The National Open University of Nigeria (NOUN) and the Commonwealth of Learning (COL) have brought together education leaders and specialists to examine how open and distance learning institutions can maintain quality as artificial intelligence and other digital technologies transform higher education.
The two-day regional workshop was organised by NOUN’s Regional Training and Research Institute for Distance and Open Learning (RETRIDOL) in collaboration with COL. It was held at NOUN’s headquarters in Abuja from 19 to 20 August 2026.
Participants included university administrators, researchers, policymakers, quality-assurance professionals and open and distance learning practitioners from different West African countries.
Why the workshop was necessary
Higher education is changing rapidly as institutions adopt technologies and learning models such as:
Artificial intelligence.
Learning analytics.
Open Educational Resources.
Digital learning platforms.
Micro-credentials.
Data-driven learning systems.
Cross-border education.
These innovations can expand access to education and improve student support. However, they can also introduce concerns about accuracy, assessment integrity, privacy, recognition of qualifications and the overall quality of learning.
NOUN Vice-Chancellor Professor Uduma Oji Uduma said institutions must ensure that technological innovation is accompanied by accountability, quality and continuous improvement.
He explained that confidence in open and distance learning qualifications depends significantly on robust, evidence-based and appropriate quality-assurance systems.
Artificial intelligence is changing teaching and assessment
Artificial intelligence is increasingly being used to produce learning content, summarise academic materials, provide feedback and support assessment.
While these tools can help students understand difficult concepts and study more efficiently, institutions must also address questions such as:
How can the accuracy of AI-generated educational content be confirmed?
How should institutions distinguish legitimate learning support from academic misconduct?
How can assessments remain credible when generative AI tools are widely available?
How should student information be protected when learning-analytics systems are used?
What evidence should institutions retain when automated systems make recommendations about learners?
These questions are especially important in open and distance learning, where students, lecturers and support personnel may interact primarily through digital platforms.
Regional study to support recommendations
Ahead of the workshop, COL commissioned a status study to examine how quality-assurance systems in West Africa are responding to emerging developments in distance education.
Participants reviewed the findings, compared institutional experiences and considered their implications for future quality-assurance frameworks.
The workshop was intended to produce practical and regionally appropriate recommendations. However, the event itself did not announce a new NOUN assessment rule or binding NUC regulation.
Students should therefore avoid interpreting the workshop as an immediate change to their TMA, examination or programme requirements.
What this means for NOUN students
The development signals that students may gradually see greater attention given to:
The quality and credibility of digital course content.
Transparent use of artificial intelligence.
Stronger academic-integrity measures.
Better accessibility for learners with disabilities.
Improved learner-support systems.
More reliable online assessments.
Responsible use of student learning data.
Recognition and quality control for micro-credentials.
Students should use AI as a learning aid and not as a substitute for studying, understanding course materials or complying with institutional assessment rules.
Information generated by AI should also be verified against reliable course materials and authoritative academic sources.
Implications for education-technology providers
Platforms serving NOUN and other distance learners may increasingly need to demonstrate that their products are accurate, transparent, inclusive and capable of supporting genuine learning outcomes.
Important quality measures include:
Citing the source of academic information.
Clearly identifying AI-generated content.
Showing confidence or verification status where appropriate.
Protecting students’ personal information.
Providing accessible and mobile-friendly interfaces.
Keeping records that support accountability.
Preventing tools from being misrepresented as official university platforms.
At NOUN Update, these developments reinforce the importance of building student-support technology that complements official university systems and promotes responsible learning.
No new academic rule has been announced
As of this report, the workshop represents an institutional and regional quality-assurance initiative. It should not be presented as a newly approved examination, TMA or admission policy.
NOUN students should continue following official university instructions while monitoring credible channels for any future policies arising from the workshop recommendations.
The original report can be read through the official NOUN news platform.
NOUN Update will continue monitoring developments affecting digital learning, assessment technology and student support across Nigeria’s open and distance learning sector.
