At Bett UK 2026, Polly Morgan, CEO of iDEA, chaired a student panel in The Arena featuring students from The Wavell School and Highlands School.
Their message was refreshingly clear. Young people do not want schools to ignore AI, fear it or ban it without explanation. They want to understand it. More importantly, they want to help shape the conversation around it.
Reasons: Students have diverse learning styles, paces, and interests. Personalized AI can adapt to individual needs.
Examples: AI tutors that adjust difficulty based on student performance; customized lesson plans.
Benefits: Increased engagement, better understanding, and improved retention.
Results: Higher academic achievement, greater motivation, and reduced dropout rates.
Immediate Feedback and Support
Reasons: Students need quick corrections and guidance to stay on track.
Results: Faster skill acquisition and increased confidence.
Reasons: AI can break geographical and physical barriers.
Examples: Language translation tools; speech-to-text for differently-abled students.
Benefits: Inclusive learning environments, wider reach.
Results: Greater educational equity and opportunities for marginalized groups.
Reasons: Traditional methods can be dull; interactive AI can make learning fun.
Examples: Gamified lessons; virtual labs and simulations.
Benefits: Enhanced motivation, deeper understanding.
Results: Increased time spent on learning, better application of knowledge.
Reasons: Students and teachers need insights into progress and areas for improvement.
Examples: AI analytics dashboards showing performance trends.
Benefits: Informed decision-making, targeted interventions.
Results: Improved teaching strategies, personalized support leading to better outcomes.
Reasons: Both students and teachers benefit from automation.
Examples: Automated grading; scheduling tools.
Benefits: More time for creative and critical thinking.
Results: More effective learning environments, reduced workload for educators.
Reasons: AI can support continuous education beyond traditional schooling.
Examples: AI-powered career guidance; skill-building platforms.
Benefits: Relevant, up-to-date skills for the job market.
Results: Better preparedness for future careers, adaptability.
Students want clarity, not confusion
One of the strongest themes from the discussion was the inconsistency surrounding AI use in schools. Rules vary widely between institutions and, in many cases, students are unclear about where the line sits between acceptable support and academic misconduct. That uncertainty creates anxiety, especially when the consequences of getting it wrong can feel significant.
Students are asking for clearer guidance around when AI can be used, how it should be used and what responsible use looks like across different subjects.
AI is already changing the way students learn
The panel also highlighted something educators already suspect: students are actively using AI in thoughtful and practical ways. From generating revision questions and checking essays against mark schemes to explaining difficult concepts and building practice resources, AI is increasingly becoming part of everyday learning. For many learners, AI is not replacing education. It is providing support when teachers are busy, helping explain concepts differently and offering instant feedback when they need it most.
The question for schools is no longer whether students are using AI. It is whether students are being taught how to use it effectively.
The new digital divide is confidence
One of the most powerful insights from the session was that inequality is no longer just about access to technology. It is increasingly about confidence and capability. Some students are discovering high quality AI tools through research, school support and peer networks. Others are relying on trial and error or social media recommendations.
Without structured guidance, the gap between digitally confident students and those left to figure it out alone will only continue to grow. AI literacy is quickly becoming one of the defining skills of the future.
Schools cannot prepare students for the future by ignoring AI
The students on the panel were realistic about the future of work. They already see AI embedded across business, research and daily life. Rather than resisting change, they argued that education should evolve alongside it. Importantly, their message was not that AI should replace teachers, creativity or independent thinking. Instead, they called for balanced and responsible integration that helps students understand both the opportunities and the limitations of the technology.
AI literacy must include ethics and critical thinking
The discussion also revealed a growing awareness among young people about misinformation, unreliable outputs and harmful uses of AI. Students recognised the importance of checking sources, questioning responses and understanding that AI is not always accurate. That matters because future-ready education is not simply about teaching students how to use AI tools. It is about developing the judgement, digital literacy and critical thinking needed to use them responsibly.
The takeaway for educators
The student panel delivered an important reminder for the education sector that young people are not expecting adults to have all the answers overnight. What they want is honesty, guidance and the opportunity to learn alongside the technology that will shape their futures. The schools that respond best to AI will not be the ones trying to ban it out of existence. They will be the ones helping students use it thoughtfully, ethically and creatively, while keeping curiosity, confidence and human connection at the heart of learning.
