🔎 Embedding Literacy and Numeracy in Vocational Training – How Do We Do It in the Real World?
That was a core challenge tackled at the recent LLN Community of Practice (CoP) session I attended! With a spotlight on Tapatoru, the Dyslexia-Friendly Quality Mark (DFQM), and AI-powered support through ALEC GPT, the session delivered practical strategies for embedding LN into vocational and trades education.
Missed it? No worries—here’s a quick recap of the key takeaways! 🎯
1️⃣ Tapatoru – A Framework for Embedding LN
The Tapatoru Ako Professional Practice Award is a structured approach that helps vocational tutors integrate literacy, numeracy, and cultural capability into their teaching.
Why Does It Matter?
Because vocational educators aren’t always LN specialists, yet literacy and numeracy are crucial for learner success in apprenticeships and employment readiness. Tapatoru provides a practical, whole-organisation approach to embedding these essential skills.
🔸 New Updates to Tapatoru:
✅ Dyslexia Friendly Quality Mark (DFQM) modules now integrated into Tapatoru’s Learning Differences content (thanks to work by Michael Grawe and Annette Tofaeono).
✅ Upcoming enhancements include:
- What is Tapatoru?
- Unpacking Your Values
- Embedding LN effectively
💡 Takeaway: Tapatoru continues to evolve as a practical, structured tool for educators looking to improve LN outcomes in vocational settings.
2️⃣ DFQM & Learning Differences – Practical Support for Educators
Michael Grawe walked us through the new DFQM learning collections on Pathways Awarua, highlighting accessible training options to help educators create more inclusive learning environments.
What’s New?
✅ DFQM modules now integrated into Tapatoru’s Learning Differences strand.
✅ Flexible learning pathways for tutors aiming to strengthen LN and neurodiversity (ND) support.
✅ Upcoming educator training options, including free webinar-based training.
💡 Takeaway: These new learning collections make it easier for tutors to embed LN-friendly and ND-inclusive practices in their teaching.
3️⃣ AI in Action – ALEC GPT’s Role in LN Support
We also introduced a game-changing tool—ALEC GPT, the world’s first AI-powered literacy & numeracy tutor assistant.
What Can ALEC GPT Do?
✅ Generate LN lesson ideas & strategies tailored for vocational tutors.
✅ Support embedding LN into training—no need to reinvent the wheel.
✅ Provide ND-aware teaching strategies, including dyslexia-friendly approaches.
Live Demo Highlights
We ran three real-world scenarios and let ALEC GPT generate instant LN strategies:
🔹 Scenario 1: Supporting a carpentry apprentice struggling with numeracy on site.
🔹 Scenario 2: Designing LN-integrated lessons for an Intro to Trades programme.
🔹 Scenario 3: Helping youth learners (18-24) build confidence with LN.
💡 Takeaway: ALEC GPT isn’t just another AI tool—it’s an instant, vocationally relevant teaching assistant, ready to support educators anytime, anywhere.
🚀 Try These Scenarios Yourself!
Want to test ALEC GPT’s capabilities for yourself? Try these prompts in a session and see how it generates real, practical support for vocational tutors.
📌 Scenario 1: Supporting an Apprentice Struggling with Numeracy on Site
🔹 Context: A carpentry apprentice is highly skilled with tools but struggles with measurements, fractions, and unit conversions. They frequently make small but costly errors when reading plans, which slows down their work. The tutor wants to support them without singling them out. 🔥 Prompt for ALEC GPT:
“Give me three ways a vocational tutor can support an apprentice who struggles with numeracy on a building site, focusing on hands-on, contextual learning strategies that don’t feel like school maths.”
📌 Scenario 2: Designing LN-Embedded Lessons for an Intro to Trades Programme
🔹 Context: A tutor is developing a 12-week Intro to Trades programme for youth learners (18-24) who have varying levels of literacy and numeracy. Some lack confidence with reading and writing, others struggle with numeracy. The tutor wants embedded LN strategies that feel practical and natural within the hands-on nature of the course.
🔥 Prompt for ALEC GPT:
“Create a lesson outline for an ‘Intro to Trades’ programme that embeds literacy and numeracy naturally into hands-on tasks. Focus on contextual learning, avoiding worksheets, and using real trade tasks as teaching tools.”
📌 Scenario 3: Supporting Youth Learners (18-24) in a Trades Training Environment
🔹 Context: A tutor working with young learners in trades training finds that some struggle with focus, organisation, and following instructions. Many fear failing, leading to avoidance behaviours when tasks involve reading, writing, or maths. The tutor wants strategies to boost engagement and confidence.
🔥 Prompt for ALEC GPT:
“Give me three strategies to support youth learners (18-24) in a trades training setting, particularly those who struggle with reading, writing, and numeracy, and who may lack confidence or focus.”
💡 Takeaway: These practical, AI-powered strategies give educators instant solutions tailored to vocational training settings. Try them out and see how ALEC GPT can enhance real-world LN teaching!
📢 Let’s keep the kōrero going!
What are your biggest challenges when embedding LN into vocational training? Drop a comment below or reach out—we’d love to hear your thoughts! 💬
📌 Stay connected for future LLN CoP sessions and updates. Until then, let’s keep making literacy and numeracy practical, relevant, and accessible for all learners! 🚀
Kia ora! Hey, I'd love to know what you think.