The Impact Of Artificial Intelligence On Undergraduates’ Effectiveness In Institutions Of Higher Learning

Abstract

One could argue that artificial intelligence (AI) is best understood as a digital platform that employs cutting-edge techniques to solve complex problems in a way that is similar to human intelligence. The purpose of this study is to analyse how AI affects undergraduate effectiveness in higher learning institutions. The study's population set consisted of 600 undergraduate students from the selected institutions of higher learning in South-Eastern, Nigeria. The sample size obtained by the Krejcie and Morgan (1970) sampling procedure was 234, which reflected the quantity of survey instruments deployed. The Cronbach Alpha method was also employed to assess the instrument's reliability; the results showed a 0.899 coefficient, indicating that the items are dependable and internally consistent. 219 copies, or 94% of the total survey instrument were distributed; of those, 208 copies (88% of the returned copies) were valid and used in the study's analysis. Finally, the collected data set was tested and evaluated using the Descriptive (Mean) and Inferential Statistical tools of the Statistical Package for Social Sciences software. The outcome of the statistical analysis suggests that artificial intelligence positively impacts undergraduates’ effectiveness in institutions of higher learning. Despite the ethical limitations that professional analysts see in performance and the commitment to excellence of aspiring young adults, it is discovered that the use and implementation of AI enhances effectiveness, and also guarantees greater viability for undergraduates. The study concludes that understanding AI and its capabilities not only gives undergraduates a great opportunity to progress in their chosen careers or jobs, but it can also be a veritable competency skill set required to shape young adults into strong professional characters.