Speaker
Description
Essien, O. M.
Federal College of Education (Technical), Ekiadolor Ekiadolor, Benin City, Edo State, Nigeria
georgekennedyresearchers@gmail.com
Track: Research, Innovation and Knowledge Ecosystems
The emergence of neuromorphic computing, which combines principles of human brain functionality with advanced artificial intelligence and low-power computing, presents new opportunities for developing sustainable digital ecosystems and preparing graduates for future technology-driven industries. The study examined the readiness of higher education institutions to adopt brain-inspired neuromorphic systems as a pathway for strengthening digital skills development and supporting industrial transformation in Africa. To achieve the objectives, four research questions and four hypotheses was formulated for the study. A correlational research design was adopted for the study. The population comprised lecturers and final-year students in computer science, and Industrial Technology Education in Nigerian Universities. Sample was selected using multistage sampling techniques. Data were collected using a researcher-developed instrument titled Neuromorphic Technology Readiness and Digital Skills Development Questionnaire (NTRD-SDQ). The instrument was validated by experts in Industrial Technology Education, Computer Engineering, Measurement and Evaluation, while reliability was established using Cronbach Alpha reliability method. Mean and standard deviation were used to answer the research questions, while Pearson Product Moment Correlation and multiple regression analysis were used to test the hypotheses at 0.05 level of significance. The study is expected to reveal the extent to which digital competencies, institutional technology readiness and curriculum preparedness predict readiness for neuromorphic computing education. The findings will provide evidence-based recommendations for universities, policymakers and industry stakeholders on developing future-ready higher education ecosystems, reducing Nigerian digital skills divide and promoting sustainable industrial transformation