COMPUTER VISION (CV) TECHNOLOGY AND ETHICAL VALUE ORIENTATION AS CORRELATE OF PRODUCTIVITY OF BUSINESS EDUCATION LECTURERS IN PUBLIC UNIVERSITIES IN SOUTH EAST, NIGERIA

Abstract

This study investigated computer vision (CV) technology and ethical value orientation as correlates of productivity of business education lecturers in public universities in South-East Nigeria. Two research questions and two null hypotheses guided the study. The study adopted a correlational research design. The population comprised 128 business education lecturers drawn from nine public universities offering business education programmes in the region. Since the population was considered manageable and accessible, the entire population was studied using the census sampling technique. Data were collected using three researcher-developed instruments titled Computer Vision Technology Questionnaire (CVTQ), Ethical Value Orientation Questionnaire (EVOQ), and Business Educators Productivity Questionnaire (BEPQ) containing 10, 10, and 15 items respectively. The face and content validity of the instruments were ascertained by three experts the reliability coefficients were determined using Cronbach Alpha which yielded coefficient values of 0.82 for CVTQ, 0.87 for EVOQ, and 0.88 for BEPQ. Out of 128 copies of the questionnaires administered, 119 copies representing 93% were correctly completed and used for data analysis. Pearson Product Moment Correlation (PPMC) was used to answer the research questions and test the null hypotheses at a 0.05 level of significance using SPSS version 26. The findings revealed a high positive and significant relationship between computer vision technology and the productivity of business education lecturers in public universities in South-East Nigeria. The study also found a moderate positive and significant relationship between ethical value orientation and the productivity of business education lecturers. The study concluded that both computer vision technology and ethical value orientation are important determinants of lecturers’ productivity, with computer vision technology demonstrating a stronger relationship. It was therefore recommended that university administrators invest in computer vision facilities to enhance business education lecturers’ productivity. Furthermore, university management should establish and strengthen ethical guidelines and value-orientation programmes to promote professional conduct, academic integrity, and improved productivity among business education lecturers.