LEAP — Learning Enhancement through Adaptive Personalisation
AI-Powered Personalised Learning for Higher Education
The Challenge
The global EdTech sector is valued at approximately $400 billion (2025), with the segment for personalised AI chatbots and adaptive learning platforms expected to reach $6.8 billion by 2027. However, current generic AI tools dominate the market but lack deep personalisation, evidence-based pedagogy, and seamless integration with university curriculum systems — creating a significant gap for institutions seeking tailored educational experiences.
The Solution: Aruva
The partnership has produced Aruva, an AI platform for higher education whose Smart Syllabus layer constrains generative output to the approved course plan. Unlike generic AI assistants, Aruva combines:
- Adaptive AI Algorithms — Real-time adjustment to individual learning styles and progress
- Evidence-Based Pedagogy — Grounded in educational research for effective interventions
- Curriculum Alignment — Seamless integration with university learning management systems
- Real-Time Analytics — Actionable insights for educators on student engagement and performance
- Scalable Customisation — Tailored content delivery across disciplines and institutions
Funding Details
| Programme | Innovate UK Knowledge Transfer Partnership (KTP) |
| Total value | £238,757 (£159,968 grant, £78,789 company contribution) |
| Knowledge Base | University of Glasgow, James Watt School of Engineering |
| Industry Partner | AWTG Limited |
| Duration | 2025–2028 |
| Pilot partners | Proof-of-concept terms agreed in principle with Nokia Saudi and Kingston University |
Commercial Platform: Aruva
Six months after the KTP Associate started (March 2026), Aruva is built and in integration ahead of its first pilots, as reported to the Local Management Committee in September 2026. The Aruva trademark application was published by the UK IPO in May 2026. The KTP Network publishes the partnership as a national case study.
- Smart Syllabus — Constrains generative output to the approved course plan
- UK IPO trademark — Aruva application published May 2026
- Pilot pipeline — Proof-of-concept terms agreed in principle with Nokia Saudi and Kingston University
Research Objectives
Develop adaptive AI algorithms for personalised learning pathways
Create real-time analytics dashboards for educator insights
Design scalable content customisation frameworks
Integrate LEAP with university learning management systems
Validate effectiveness through pilot deployment at University of Glasgow
Refine platform for market readiness and global scalability
Methodology & Approach
The KTP will embed advanced capabilities in:
Personalised Learning Systems
AI models that adapt to individual student needs
Adaptive Algorithms
Machine learning for targeted interventions based on learning patterns
Data-Driven Insights
Analytics pipelines connecting student behaviour to outcomes
Curriculum Integration
APIs and connectors for seamless LMS integration
Collaborative Tools
Features enabling student-educator interaction and feedback loops
Academic Team (University of Glasgow)
Dr Ahmed Zoha
AI/ML for personalised systems, federated learning, data analytics, edge intelligence, IoT sensing
Prof Sajjad Hussain
Machine learning, intelligent systems
Prof Muhammad Ali Imran
Communications systems, 5G/6G, smart campus technologies
Industry Partner
AWTG Limited
Company Profile
AWTG Limited is an EdTech company headquartered in London, focused on delivering scalable, AI-driven educational tools. The KTP with University of Glasgow will enable AWTG to become a global leader in personalised learning solutions.
