Faculty Development Scheme (FDS) 2026/27 Exercise
- Panels across disciplines agreed that the general standard of submissions remained consistently high this year. Most submissions were clearly written, presented well-argued justifications for their research, and featured better-formulated research objectives along with explicitly stated research questions.
- Good quality proposals featured innovative integration of artificial intelligence (AI) that aligned well with pressing and topical research areas. Some proposals employed a “pain point problem + AI-based solutions” framework, showcasing a diverse range of problem areas and reflecting the richness and variety of the proposed research topics.
- A prevalent tendency towards excessive budget requests was noted. The panels therefore emphasised the necessity for PIs to furnish rigorous, itemised justifications for specific requested expenditures in accordance with the guidance notes.
- Some proposals failed to thoroughly define key constructs or clearly derive their theoretical frameworks from the literature, which could affect the achievement of the stated objectives. Some submissions adopted multi-method approaches that combined qualitative interviews with quantitative studies, often without clear justification. Concerns were raised regarding project feasibility and impact sustainability.
- A number of proposals lacked sufficient methodological details, and some adopted overly ambitious approaches without adequate scientific evidence or preliminary data to support their feasibility. Greater attention to methodological rigour and stronger justification of experimental design would further strengthen these submissions.