We present realistic scenarios in the context of the learner’s employment and programme of study. This will empower apprentices to apply theoretical understanding to the skills and behaviours they are working towards, fostering a deeper understanding of on-the-job challenges. This supports the goal of aligning apprenticeship training and real-world requirements, while also providing tutors with a comprehensive understanding of each learner’s progress.  

The first phase of development focuses on efficiently housing information about the submission within Aptem, enabling learners and tutors to easily access it via the Learning Plan. A streamlined process that encourages clarity of expectations and standardised assessment criteria for consistency, fairness and efficiency.

Learn more: https://www.aptem.co.uk/aptem-news/aptem-and-graide-launch-first-ai-driven-integrated-marking-aid-for-apprenticeships/

The review summarisation eliminates the trade-off between valuable conversations and accurate record-keeping, by automatically generating the key discussion points and themes from each review. As the conversation progresses, crucial feedback and action points will be documented, helping to improve engagement, boost accuracy and shorten feedback loops.

Unlock impactful, learner-centred support by shifting the focus from basic routine feedback to meaningful constructive guidance, tailored to each learner’s needs.

Unlike generic chatbots, our virtual assistant is purpose-built for each learner’s apprenticeship programme, so its accuracy in relation to the apprenticeship standard is far higher than that of a standard large language model.

Using this approach gives learners more ownership of their learning journey, maximise learning momentum, and reduce the administrative burden for tutors to respond to repetitive questions.

To help identify areas where learners may need additional support or stretch, tutors can now see the chat history between the virtual assistant and the learner. This has been developed in response to Early Adopter feedback. It can also be used for QA purposes.

Aptem has integrated its virtual assistant with the Checkpoint functionality. As a result, after completing a Checkpoint, the virtual assistant will be available to the learner, providing them with the opportunity to delve deeper into the topic. This timely intervention allows learners to enhance their understanding by engaging in targeted conversations right at the moment they are assessing their knowledge.

Expanding on the initial iteration of Aptem’s marking aid, this feature introduces intelligent KSB criteria mapping to assist tutors during the marking process. The tool learns how you mark, every time you mark. With this human-in-the-loop approach, it helps to drive accuracy and efficiency, freeing up tutors’ time and allowing them to focus on personalised guidance that supports learner progress.

Achieve significant time savings without compromising feedback quality. By reducing the time taken to provide repetitive feedback, it allows for more personalised guidance that improves learner outcomes.

This new feature allows organisations to save time and drive high quality marking across all apprenticeship standards. The ability to deliver this at scale is a significant time saving that gives tutors more time to spend with learners.

This new feature allows organisations to pinpoint and address any quality issues relating to marking and also to implement improvements in a syllabus or learning materials where learner performance is not as expected across a cohort.

To support better-informed reviews, this feature will provide a summary of key points, including achievements, outstanding actions and previous review summarise to ensure that both the tutor and the learner can effectively prepare for a structured review.

This feature adds more value to reviews by generating specific actions and goals for learners that are measurable and time limited. These goals can be tracked through the system to allow tutors to monitor progress and support where required. 

The additional flexibility of Checkpoint triggering will allow organisations to use the resource for all learners regardless of their start and end dates, allowing for greater personalisation of the learner journey. 

This development will allow organisations to personalise the style and tone of the virtual assistant based on their teaching practices and brand values. The update will also allow for the addition of supplementary knowledge such as employer practices and proprietary learning materials.