and assessment methods. It will support educators to make informed, innovative and pedagogically sound approaches to learning, teaching and assessment practices and point to further support that is not always visible.

This project aligns with the following funding priorities as outlined in the University’s Learning and Teaching Strategy (2023):

  • Reviewing our approach to assessment and feedback, with the aim of improving quality and reducing workloads for staff 
    Feedback is the area where student dissatisfaction is often particularly high. This is due to various factors but the way feedback is communicated and phrased plays a key role in shaping students’ experiences and satisfaction. Crafting effective feedback does not always come naturally and can often place a significant demand on staff time.

    Training the bot on how to best refine feedback (taking into account disciplinary cultures in Science, Technology, Engineering, Mathematics, Medicine, and Business, STEMMB) and good practices from the wider higher education sector can enhance students' engagement with feedback and encourage them to take meaningful action based on it. This initiative aligns with university-wide efforts to reduce the workload associated with feedback and assessment.
  • Growing our digital education capabilities in both scale and scope to enhance the use of novel digital technologies, expand virtual educational spaces, and share good learning, teaching and assessment practices

    Staff support for designing effective learning, teaching activities and assessments is essential. While some support is currently available, the need is greater than the support. By synergising new and existing resources and pedagogical knowledge about effective teaching, learning and assessment, we can configure and train the bot to provide relevant information and facilitate reflection on existing practices as well as personalised decision-making in educational design, particularly around using GenAI in higher education.

To develop the custom bots, this project has three phases – ‘Research’, ‘Pedagogical transformation and innovation’ and ‘Testing, implementation and evaluation’.

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Research

To inform the development of the Feedback-focused bot, we explore how students and staff perceive effective feedback practices within STEMMB disciplines in higher education. We also look into views on the potential and limitations of using GenAI to support the feedback process, including how GenAI-assisted feedback might influence perceptions of feedback quality.

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Pedagogical transformation and innovation

We believe in the power of an evidence-based approach to inform the design and development of custom chatbots, tailored to meet the diverse needs of educators in a higher education context.

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Testing, implementation and evaluation

The chatbots will be carefully reviewed and tested with key stakeholders to ensure its responses are accurate, inclusive, and aligned with the needs of the Imperial community. Drawing on expertise from across faculties and services, we aim to refine its outputs before implementation to ensure quality and impact.

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