Artificial intelligence integration in education is proven to be an easier and convenient way of delivering knowledge to students and hence became the demand of 21st-century classrooms. The findings from the literature review show that implementing artificial intelligence in education by following different pedagogical models of artificial intelligence in education (i.e. the SAMR model, the TPACK model, and the TAM model) can lead to fruitful outcomes in the teaching and learning process, and also this study would help in fulfilling the knowledgeable, contextual, and pedagogical gaps for the integration of artificial intelligence in the era of digitization of education.
Top1. Introduction
The 21st century has witnessed unprecedented technological advancements, leading to a digitally revolutionized world as depicted in science-fiction movies (Küçük & Gündoğdu, 2020). This transformation has been primarily driven by digitalization, which has permeated virtually every aspect of human life. At the forefront of this digital revolution stands Artificial Intelligence (AI), a technology that is reshaping industries and transforming the way we interact with technology. AI's cognitive abilities, including problem-solving, adaptive learning, and decision-making, are increasingly mirroring human-like intelligence (Zhou, Zhang, & Xu, 2020). One domain where AI has gained substantial ground is education, revolutionizing traditional teaching and learning methods in educational institutions (Kučak et al., 2018). The integration of AI in education has yielded remarkable changes, ranging from enhanced efficiency and global learning opportunities to personalized educational experiences and more intelligent content delivery. By harnessing the potential of AI, educational institutions have witnessed a paradigm shift in teaching practices, administration, and overall effectiveness. Over the past decade, AI has rapidly risen in prominence within the education landscape, fostering innovative approaches to teaching and learning (Sun & Zhang, 2021). Its applications are not limited to specific educational levels or subject areas but encompass various sectors, from primary and secondary education to higher education and professional training. AI's influence in education spans several key areas. Firstly, it streamlines administrative processes, such as enrollment management, student record keeping, scheduling, and resource allocation, enabling educational institutions to operate more efficiently (Kovalchuk, 2021). Secondly, AI-powered tools analyze vast educational data to create personalized curricula and learning materials tailored to individual student needs and learning styles (Zhang et al., 2020). Thirdly, AI facilitates adaptive learning, where learning platforms adjust the pace and content based on individual student progress and performance, ultimately enhancing learning outcomes. Additionally, AI enables the integration of immersive technologies, like augmented reality, virtual reality, and three-dimensional simulations, enriching the learning experience and simplifying complex concepts (Sandhya & Maheshwari, 2021). The success of AI in education is underpinned by various technical advancements, including natural language processing, machine learning algorithms, computer vision, and data analytics (Zhou, Zhang, & Xu, 2020). These technologies empower AI systems to process vast amounts of educational data, understand natural language, and provide personalized learning experiences at an unprecedented scale. Hence, the continuous advancement of AI is expected to further amplify its impact on education, ushering in an era of transformative educational innovation. This chapter explores the diverse applications of AI in education, from administrative tasks to personalized learning experiences, and highlights the technical advancements supporting its success in this domain. By embracing AI's potential, educational institutions can enhance learning outcomes, empower educators, and offer students a more enriching and adaptive educational journey. This research aims to study how using advanced AI in Education 4.0 in digital classrooms affects teaching methods, student involvement, and learning results. We want to understand how AI changes regular classes into exciting, technology-based learning places. One important part of our study is to find and talk about the problems that come up when AI for Education 4.0 is used in digital classrooms. These issues include technical challenges, worries about keeping data private, and how AI should be used in teaching. Apart from finding these problems, we also want to learn about good teaching methods that can overcome the challenges of using AI for Education 4.0 in digital classrooms. Our goal is to find ways for AI tools to work well with human teachers. We want to use these solutions to not only solve the problems but also make learning even better by using AI. By carefully handling the technical, ethical, and teaching parts, our research wants to make the most out of AI for Education 4.0. We hope this will bring better and more effective learning in the digital age.