Integration of Artificial Intelligence Tools in Academic Staff Development Programmes for Goal Achievement in Public Universities in Rivers State

Abstract

The study examined the integration of artificial intelligence tools in academic staff development programmes for
goal achievement in public universities in Rivers State. Three research questions and one hypothesis guided that
study. The study adopted a descriptive research design to examine the integration of artificial intelligence tools in
academic staff development programmes for goal achievement in public universities in Rivers State. The design
was chosen because it enables the investigation of relationships between variables without manipulation. The
population comprised 3,787 teaching staff from three public universities, including one federal and two state
institutions. A 10% sample was drawn proportionally from each university, and respondents were randomly
selected across faculties and administrative levels to enhance representativeness and minimise bias. Data were
collected using a structured questionnaire titled Integration of Artificial Intelligence Tools in Academic Staff
Development Programmes for Goal Achievement Questionnaire (IAITASDPQ). The questionnaire’s validity was
confirmed through expert review, and reliability was established with Cronbach’s Alpha (α = 0.76), indicating
high internal consistency. The study found that artificial intelligence tools enhance academic staff development by
improving teaching, research productivity, and administrative efficiency, with no significant differences between
male and female staff, although challenges such as limited infrastructure, high costs, and low AI literacy were
identified. It concluded that integrating AI into staff development programmes strengthens professional
competence and supports institutional goal achievement when accompanied by adequate training, policy support,
and resource allocation. Therefore, it is recommended that public universities in Rivers State provide accessible
AI tools, develop staff training initiatives, and improve digital infrastructure to ensure effective adoption and
maximize the benefits of AI for achieving institutional objectives.