Bett UK 2026 Institutional Reflections:

How AI Assessment Becomes a Bridge Between Teachers and Students

From January 21–23, 2026, the PagePeek team attended Bett UK at ExCeL London.
As one of the world’s largest education technology events, Bett UK is not only a showcase of tools, but a critical space where universities and education institutions examine long-term shifts in teaching, learning, and assessment systems.

Across three days of conversations with university leaders, faculty members, teaching and learning centers, and academic support teams from the UK, Europe, North America, and Asia-Pacific, one message became increasingly clear:

The real value of AI in education lies not in content generation, but in assessment.

Higher Education Is Reframing the Question:

Not “Whether to Use AI,” but How to Redesign Assessment

At Bett UK 2026, discussions around AI had clearly moved beyond adoption debates. Instead, institutions were focused on structural questions:

How can assessment quality improve without increasing faculty workload?
How can students understand academic standards before submission?
How can institutions preserve academic integrity and fairness in the age of generative AI?

All of these concerns point to the same conclusion:
assessment systems themselves must evolve.

For universities, assessment is far more than grading. It underpins learning outcomes, feedback quality, curriculum alignment, and institutional accountability. This is why AI assessment is increasingly viewed not as a single tool, but as core educational infrastructure.

AI Assessment Is Not a “Black Box” — It Is a Bridge

One common concern raised during Bett UK 2026 was whether AI assessment tools might become opaque systems standing between teachers and students.

What we observed was the opposite.

In conversations with faculty and academic support teams, it became clear that well-designed AI assessment tools do not replace teacher–student interaction; they reshape it.

For teachers, AI assessment can:

Identify recurring issues across student work without changing grading authority
Transform repetitive structural feedback into reusable, explainable insights
Free up time for higher-value academic guidance and discussion

For students, AI assessment becomes a safe, repeatable self-review mechanism:

Understanding assessment criteria and academic expectations before submission
Seeing why issues occur, not just final outcomes
Practicing and improving independently without increasing faculty workload

Most importantly, AI assessment creates a shared language between teachers and students.
Instead of repeatedly explaining why marks were deducted, educators can point to clear evaluation logic—while students engage actively with feedback rather than passively receiving results.

In this sense, AI assessment is not a black box.
It is a bridge connecting teacher expertise with student self-directed learning.

“Grade My Essay”: An Underestimated Institutional Need

“Grade my essay” is often treated as an individual student request.
At Bett UK 2026, however, universities highlighted a deeper institutional issue behind it:

Many students do not understand what academic assessment standards actually require.

Faculty consistently noted that student essays often fall short not due to lack of knowledge, but due to weaknesses in structure, argumentation, and academic expression. Significant teaching time is then spent repeating similar explanations—feedback that does not always translate into lasting learning.

When students search for “grade my essay,” they are not simply asking for a score. They are seeking:

Clear judgment of argument quality
Explanation of structure and logical flow
Actionable guidance for improvement

This is precisely where AI assessment delivers the most value—and where misunderstandings often arise.

A Shared Signal from Bett UK 2026:

Institutions Need Explainable AI Assessment

Across discussions with IT departments, teaching and learning centers, and academic leadership, three requirements surfaced repeatedly:

Transparency
Explainability
Alignment with academic standards

Universities remain cautious of opaque AI systems. Any assessment technology that cannot explain its reasoning or align with course objectives is unlikely to be integrated into formal academic processes.

As a result, institutions are increasingly focused on how AI can support evaluation decisions, not replace academic responsibility.

PagePeek’s Perspective: AI as an Extension of Academic Judgment

The conversations at Bett UK 2026 reinforced PagePeek’s direction as an PagePeek:

AI should not make final academic judgments
AI should help educators surface issues faster and articulate standards more clearly
AI should help students understand assessment logic before submission

In PagePeek, assessment is not a standalone scoring feature. It is a feedback system embedded throughout the learning process, designed to amplify—not diminish—academic judgment.

Institutional Impact: Why This Matters Long Term

From an institutional perspective, AI assessment supports:

Consistency across courses and instructors
Higher-quality feedback that students can act on
Reduced faculty burden without compromising rigor
Academic integrity in a generative AI era

This is not a short-term productivity tool.
It is a long-term investment in teaching and learning capacity.

Conclusion: Assessment Determines Whether AI Truly Belongs in Higher Education

The clearest takeaway from Bett UK 2026 is this:

Whether AI is accepted in higher education depends on how it participates in assessment—not writing itself.

If AI only generates content, it remains peripheral to education.
If it helps explain standards, support judgment, and strengthen learning, it can become part of the academic system.

These insights will continue to guide PagePeek’s work in building a clearer, fairer, and more learning-focused AI assessment ecosystem—together with universities and educators worldwide.