It’s an AI Toolkit, Not a Chatbot

Generic AI tools like ChatGPT, Copilot, Gemini and Claude can be powerful, yet they require teachers to become skilled at prompt engineering if they want to produce any meaningful content.

This is not realistic or conducive as most educators do not have the time to develop specialist AI-prompting skills alongside their existing responsibilities.

As Peter explained, TeacherMatic has been designed to remove this as an onboarding barrier:

“A toolkit that would avoid the need for prompt engineering and would cover a range of everyday tasks that people in education carry out.”

“It’s designed to make using AI accessible for everybody, not just people who are confident using technology.”

This is important to consider for vocational learning, which spans from welding and engineering to childcare, hospitality, health and social care. Each subject has its own resources, qualifications and assessment frameworks, so a generic chatbot cannot easily meet such varied requirements.

However, an AI toolkit built with role and task-specific generators can.

Keeping the Human in the Loop

A prime example of this human-AI philosophy can be seen in TeacherMatic’s Advanced Feedback generator.

This AI tool enables educators to upload assignment briefs, marking rubrics and student work to generate structured feedback alongside grading suggestions and a wide range of vocational frameworks.

TeacherMatic also has a specialist BTEC assessment tool that uses BTEC specifications and provides feedback on achievement or not of P1s, P2s, M1s and M2s, etc.

“It’s designed so the human is still in the loop, but the AI does a lot of the heavy lifting.”

Educators can use AI tools to make a strong first pass at the structured, repetitive elements of the marking process, then spend their professional time on the more nuanced areas that require personalised, human judgement.

This is the ‘human-in-the-loop’ or ‘hybrid marking’ approach.

Case Study: How GTA England Rolled Out AI Across a National Network

We were happy to be joined by Gavin Smith, Network Development Manager at GTA England, which represents 26 group training association members, working with around 24,500 employers and 22,000 apprentices. The network accounts for roughly 15% of all engineering and manufacturing apprenticeships each year.

Through its community of practice, GTA England identified the time pressure on teaching staff and how they would benefit the most from AI support: assignment marking on BTEC, HNC and HND programmes.

“This is absolutely the bit that is saving the time for our members, in that assignment feedback, that assignment marking.”

Rather than expecting each member to outsource and use AI tools on their own, GTA England chose to manage two licences per member to get them started, with the option to add further licences as needed.

After eleven months of live use, Gavin shared insights from his team:

• The Feedback generator is by far the most-used tool.
• 2,299 uses have been recorded.
• On average, for each user TeacherMatic saves approximately 3.5 hours per week.

Notably, one TeacherMatic user has built their own creative workflow around TeacherMatic:

“They have put an administrator in place who receives all the assignments from their instructors, loads them into TeacherMatic and generates the initial assignment feedback. That then goes back to the instructor, who has to check it and provide the feedback to the learner.”

GTA England also shared why its team recommends TeacherMatic to other vocational educators:

“It’s easy to use, it’s cost-effective, and it’s achieving one of the main objectives that the community set out to do, and that was to achieve some time and resource-saving for our members. So we would absolutely recommend it.”

Case Study: How Yuzu Training Built a Safe and Ethical Foundation

During this session, we gained more AI in vocational education insights from Ruth Cole, Director of Quality of Education and Safeguarding DSL at Yuzu Training, the Southampton-based independent training provider delivering apprenticeships, skills bootcamps and adult skills funded training.

For Yuzu Training’s AI adoption, Ruth and her team’s focus was:

“How could we enhance our quality of teaching to have more impactful learning?”

“The first thing we looked at was the ethics. We knew that our team members might have questions about the ethical use, and they might be concerned about it replacing them. So we spoke with the team members, we identified what their fears were, and we looked at our own research and our best-fit approach.”

The early steps included listening and responding to staff concerns about AI replacing roles, running a structured trial across their entire teams and identifying volunteer trailblazers across leadership, marketing and delivery.

Ruth highlighted how important the role of formal governance has played from the start:

“We devised a safe use of AI policy, which looked at absolutely everything, the governance of the AI, it looked at prescribing platforms, and also the staff training and the learner journey.”

Ruth also addressed how TeacherMatic has continued to support the team at Yuzu Training through quality assurance sampling, self-assessment review writing, quality improvement planning, tender writing, marketing, lesson planning, interactive resource creation, feedback drafting and time-saving benefits:

“On average, we save about 5 hours a week, so it does support our staff work-life balance, which is absolutely critical.”

A very interesting point was how direct Ruth and her team have been about their AI usage during their Ofsted visits, with inspectors briefed openly on how AI is applied to teaching and learning, and how it is governed:

“They were very interested in having the conversation about what we use. How did we make sure it’s safe? How did we make sure it’s ethical?”

We feel Ruth’s honest advice for other vocational education providers will resonate:

“Don’t hide it, use it effectively, but talk about it. And also, when you’re talking about it, make sure your learners know how you’re using it, and again, it supports their ethical use of it, because you can use that expertise to train them.”

What AI in Education Means for Vocational Providers

From these perspectives, we can see a valuable, coherent picture of what makes AI work in vocational education and training:

• Safety and governance: Both Yuzu Training and GTA England built their adoption around clear policies and approved platforms with structured staff training.
• Educators staying in control: Whether the focus is on lesson planning, scheme of work generation or assignment feedback, the human-in-the-loop approach means AI can make time-consuming tasks more manageable, letting educators make the final decisions before sharing feedback with their students.
• Time savings and increased capacity: The hours AI saves can be reinvested to support learners, share best practice, refine feedback quality and reduce the marking workload that often spills into an educator’s personal time.
• Transparency and trust: Both GTA England and Yuzu Training case studies show that being open about AI use earns credibility, whether that clarity is during Ofsted inspector conversations or learner discussions.

Let’s Continue the Conversation

If your organisation is exploring how AI could support teaching, assessment and operational workflows in vocational education and training, speak to the TeacherMatic team.

Whether you are running a small independent training provider, a college or a national network of GTAs, the goal is the same:

To give educators back time, support learners more effectively and adopt AI in a way the whole sector can be confident using.

See how with platform demonstrations, trial accounts and resources tailored to vocational providers. Our team is always open to discussing how the platform can fit your setting.

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