Barriers to Effective Use of AI in Academic Research: Evidence from Lecturers in Bayelsa State
Abstract
The study investigated the barriers to the effective use of artificial intelligence (AI) in academic research among lecturers in Bayelsa State using a descriptive survey research design. The study was conducted among lecturers in the four public universities in Bayelsa State. The population of the study comprised all the 5,000 lecturers working in these universities. A stratified random sampling technique was used to draw a sample of 400 respondents (lecturers) from the population. The instrument for data collection was a researcher-developed questionnaire titled Barriers to AI Use in Academic Research Questionnaire (BAIUARQ). The reliability of the instrument was established at 0.80 using Cronbach’s Alpha, while validity was ensured through expert review by specialists in Educational Technology, Research Methods, and Measurement and Evaluation. Data collected were analyzed using descriptive statistics, including mean and standard deviation, with a benchmark of 2.50 for decision making. The study revealed that lecturers experience moderate but significant barriers to the effective use of AI in academic research, including technological limitations, inadequate institutional support, and individual skill-related challenges. The findings further showed that the interaction of technological, institutional, and individual factors has a moderate influence on lecturers’ adoption and utilization of AI tools. The study concluded that effective AI use in academic research is shaped by interconnected factors rather than isolated variables, and that addressing these barriers requires a holistic approach. The study recommended the provision of structured AI training programs, improved digital infrastructure, and the establishment of clear institutional policies to enhance the effective and responsible use of AI in academic research among lecturers in Bayelsa State.
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