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The wide availability of GenAI offers transformative potential to improve efficiency, enhance learning experiences, and better prepare students for a technology-driven future. However, the growing use of GenAI in feedback practices also raises important questions about feedback quality, trust, human judgement and students’ engagement with feedback.

As staff and students navigate this fast-evolving space, there is a need to explore how GenAI can be used responsibly and meaningfully to support feedback processes, while preserving the human and relational dimensions of effective feedback.

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.

We believe in the power of an evidence-based approach to inform educational innovation and practice. Through focus groups with students and staff across STEMMB disciplines, we explore how they perceive effective feedback practices and their 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.

These findings provide the evidence base for our pedagogical innovations, informing both the development of custom chatbots and the co-creation of student-facing resources to strengthen feedback literacy and AI feedback literacy.

The FLAIR project focuses on two complementary areas of pedagogical innovation:

• Custom chatbot development

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 Imperiacommunity.

We will focus on the development of two staff-facing 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.

• Pedagogical materials development and innovation

Working in partnership with our student partners, we have co-developed a suite of evidence-based resources that support students in understanding effective feedback practices and how GenAI can be used responsibly, ethically and efficiently within feedback practices. These include posters, postcards, bookmarks, animations and videos, designed to strengthen students' feedback literacy and AI feedback literacy.