Harnessing Computational Intelligence for Educational Transformation

Abstract

The chapter explores opportunities for implementing Computational Intelligence (CI) in education through two primary perspectives: teacher-centric intelligence and student-centric intelligence. Within the realm of teacher-centric intelligence, we discuss the potential benefits of Intelligent Teaching Assistant Systems (ITAS), automated student assessment, Student Progress Analytics (SPA), and strategies for professional development and upskilling of educators. Transitioning to student-centric intelligence, we examine Intelligent Tutoring Systems (ITS), simulations and gamification, real-time feedback mechanisms leveraging NLP, EDM, and LA technologies, as well as accessibility tools aimed at promoting equity in education. Additionally, the paper addresses potential challenges and limitations of CI adoption in education, including ethical considerations, data privacy and security issues, infrastructure limitations, socioeconomic disparities, biases in AI models, and human factors in AIED implementation.