The Kwame Nkrumah University of Science and Technology (KNUST), Kumasi College of Engineering is set to develop a bespoke Artificial Intelligence (AI) model through collaboration between the Responsible AI Lab (RAIL), the Distributed IoT Platforms, Privacy and Edge-Intelligence Research (DIPPER) Lab, and other research centres. The initiative will embody the college’s core values, promote the ethical use of AI, and address local educational and research needs within engineering education.
The announcement was made during the College of Engineering’s session of the 11th KNUST Summer School, held at the Kumapley Auditorium, which focused on how AI can redefine teaching, learning, and research in engineering education.
Professor Kwabena Nyarko Biritwum, Provost of the College of Engineering, emphasised the need for academia to adapt deliberately to the rapid evolution of AI technologies in both education and industry.
He reminded participants that as educators, they play a crucial role in determining how AI is integrated into the classroom, research, and professional practice.
“As a college, we must ask ourselves what we should do with AI and how we can adapt these tools to lift our unique concepts and enhance productivity,” he said.
He encouraged faculty members to use the Summer School as a platform to experiment, learn, and innovate with AI while preparing students to graduate not only as competent users of technology but also as critical thinkers and ethical innovators. His message set a forward-looking tone, calling for readiness, responsibility, and creativity in engineering education.
Professor Jerry John Kponyo, Principal Investigator and Scientific Director of the Responsible AI Lab (RAIL), speaking on “Responsible AI: Opportunities and Challenges for Modern Engineering Education,” said that AI is transforming every field of human activity, but its potential must be guided by principles of ethics and accountability.
He outlined key principles such as fairness, reliability, privacy, transparency, sustainability, and accountability, which form the backbone of responsible AI practice.
Drawing on the RAIL FACETS Framework, Professor Kponyo explained how these principles can inform curriculum design, research, and professional development. He urged collaboration across disciplines, saying, “Education is the foundation, and engineers are the custodians of the future.”
Dr. Andrew Selasi Agbemenu, Deputy Scientific Director of the DIPPER Lab, presented on “Engineering AI Fluency-Best Practices for LLM Integration in Engineering Workflows.”
He introduced an AI Fluency Framework built around automation, augmentation, and agency, demonstrating how AI tools such as ChatGPT, Claude, and Gemini can be used for research, ideation, documentation, and project management.
He also presented the CLEAR prompting framework, which focuses on context, length, examples, audience, and role, to guide effective communication with AI models. “Using clear prompting frameworks leads to professional excellence,” he said. “The clearer your input, the better your output.”
A question-and-answer session followed, during which participants discussed strategies for preparing students for AI-integrated learning and adapting teaching methods to evolving technologies.
The dialogue concluded with a shared vision to develop a College of Engineering-specific AI model through collaboration among RAIL, DIPPER Lab, and other research centres.
The proposed model will reflect the college’s values, promote ethical AI use, and address local educational needs, positioning KNUST as a leader in responsible AI innovation in higher education.
The day also featured a hands-on session led by Dr. Theresa-Samuelle Adjaidoo and Dr. James Okae of the Department of Computer Engineering, where participants explored generative AI tools such as ChatGPT, Copilot, and Gemini to design lesson plans, quizzes, and course outlines.
They also worked with virtual lab platforms like Labster and MATLAB Grader, and assessment tools such as Gradescope and Turnitin AI, which demonstrated AI’s potential to enhance learning, streamline evaluation, and maintain academic integrity.