Key Contacts
Partnership Model
University of Glasgow
- AI/ML Research Expertise
- Educational Technology
- Smart Campus Infrastructure
- PhD Student Training
AWTG Limited
- EdTech Commercialisation
- Software Development
- Market Access
- Customer Networks
Joint Innovation
- Knowledge Transfer
- Technology Development
- Product Validation
- Market Launch
Work Packages
WP1 Requirements & Design
Foundation & Architecture
Requirements & Design
Foundation & Architecture
- Stakeholder engagement with students, educators, and institutions
- User research and persona development
- System architecture design
- Curriculum mapping frameworks
WP2 AI Algorithm Development
Core Intelligence
AI Algorithm Development
Core Intelligence
- Adaptive learning models
- Personalisation engines
- Student behavior prediction models
- Learning style classification
WP3 Analytics Dashboard
Educator Insights
Analytics Dashboard
Educator Insights
- Real-time educator insights
- Student engagement tracking
- Performance visualization
- Intervention recommendation system
WP4 Platform Integration
System Connectivity
Platform Integration
System Connectivity
- LMS connectors (Moodle, Canvas, Blackboard)
- Curriculum alignment tools
- API development
- Authentication and security
WP5 Pilot Deployment
Real-World Testing
Pilot Deployment
Real-World Testing
- University of Glasgow trial implementation
- Student cohort recruitment (target: 500+ students)
- Educator training and onboarding
- Usage monitoring and data collection
WP6 Evaluation & Refinement
Performance & Market Readiness
Evaluation & Refinement
Performance & Market Readiness
- User feedback collection and analysis
- Performance metrics evaluation
- Iterative improvements
- Market readiness assessment
- Documentation and knowledge transfer
Key Innovations
Adaptive Personalisation Engine
AI that learns individual student patterns and adjusts content delivery in real-time based on learning velocity, engagement patterns, and comprehension levels.
Evidence-Based Pedagogy Integration
Learning interventions grounded in educational research, incorporating spaced repetition, retrieval practice, and metacognitive strategies.
Real-Time Analytics Dashboard
Comprehensive insights for educators showing student engagement, predicted at-risk learners, topic difficulty analysis, and suggested interventions.
Scalable Curriculum Alignment
Framework enabling rapid customisation across disciplines while maintaining learning outcome alignment with institutional requirements.
Collaborative Learning Tools
Features fostering student engagement through peer interaction, study groups, knowledge sharing, and collaborative problem-solving.
Expected Commercial Outcomes
Market Position
Target Share: 3-5% of $6.8B personalised AI education segment by Year 5
Projected Value: $204-340 million annually
Job Creation Breakdown
Software Development
4-6 roles
Full stack developers, AI/ML specialists
Data Analytics
2-3 roles
Data scientists, analysts
Customer Success
2-3 roles
Implementation, training, support
Sales & Marketing
2-3 roles
Business development, partnerships
Societal Impact
Democratising Education
Personalised learning accessible to diverse student populations regardless of background, learning style, or pace. Reduces educational inequality through tailored support.
Improving Student Outcomes
Data-driven interventions support struggling learners with early identification and targeted assistance. Predicted 15-20% improvement in student retention and performance.
Reducing Educator Burden
Automated insights and administrative tasks free up 30-40% more time for meaningful student interaction, mentorship, and curriculum development.
Enhancing Accessibility
Adaptive tools supporting neurodiverse learners, students with disabilities, and those with different learning preferences. Multi-modal content delivery.
Research Advancement
Contributing to educational research through anonymised learning analytics, publishing findings on effective AI-driven pedagogy.
Publications & Outputs
Status: Coming Soon
Publications will be updated as the project progresses
- • Academic papers
- • Conference presentations
- • Technical reports
- • Open datasets (subject to ethics approval)
Project Documents
LEAP Product Overview
Status: Coming Soon
Comprehensive overview of LEAP platform features, architecture, and value proposition
Format: PDFTechnical White Paper
Status: Coming Soon
Deep dive into AI algorithms, adaptive learning models, and system architecture
Format: PDFPilot Results Report
Status: Coming Soon (Post-pilot)
Analysis of University of Glasgow pilot deployment with student and educator feedback
Format: PDFImplementation Guide
Status: Coming Soon
Step-by-step guide for institutions adopting LEAP
Format: PDFNews & Updates
Project Launch
University of Glasgow and AWTG Limited announce innovative Knowledge Transfer Partnership to develop AI-powered personalised learning platform.
Additional updates will be posted as the project progresses
Media Coverage
Coming Soon
Press releases, news articles, and media features
Presentations & Talks
Coming Soon
Conference presentations, demo videos, and slides
Collaborators Welcome
We welcome collaboration with:
- Universities interested in piloting LEAP
- EdTech companies exploring partnerships
- Researchers working on AI in education
- Funding bodies supporting educational innovation