Speaker
Description
Nwike, M. I.
NWAFOR ORIZU COLLEGE OF EDUCATION, NSUGBE, ANAMBRA STATE, NIGERIA.
nwikemichael440@gmail.com
Track: AI, Emerging Technologies and Future Learning
The increasing integration of Artificial Intelligence (AI) into higher education presents new opportunities for enhancing teaching, assessment, research, and academic productivity. Despite the growing relevance of AI technologies, little is known about their acceptance and utilization among Biology lecturers in Colleges of Education in Nigeria. This study investigated the level of acceptance and utilization of AI tools among Biology lecturers in Colleges of Education in South-East Nigeria and examined the factors influencing their adoption. The study adopted a descriptive survey research design grounded in the Technology Acceptance Model (TAM). A sample of 312 Biology lecturers was selected through a multi-stage sampling procedure. Data were collected using a validated questionnaire titled “Artificial Intelligence Acceptance and Utilization Scale (AIAUS)”, with a reliability coefficient of 0.91. Descriptive statistics and multiple regression analysis were used to analyze the data at a 0.05 level of significance. The findings revealed that Biology lecturers demonstrated a high level of awareness and positive acceptance of AI tools. However, the extent of pedagogical utilization was moderate. Perceived usefulness, perceived ease of use, digital competence, and institutional support significantly influenced AI utilization, while concerns regarding ethical issues, data privacy, inadequate infrastructure, and limited professional development opportunities constituted major barriers to adoption. The study further found that digital competence significantly enhanced the relationship between AI acceptance and actual utilization. The study concludes that although Biology lecturers are receptive to AI technologies, effective integration into teaching and learning requires strengthened digital capacity, institutional support, and targeted professional development. The findings provide empirical insights for advancing AI-driven innovation in biology teacher education and promoting future-ready higher education systems in Nigeria. It is recommended that Colleges of Education develop comprehensive AI literacy and capacity-building programmes to facilitate sustainable adoption and effective utilization of AI tools.
Keywords: Artificial Intelligence, Technology Acceptance, AI Utilization, Biology Education, Digital Competence, Teacher Education.