Harnessing the Potential of Artificial Intelligence for the Management of Secondary Schools in Bayelsa State, Nigeria

AbstractThe study investigated the potential of harnessing artificial intelligence (AI) for the management of secondary schools in Bayelsa State, Nigeria. Employing a descriptive survey research design, the study was guided by two objectives: to examine the current level of utilization of AI tools in school management, and to identify the perceived challenges affecting their integration into administrative operations. The population comprised principals and teachers from public secondary schools across Bayelsa State, from which 350 respondents were selected using stratified random sampling techniques. Data were collected using a structured instrument titled “Artificial Intelligence Utilization and Challenges in School Management Questionnaire” (AIUCSMQ), validated by experts, with a reliability coefficient of 0.88 determined through Cronbach Alpha. The data were analyzed using mean and standard deviation to address the research questions. Findings revealed a low level of AI utilization in secondary school management, despite its perceived potential to improve administrative efficiency. Major challenges identified include inadequate infrastructure, limited technical support, budgetary constraints, and resistance to change among staff. Based on the findings, the study recommended investment in infrastructure and training, the development of AI-supportive policies, and the establishment of local technical support systems to improve AI adoption and management effectiveness in secondary schools.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-01
DOI
https://doi.org/10.5281/zenodo.17232613
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
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article

Harnessing the Potential of Artificial Intelligence for the Management of Secondary Schools in Bayelsa State, Nigeria

Zenodo (CERN European Organization for Nuclear Research)
Genomics and Phylogenetic Studies
article

Harnessing the Potential of Artificial Intelligence for the Management of Secondary Schools in Bayelsa State, Nigeria

article en

Abstract

AbstractThe study investigated the potential of harnessing artificial intelligence (AI) for the management of secondary schools in Bayelsa State, Nigeria. Employing a descriptive survey research design, the study was guided by two objectives: to examine the current level of utilization of AI tools in school management, and to identify the perceived challenges affecting their integration into administrative operations. The population comprised principals and teachers from public secondary schools across Bayelsa State, from which 350 respondents were selected using stratified random sampling techniques. Data were collected using a structured instrument titled “Artificial Intelligence Utilization and Challenges in School Management Questionnaire” (AIUCSMQ), validated by experts, with a reliability coefficient of 0.88 determined through Cronbach Alpha. The data were analyzed using mean and standard deviation to address the research questions. Findings revealed a low level of AI utilization in secondary school management, despite its perceived potential to improve administrative efficiency. Major challenges identified include inadequate infrastructure, limited technical support, budgetary constraints, and resistance to change among staff. Based on the findings, the study recommended investment in infrastructure and training, the development of AI-supportive policies, and the establishment of local technical support systems to improve AI adoption and management effectiveness in secondary schools.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 49%
Genomics and Phylogenetic Studies
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Harnessing the Potential of Artificial Intelligence for the Management of Secondary Schools in Bayelsa State, Nigeria · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS