JAMB Plans Leveraging AI To Improve UTME Access For Candidates With Disabilities

The Joint Admissions and Matriculation Board (JAMB) is planning to leverage artificial intelligence (AI) to improve the accessibility of the Unified Tertiary Matriculation Examination (UTME) for candidates with disabilities, as part of its broader commitment to inclusive higher education in Nigeria.

JAMB Registrar, Prof. Is-haq Oloyede, disclosed the plan during the National Engagement on Inclusive Higher Education and Artificial Intelligence organised by the JAMB Equal Opportunity Group (JEOG) in Abuja.

According to Oloyede, artificial intelligence presents a unique opportunity to expand access to education, provided it is deployed responsibly and ethically.

"AI is just like the internet or the cell phone. It is value-free. It can be used positively and it can be used negatively. It is only important to use it to serve our purpose while remaining careful of the merits."

He stressed that AI should be viewed as a tool for enhancing, rather than replacing, human intelligence.

"There is no escape from AI. The more we engage with it without losing our natural and native intelligence, the better it will be for us and society. AI cannot replace people except those who fail to know and utilise it for good reason."

The JAMB registrar also urged universities and other educational institutions to move beyond discussions about artificial intelligence and begin applying the technology to solve practical challenges in teaching, learning and educational access.

Speaking at the event, Chairman of the JAMB Equal Opportunity Group, Emeritus Prof. Peter Okebukola, explained that AI could significantly improve how UTME is administered to candidates with disabilities, particularly those with visual impairments.

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ALSO READ: JAMB: Over 4,216 Candidates with Disabilities Admitted Into Tertiary Institutions in 10 Years

He noted that one of the recurring challenges involves examination questions containing diagrams, maps, and other visual elements that are inaccessible to blind candidates.

According to him, AI can automatically identify equivalent questions that assess the same learning objectives without relying on visual materials.

"You can write an AI algorithm that goes into the item bank of Biology and picks out questions without diagrams that assess the same content. In milliseconds, it can generate an appropriate set of questions. The same can be done for other subjects."

Okebukola explained that JAMB already modifies examinations for visually impaired candidates by excluding diagram-based questions where necessary while ensuring the alternative questions maintain the same standard and level of difficulty.

It was also stated that JEOG has supported 4,213 candidates with disabilities over the past 10 years, comprising persons with visual impairment, albinism, autism and other special needs seeking admission into universities, polytechnics and colleges of education.

However, despite the progress recorded, Okebukola identified inaccurate disability declarations during UTME registration and inaccessible examination items as persistent operational challenges.

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He noted that some candidates are mistakenly registered under the wrong disability category, creating logistical difficulties when examination arrangements have already been made.

"One challenge is in completing the registration form. Some candidates will say they have visual impairment or they have one form of disability or the other, whereas it was misfilled for them."

"By the time you say, wait, no, I can't come to your center. Why should I come? I can't see. I am visually incapable. So that gives us some challenges."

He, however, expressed optimism that artificial intelligence would help address many of these issues by improving examination design, candidate profiling and the delivery of accessible assessments for learners with disabilities.

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