Ambios provide training in employer identified practical skills required to gain jobs in nature conservation. They currently have their own informal certificate of attendance but 95% of their trainees would welcome more formal recognition as evidence for future employers. Assessment of vocational skills to determine if a learner is competent typically involves an assessor examining multiple forms of evidence presented by the candidate and mapping it to a list of required competencies. In the nature conservation sector, evidence takes considerable time for candidates to produce and assessors to consider.
This project aims to use a combination of artificial intelligence (AI) and audio recording to ease the assessment process for both trainer and trainee. It will replace existing evidence types with assessor observations of a candidate’s practice, analysed for competence by AI. Assessor observations are regarded by Awarding Bodies as exemplary evidence of a candidate’s competency – using AI will make this process more robust and quicker to deliver.
Issues around collecting evidence for assessment are common and shared among many training providers. Ambios’ project could be an excellent demonstrator of how AI can be used to map assessor observations. The project will produce a framework of vocational qualification Level 2/3 performance criteria with knowledge and understanding from Ambios’ existing curriculum that will enable formal assessment by observation. These will be audio recorded and an AI system will map voice output conversations to the learning framework, indicating which performance criteria have been covered and where further skills learning is required.