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AI Feedback-Form / Form-Filling

Completing workplace-based assessment forms represents a significant challenge for both Trainees and Supervisors, who are often time-pressed individuals in these settings. Often currently finding themselves burdened by the administrative task of filling out feedback or WBA forms, detracting Supervisors/Clinicians from their role of mentoring and guiding trainees but also taking significant time away from their Primary roles or rest time. Similarly, trainees often are required to capture WBA's for submission and need to ensure its completed correctly and fully. Again, an administrative burden.
Utilising AI across risr/ platform can assist in filling in feedback and/or WBA forms enabling supervisors to conduct feedback sessions naturally and conversationally, without the distraction of screens or keyboards. While supervisors focus on delivering valuable insights and guidance, our AI module discreetly records the conversation, employing sophisticated algorithms to analyse the dialogue and intelligently transcribe and complete the feedback forms - aligned to competency and blueprinting before human-in-the-loop review and submission.

  • Status: Conceptual Demo is available for initial feedback
  • Use cases include: Immediate trainee feedback, accelerated trainee WBA or form capture, research purposes against human based feedback and form filling, Special Interest.
  • Ideas for the future: Extend to automatically provide suggested areas of focus and learning to the trainee as part of feedback received. This could be in the form of various content types (knowledge articles, short videos etc) or even encourage trainees to take knowledge and/or simulated assessments on teh subject (using the above capabilities described)

 

AI Progress summary and early intervention

Utilising the rich data from supervisors, colleagues, and assessment outcomes, AI can assist in distilling this information into concise, actionable summaries. This aims to simplify the vast array of data into clear, actionable progress summaries, not only benefiting learners and their immediate supervisors but also providing valuable insights for a broader group of evaluators, especially during annual appraisals. This also helps identify and address potential issues or interventions required before they escalate.
We can achieve this by combining the automated form filling and feedback capture from WBA or supervisor feedback with auto identification of at risk students/trainees by using auto summarisation and sentiment analysis.

  • Status: Conceptual Demo is available for initial form-filling, feedback and summarisation. Conceptual design is in-work for sentiment analysis/presentation.
  • Use cases include: Real-time, holistic view of trainee/supervisor/cohort data for progress, performance and intervention purposes. Research purposes against manual human based progression tracking and intervention/drop outs. Special Interest.
  • Ideas for the future: Extend to automatically provide suggested areas of focus and learning to the trainee/supervisor/cohorts/curricula performance and progression.