Navigating AI in further education maths: A professional development roadmap

JUDE MORTIMER, FE AND ADULT MATHS EDUCATION SUPPORT SPECIALIST, MATHEMATICS IN EDUCATION AND INDUSTRY (MEI), UK

EMMA BELL, FE CPD PROGRAMME LEAD, MATHEMATICS IN EDUCATION AND INDUSTRY (MEI), UK

The UK government’s AI Opportunities Action Plan highlights the role that artificial intelligence (AI) could play in enhancing services, citizen experiences and productivity (Clifford, 2025). Meanwhile, the National Numeracy charity emphasises the importance of numeracy in education, employment and everyday confidence (National Numeracy, 2019). As AI becomes more embedded in society, educators must ensure that students develop both numeracy and digital literacy skills in order to engage with new technologies effectively.

Debra Gray, Principal of Hull College, writes, ‘In an increasingly AI-driven world, Further Education (FE) colleges… play a critical role in preparing students for a rapidly evolving workforce. The demands of modern employers are changing, with digital skills and AI literacy now essential across a wide range of industries.’ (Gray, 2025a, p. 14) FE colleges must ensure that students not only develop essential numeracy skills but also gain AI literacy in order to navigate this changing landscape.

FE educators have a responsibility to ensure that AI is used safely and ethically, helping students to navigate its benefits, limitations and risks. They also have a unique opportunity to develop students’ critical thinking and digital skills, preparing them for future employment.

How can AI be used to enhance FE maths teaching and learning? 

In ‘Using AI for question generation in mathematics education’, Rycroft-Smith and Macey (2024) explore how large language models (LLMs) can support mathematics education, highlighting AI’s potential to generate questions, foster critical thinking, personalise learning and act as a pedagogical agent. However, they also note limitations, including issues with accuracy, embedded bias, and the need for careful human oversight. These challenges suggest that while AI holds promise, it should be used thoughtfully and in partnership with educators.

From an FE maths perspective, particularly in GCSE maths resit and functional skills, AI offers significant value. Teachers can prompt AI systems to generate contextualised resources tailored to students’ vocational areas, making learning more relevant and engaging. As Rogan and Deakin (2024) highlight, AI has the potential to be transformative for learners with special educational needs and disabilities (SEND). AI tools can be used to enhance accessibility by providing differentiated materials, which is especially beneficial in catering for diverse needs in GCSE resit classrooms.

AI systems can also be used to support personalised learning, guiding students through tailored questions and explanations. Additionally, developing students’ ability to critique AI-generated solutions fosters critical AI literacy, helping them to assess the reliabilityIn assessment, the degree to which the outcome of a particular assessment would be consistent – for example, if it were marked by a different marker or taken again and limitations of AI – a crucial skill, as technology becomes more embedded in daily life (Centre for Teaching and Learning, 2024).

Implementing structured AI professional development 

A structured CPD (continuing professional development) roadmap is essential to ensure that both teachers and students benefit from AI, equipping educators with the confidence, knowledge and motivation to integrate it effectively, while remaining adaptable to rapid advancements. However, many teachers lack the time, training and confidence to implement AI meaningfully (EEF, 2024). While AI adoption among students is growing, teachers engage with it at significantly lower rates (Teacher Tapp, 2024). Without clear guidance and professional development, there is a risk of AI being underutilised or misapplied. A phased roadmap can support educators in developing AI literacy, using it purposefully and embedding it within effective pedagogical practice.

Drawing on our experience in facilitating professional development in FE maths across the country, this roadmap provides a structured, practical approach to AI adoption – helping teachers to integrate AI in ways that enhances learning, while remaining flexible to future developments.

Stage 1: Discover and build

The first stage of the roadmap focuses on exploring how AI can enhance maths teaching and learning, assessing staff confidence levels and identifying areas for development. 

Building confidence is key. Debra Gray highlights that technological change has always been met with hesitation, referencing historical shifts such as the printing press, the steam engine and the internet, all of which initially sparked uncertainty before becoming integral to society (Gray, 2025b). Similarly, AI’s introduction in education may cause apprehension, but its potential to support and enhance teaching is significant.

One way in which to ease concerns is by highlighting AI’s presence in everyday life. Many educators may not realise how AI is already embedded in familiar tools, such as smartphone assistants, predictive text and adaptive learning platforms. Recognising this can help to shift perceptions, making AI feel less intimidating and more relevant to teaching.

