The Role of Computational and Al-Assisted Tools in Interdisciplinary Teaching

Abstract

In response to the growing complexity of global challenges and the evolving demands of the workforce, interdisciplinary education has emerged as a crucial pedagogical approach. This chapter explores the transformative role of computational and Al-assisted tools in facilitating interdisciplinary teaching and learning. It outlines how technologies such as intelligent tutoring systems, Al-powered simulations, natural language processing tools, and data analytics platforms foster integrative learning experiences by bridging disciplinary divides, personalizing instruction, and enhancing learner engagement. By enabling modelling, data visualization, language translation, and collaborative problem-solving, these tools support the development of critical thinking, creativity, and systems-level understanding. Real-world case studies demonstrate the application of Al in collaborative student projects across domains like. public health, climate change, and smart city planning. The chapter also critically addresses ethical considerations, including algorithmic bias, data privacy, inclusivity, and digital literacy. It concludes by emphasizing the need for informed and ethical implementation of Al in education, calling for collaborative efforts among educators, institutions, and policymakers to realize the full potential of these technologies in shaping a more connected and adaptive educational paradigm.