Certainly! Teachers, curriculum supervisors, and policymakers have specific expectations and needs from AI in education. Here's a detailed overview of what they want, the reasons behind those desires, examples, benefits, and potential results:
1. Personalization of Learning
What they want:
AI systems to tailor educational experiences to individual student needs, learning paces, and styles.
Reasons:
- Students have diverse learning preferences and abilities.
- Personalized learning can improve engagement and retention.
- It helps identify students who need additional support early.
Examples:
- AI-driven adaptive learning platforms like DreamBox or Carnegie Learning.
- Customizable lesson pathways based on student performance data.
Benefits:
- Increased student motivation and confidence.
- Higher achievement rates.
- Efficient use of teacher time by focusing on students who need intervention.
Results:
- Improved academic outcomes.
- Reduced dropout rates.
- More equitable learning opportunities.
2. Data-Driven Decision Making
What they want:
AI tools that analyze vast amounts of student data to inform curriculum design, teaching strategies, and policy decisions.
Reasons:
- Evidence-based policies lead to better educational outcomes.
- Identifies trends and issues that might be missed through traditional assessments.
- Supports continuous improvement at institutional and systemic levels.
Examples:
- Learning analytics dashboards showing student progress.
- Predictive analytics to forecast future performance and intervene proactively.
Benefits:
- Data-informed curriculum adjustments.
- Early identification of at-risk students.
- More effective resource allocation.
Results:
- Enhanced accountability.
- Improved student support systems.
- Dynamic curriculum evolution aligned with student needs.
3. Automated Administrative Tasks
What they want:
AI to handle routine administrative tasks such as grading, attendance, and scheduling.
Reasons:
- Teachers spend significant time on administrative duties.
- Freeing up time allows teachers to focus on instruction and mentorship.
- Reduces errors and increases efficiency.
Examples:
- AI-powered grading systems for multiple-choice and even essay responses.
- Automated attendance tracking via facial recognition or biometric data.
Benefits:
- Reduced teacher workload.
- Faster feedback cycles.
- Improved accuracy in record-keeping.
Results:
- More time for pedagogical innovation.
- Enhanced accuracy in administrative processes.
- Streamlined school operations.
4. Enhancing Accessibility and Inclusivity
What they want:
AI solutions that support learners with disabilities and language barriers.
Reasons:
- Promotes equitable education for all students.
- Addresses diverse learning needs with assistive technologies.
Examples:
- Speech-to-text and text-to-speech tools.
- AI translation for multilingual classrooms.
- Customized learning tools for students with special needs.
Benefits:
- Increased participation of marginalized groups.
- Better learning outcomes for students with disabilities.
- More inclusive classroom environments.
Results:
- Reduced achievement gaps.
- Broader access to quality education.
- Support for diverse learners.
5. Support for Teacher Professional Development
What they want:
AI-driven platforms that provide personalized training and resources for teachers.
Reasons:
- Teachers need ongoing professional growth.
- AI can identify skill gaps and suggest targeted training.
- Facilitates lifelong learning for educators.
Examples:
- Intelligent tutoring systems for teacher training.
- AI feedback on teaching practices based on classroom recordings.
Benefits:
- Improved teaching quality.
- Greater confidence among educators.
- Stay updated with pedagogical advancements.
Results:
- Enhanced student learning experiences.
- Increased teacher satisfaction and retention.
- Continuous improvement in teaching standards.
6. Policy and Ethical Frameworks
What they want:
AI tools that are transparent, fair, and aligned with ethical standards and policies.
Reasons:
- Ensures student privacy and data security.
- Prevents bias and discrimination.
- Builds trust among stakeholders.
Examples:
- AI systems with explainability features.
- Clear policies on data use and student rights.
Benefits:
- Ethical deployment of AI.
- Increased stakeholder confidence.
- Compliance with regulations.
Results:
- Responsible integration of AI.
- Sustainable and equitable educational technologies.
- Enhanced public trust in AI initiatives.
Summary
In essence, educators and policymakers seek AI solutions that are personalized, data-driven, efficient, inclusive, supportive, and ethical. These technologies promise benefits like improved student outcomes, more effective teaching, operational efficiency, and equitable access to quality education. When implemented thoughtfully, AI can transform education into a more responsive, inclusive, and effective system.
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