To alleviate concerns that AI might replace teachers, it is crucial to emphasise that AI is a tool, and not a substitute for professional expertise. While AI can enhance teaching and streamline processes, subject knowledge, creativity and pedagogical expertise remain at the heart of effective education.

Within FE maths CPD sessions, staff confidence can be assessed and built on by:

• using anonymous polls or reflection prompts to uncover perceptions and identify support needs
• exploring examples of how AI can enhance maths teaching, such as reviewing AI-generated exam questions and discussing how they could be adapted or improved
• identifying areas for development, through collaborative mapping of current practice, where AI could offer value and be tailored to specific teaching contexts.

Stage 2: Develop and explore

The second stage focuses on exploring AI tools through training, workshops and peer collaboration, building confidence through hands-on, low-risk experimentation. Key recommendations for this stage include:

• Focus on AI tools that address specific teaching challenges
• Start with small, manageable changes to build confidence
• Ensure that staff receive ongoing support and training, with opportunities to share insights
• Regularly collect feedback and refine approaches based on staff and student experiences
• Embed AI within pedagogical goals, aligning it with broader teaching and learning strategies.

This approach aligns closely with our work on MEI’s FE CPD menu (MEI, 2025), where AI has already been seamlessly integrated into a range of sessions. The menu is made up of elements of professional development that have been written for teachers of FE maths (MEI, 2025). For example, Quizalize can be explored in our Responsive Teaching session to support adaptive learning by uncovering misconceptions and gaps in knowledge, while ChatGPT can assist in our Planning and Sequencing menu element by generating lesson structures for discussion from schemes of learning. By embedding AI into everyday teaching and CPD educators can develop confidence and see AI as a practical, purposeful tool that enhances both teaching and learning.

Stage 3: Reflect and refine

This stage is an ongoing process of building confidence, exploring AI tools and refining their use in the classroom. Peer collaboration, shared planning and student discussions help teachers to exchange ideas, reflect on successes and adapt their approaches. As confidence grows, the focus shifts to identifying the most effective AI tools for GCSE maths resits and functional skills, and embedding them into practice.

AI evaluation should be practical and purposeful, using simple measures such as student engagement, the extent to which AI systems enable personalised learning experiences, workload reduction and achievement outcomes. These can be evaluated through insights from lesson observations, student feedback and performance data, allowing teachers to refine their approach based on what works best. AI integration must also be ethical, inclusive and accessible. Regular reflection on its use and impact ensures fair, transparent implementation that supports both students and teachers in a meaningful, manageable way.

Stage 4: Sustain and evolve

Although this is the final stage of the roadmap, in many ways it marks the real beginning of AI’s long-term role in FE maths education. For AI to remain embedded in teaching and learning, ongoing support, training and reflection are essential. As AI evolves, so too must the strategies for its effective integration, ensuring that it continues to enhance education rather than becoming outdated or underutilised.

Long-term success requires strategic decision-making, including investment in infrastructure and adapting plans as needed. Sustaining AI integration goes beyond individual colleges – collaborative networks enable FE maths educators to share insights, strategies and best practices. Engaging with AI-focused education communities and conferences helps teachers and leaders to stay informed about emerging trends and refine their approach as technology advances.

Figure 1: Roadmap for professional development in the use of AI in FE maths

Concluding thoughts

Ultimately, the goal is for AI integration to become a natural part of everyday teaching practice, embedded seamlessly within FE maths classrooms. By following a structured roadmap such as that summarised in Figure 1, educators can progress from discovery to sustainable implementation, ensuring that AI is used purposefully and effectively to support both teaching and learning.

As AI continues to evolve, so must our approach. A well-implemented strategy not only enhances numeracy teaching but also strengthens digital literacy, equipping students with the skills that they need for an AI-driven world. Through thoughtful integration, collaboration and ongoing reflection, AI can be recognised as a valuable tool for enhancing learning, rather than perceived as a challenge to overcome.

The examples of AI use and specific tools in this article are for context only. They do not imply endorsement or recommendation of any particular tool or approach by the Department for EducationThe ministerial department responsible for children’s services and education in England or the Chartered College of Teaching and any views stated are those of the individual. Any use of AI also needs to be carefully planned, and what is appropriate in one setting may not be elsewhere. You should always follow the DfE’s Generative AI In Education policy position and product safety expectations in addition to aligning any AI use with the DfE’s latest Keeping Children Safe in Education guidance. You can also find teacher and leader toolkits on gov.uk .