SKILLS NEEDED BY BUSINESS EDUCATORS FOR PREDICTIVE MAINTENANCE OF OFFICE MACHINES IN PUBLIC COLLEGES OF EDUCATION IN ANAMBRA STATE

Abstract

The study determined the skill needs of business educators for predictive maintenance of office machines in public colleges of education in Anambra State. One research question guided the study, and one null hypothesis was tested. A descriptive survey research design was adopted. The population of the study consisted of 83 business educators in two public colleges of education in Anambra State. The entire population was studied without sampling because the population was manageable. A structured questionnaire, which was validated by three experts, was used for data collection. Cronbach alpha was used to measure the internal consistency, which yielded an overall reliability coefficient of 0.72. The researcher administered 83 copies of the instrument with the help of four research assistants using the direct method on the respondents. Mean and standard deviation were used to answer the research questions, while the t-test was used to test the null hypothesis at a 0.05 level of significance. The outcome of the study disclosed that skills for predictive maintenance of office machines were highly needed by business educators in public colleges of education in Anambra State. Also, business educators did not differ significantly in their mean ratings on skills needed for predictive maintenance of office machines in public colleges of education in Anambra State based on institutional ownership. The study concluded that skills improvement for predictive maintenance of office machines were highly needed by business educators in colleges of education in Anambra State because they appear not to have the technical background to promptly identify machines that were not in good working conditions. Among others, it was recommended that business educators in colleges of education in Anambra State should undergo professional training and development programmes on predictive maintenance with servicing and maintenance companies to enable them quickly to detect, analyze, and handle issues affecting the usability of office machines before they break down