AI for RPL Evidence Analysis
Enable RPL assessors and coordinators to use AI to index, organise and compare candidate evidence against training product requirements, identify gaps and authenticity or currency risks, and plan supplementary assessment, while the assessor makes and documents every competency decision.
Upcoming course. LMS delivery and enrolment are not open. Release dates will be confirmed.
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Planned learning outcomes
- Explain RPL and credit transfer requirements under Outcome Standards 1.6 and 1.7, and how the principles of assessment and rules of evidence apply
- Use AI to index a candidate's evidence portfolio and map it to unit requirements, with traceable references
- Use AI-assisted document comparison critically, distinguishing similarity of wording from evidence of competence
- Identify evidence gaps and authenticity and currency risks, and design proportionate supplementary assessment
- Make and document defensible assessor decisions with complete audit trails and appropriate privacy controls
- Develop an RPL evidence matrix and gap assessment for a candidate, supported by an AI use and decision record