Integrating Computer Science with Management Education: A Framework for Enhancing Decision-Making Skills in the Digital Age

Abstract

Management education cannot afford to remain bereft of computer science in the age of the digital. Integration of computer science in management education is important so as to improve decision making skills. Referred in this research: A framework using artificial intelligence (AI), machine learning, gamification and data driven analytics to enhance strategic thinking in management studies. The study examines four main algorithms i.e. Decision Trees, Random Forest, Support Vector Machine (SVM) and Artificial Neural Network (ANN) to figure out which one best suits in predictive decision making. The experimental results also show that ANN has the maximum accuracy of 92.3%, Random Forest (89.5%), SVM (86.7%), and Decision Tree (83.2%). The comparative analysis with existing methodologies argues that the enhancement of decision efficiency by 15% across management education can be achieved by integrating AI driven models. This findings show that AI powered learning tools, enterprise architecture frameworks and simulation based training constitute much more in business environment for data driven decision making. According to the study, management education will flip with the addition of adaptive AI models, predictive analytics, and gamified learning, which can transform it to become more interactive, analytical and industry related. Personalized AI driven educational systems should be further optimized and are subject to future research.