Marion Angelin

Events and Membership Services Officer

Marion is a bilingual communications and coordination professional with experience across the education and creative sectors. Her background includes PR, textile design and long-standing involvement in a bilingual school community, giving her strong organisational skills, attention to detail, and a collaborative approach. Her experience in school settings has strengthened her ability to support diverse communities and contribute to positive, well-organised learning environments.

At NEON, she supports events, membership services, and communications, helping to deliver a professional, engaging, and seamless experience for members.

The Framework for Personalised Learning with AI Tools

Added 30/01/2025

By Geoff Paul, Assistant Director (Academic) & Theo Ammari-Allahyari, Senior Lecturer (Academic Development), University of Sunderland in London
This blog is part of our NEON Summer Symposium 2024 series. 

Personalised learning is emerging as a transformative approach in today’s rapidly evolving educational landscape. It leverages AI tools to tailor the educational experience to each student’s needs, strengths, and weaknesses. This blog post delves into the framework for personalised learning, highlighting the key components that make it possible and the profound impact it can have on both educators and students.

Introduction to Personalised Learning

Personalised learning aims to create a unique lesson plan and learning environment for each student, accounting for their distinct learning styles. This approach optimises the pace and methods used for each learner, ensuring a more effective and engaging educational experience.

The Framework for AI Tools Enhancing Personalised Learning

The integration of AI tools into personalised learning frameworks facilitates several critical processes:

1. Data Collection:
• Initial Assessment & Ongoing Data Collection: Continuous gathering of student data to understand their starting point and track progress.

2. Student Profiling:
• Identify Learning Styles: Using AI to determine each student’s preferred learning styles and dynamics.
• Dynamic Profiling: Continuously updating student profiles to reflect their evolving needs and preferences.

3. Customisation:
• Adaptive Learning Materials: Personalising learning paths with materials that adapt to the student’s pace and comprehension levels.
• Personalised Learning Paths: Tailoring the educational journey to individual student requirements.

4. Interactive Learning Experience:
• AI Tutors & Chatbots: Providing instant support and guidance.
• Simulations & Gamification: Engaging students through interactive and immersive experiences.

5. Assessment:
• Automated Formative Assessments: Offering instant feedback to help students understand their progress and areas for improvement.

6. Social Learning:
• Group Formation & Activities: Facilitating collaboration and peer learning.
• Peer Assessment & Feedback: Encouraging students to evaluate each other’s work, fostering a collaborative learning environment.

7. Reflection & Adjustment:
• Reflective Learning: Encouraging students to reflect on their learning journey.
• Continuous Use of Learning Analytics: Using data to adapt and improve the learning experience continuously.

The Educator’s Role in Personalised Learning

Educators play a pivotal role in implementing and enhancing personalised learning. They use data-driven insights provided by AI tools to customise lectures, assignments, and resources to meet individual student needs. This personalised approach increases student engagement and comprehension.

Feedback from Educators:

• Economic Lecturer: “The personalisation of my economics courses has been significantly enhanced by AI tools. They offer data-driven insights into student performance, enabling me to customise lectures, assignments, and resources to accommodate individual requirements. This personalised approach has resulted in increased student engagement and comprehension. Students appreciate the adaptive learning paths and the capacity to concentrate on the areas where they require the most development.”


• Business Lecturer: “Higher education has made substantial strides in personalising learning materials through AI tools. These tools establish personalised learning paths tailored to each student’s unique assets and weaknesses. This not only enables students to remain focused but also enables them to delve more thoroughly into topics that pique their interest. The adaptive learning strategies and immediate feedback enhanced my classes’ academic performance and engagement.”

Feedback from Students:

• “Using visuals to convey information rather than relying solely on text encouraged us to think about the concept of globalisation in a new way. We are grateful to our Module Leader Qurat-ul-ain Jahangir for her support and inspiration!” — Alexandra & George

This framework for personalised learning using AI tools is a game-changer in the higher education sector. Focusing on individual student needs and leveraging advanced technology creates a more engaging, effective, and dynamic learning environment. As AI continues to evolve, the potential for further enhancing personalised learning is immense, promising a future where education is truly tailored to each learner’s unique journey.

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