There’s a huge number of ways to take advantage of artificial intelligence in education, from freeing up teachers’ time to providing personalised support to learners.
As we learn more about AI, it’s clear that some applications could instantly have a positive impact in education.
The ability to save time on repetitive tasks and free up trainers is a no-brainer – that’s why our upcoming marking feature, uses AI to reduce manual marking time so trainers can focus on more complex feedback.
However, there are still question marks over other aspects of AI. We spoke to some of the apprenticeship providers from our recent AI pilot to find out the biggest questions they still have about the technology.
The ethical considerations of learner data are still the top priority, as organisations continue to grapple with how to safeguard potentially sensitive learner information.
There are concerns about data being hacked and confidential information leaked, and providers also raise the lack of transparency around how the data collected is being used by third-party vendors.
When it comes to using AI in your organisation, it’s important to only work with vendors that you trust to have responsible data practices. Good questions to ask include:
Additionally, you can read the Department for Education’s (DfE) position on protecting data, learners and staff while using generative AI (GenAI) in this document.
Overreliance on AI was raised in the DfE’s research into GenAI in education earlier this year, with one interviewee calling it the “main risk at the moment”. Teacher surveys flagged concerns that GenAI tools would reduce pupils’ creativity, while others worried that relying too heavily on GenAI would impede intellectual growth.
While it’s harder to cheat in apprenticeships given the different assessment methods, providers are still worried that learners will become too dependent on AI and fail to really understand topics.
The same DfE report called for guidance to help teachers identify and manage student use of AI, adding that:
“Funding for research is needed to support the development of tools that can reliably detect AI-generated outputs and for other initiatives that could help (e.g. watermarking outputs). Curricula should also be updated to reflect current student use or to integrate AI tools as an explicit part of learning and assessment.”
AI can struggle to fully accommodate additional learning needs in assessments, particularly if it hasn’t been designed with inclusivity in mind. Possible challenges include:
Lack of contextual understanding: AI may not understand the nuances of different responses from individual learners, such as those with neurodivergent conditions like dyslexia or ADHD
Adherence to rigid scoring systems: Learners with additional needs might demonstrate knowledge in ways that fall outside the AI’s predefined criteria, such as drawing diagrams instead of writing
Lack of emotional or behavioural considerations: Learners may present behaviours like anxiety-related errors or inconsistent focus, which a human could contextualise but AI might penalise
The solution to this is to use a combination of human and AI to deliver the best results for learners. Use AI to do the heavy lifting and reduce overall marking time, which will free up trainers to focus on instances that require nuance or more sophisticated feedback.
Are you exploring ways to take your apprenticeship training to the next level? From easy enrolment to pre-built reporting dashboards, Bud’s platform harnesses the latest technology to help you deliver a seamless, engaging learning experience.
Browse our case studies to find out why training providers love using Bud, or book a discovery call with us now.