AI is forcing distance education into an assessment reckoning

As essays, assignments and remote exams become easier to game, institutions must rethink how they measure genuine understanding.

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Distance education is not disappearing. In fact, it is becoming more embedded in higher education strategy, with distance enrolment still substantial and institutions under pressure to serve working adults, part-time learners and geographically dispersed students. Inside Higher Ed recently noted that distance education enrolment nationwide stood at 53.2% in 2023, far above pre-pandemic levels, while

Deloitte’s 2026 higher education outlook points to AI, regulation and new delivery models as forces pushing institutions towards reinvention rather than retreat. But the real problem is no longer access or platform choice. It is assessments. If students can outsource essays, rely heavily on generative AI, or get assistance during remote tests, then institutions face a much harder question: what does the qualification still mean?

CONTEXT AND BACKGROUND

For years, distance education was framed mainly as a technology and inclusion challenge. Could institutions provide stable platforms, quality content and enough student support? Those questions still matter, especially in Africa, where connectivity, device access and home environments vary sharply. But AI has shifted the centre of gravity. The issue is no longer simply whether students can learn remotely. The question is whether universities can still verify an authentic understanding remotely. That is a very different problem.

Professional and high-stakes testing bodies are already signalling their discomfort. Reuters reported in February that the Law School Admission Test in the United States ended its online option over cheating concerns, while Times Higher Education reported this month that IELTS pulled back from a UK government bid involving remote testing because of security fears. When organisations responsible for consequential assessments start retreating, it becomes clear that this is not a minor classroom issue. It is a credibility issue.

INSIGHT AND ANALYSIS

Artificial intelligence is forcing this reckoning because it has made traditional written assessment far less trustworthy. A polished essay or take-home assignment no longer proves what many lecturers once assumed it proved. AP reported recently that colleges are increasingly turning to oral exams and live defences because written submissions can now be heavily shaped by AI. That is a profound shift. It means assessment is moving away from static outputs and back towards real-time demonstration of understanding.

This does not mean distance education is doomed. It means its assessment model must evolve. Oral examinations can be conducted virtually through video platforms, structured viva-style questioning and recorded defences.

Recent commentary has also suggested that AI tools can support this process by generating follow-up questions, transcribing responses and helping examiners review consistency, although human judgment still needs to remain central. The more realistic future is not a fully automated assessment, but a more layered assessment: projects, portfolios, staged submissions, short live defences and targeted oral verification.

The temptation, of course, is to respond with more surveillance. Proctoring vendors argue that layered monitoring, computer vision, liveness checks and audio analysis can strengthen integrity. But surveillance alone is not a strategy. It can create false confidence, trigger privacy concerns and disadvantage students whose homes and connectivity do not resemble the assumptions built into these systems. In African contexts, that matters greatly.

IMPLICATIONS

Institutions now need to redesign assessment, not merely defend old formats with new software. That means asking a more educational question: what kind of task best reveals understanding, judgement, communication and originality? In many cases, the answer will be a hybrid model. Teach flexibly, assess more authentically, and verify more directly.

For South Africa and the rest of Africa, the stakes are especially high. Distance education remains essential for widening participation. But if credibility weakens, the very students who rely on these pathways may suffer most. We therefore need approaches that protect standards without importing heavy-handed surveillance models that ignore local realities.

CLOSING TAKEAWAY

Distance education has not failed because of technology. It is being tested because AI has exposed the weakness of assessment methods that were already under strain. The answer is not to abandon online learning, nor to pretend that proctoring software will solve everything. The answer is to build more credible, humane and context-aware models of assessment. That will often mean more oral examinations, more project-based evidence and more thoughtful use of AI as support rather than a substitute. If institutions get this right, distance education can remain both accessible and trustworthy. If they do not, flexibility may survive while credibility quietly erodes.

Author Bio: Johan Steyn is a prominent AI thought leader, speaker, and author with a deep understanding of artificial intelligence’s impact on business and society. He is passionate about ethical AI development and its role in shaping a better future. Find out more about Johan’s work at https://www.aiforbusiness.net