AI-augmented coaching, reporting and its assessment

This project will develop general cutting edge generative AI and natural language processing methods to advance AI-augmented human-in-the-loop coaching and associated training planning and outcome reporting.

The research will be completed specifically in the context of novel AI-augmented gaming coaching and National Disability Insurance Scheme (NDIS) reporting methods for Crank Crew members with autism spectrum disorder (ASD), psychosocial and other barriers. Moreover, the quality of these methods will be assessed in the context of improved coaching, NDIS reporting efficiencies and Crew member outcomes.

Crank Group will provide re-identifiable, de-identified demographic information, NDIS plans, coaching transcripts and other datasets from their Crew members to enable the development of AI-augmented gaming coaching reporting tools.

The recruited PhD student will perform natural language processing and machine learning research into AI-augmented coaching to provide a pre-coaching session AI-based question and answer tool for Crank crew members to prepare for coaching sessions around specific video gaming topics.

Moreover, the PhD student will complete natural language processing and machine learning research into AI-based activity planning and National Disability Insurance Scheme (NDIS) report generating based on demographic information, NDIS plans, coaching transcripts and other datasets of Crew members. This will lead to a tool that generates coaching plans, coaching activities and NDIS reports for Crank Crew members.  

Finally, the PhD student will assess the utility of the tools and methods described above for the purposes of supporting Crank Crew and demonstrating increased efficiencies in NDIS reporting and improved coaching and outcomes for Crank Crew members The AI-based approach will be benchmarked against standard manual approaches.

In addition to a topped-up PhD scholarship under the AI for Mental Health Next Gen program, Crank intends to hire the full-time PhD student in a part-time role for up to 20 hours per week. As such the candidate will have a very high income during the project as compared to the standard PhD scholarship.