Current educational developments in theories and practices advocate a more personalized, student-centered approach to teach 21st-century skills. However, the existing pedagogical practices cannot provide optimal student engagement as they follow a ‘one size fits all' approach. How can we provide high-quality adaptive instructions at a personalized level? Intelligent tutoring systems with embedded artificial intelligence can assist both students and teachers in providing personalized support. This chapter highlights the role of artificial intelligence in the development of intelligent tutoring systems and how these are providing personalized instructions to students with and without disabilities. This chapter gives insight into the challenges and barriers posed by the integration of intelligent tutoring systems in K-12 classrooms.
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The digitization of technology has changed the way of human interaction within our society in the 21st century. From accessing information, communication, and behavior, almost every aspect of our lives has technology imprints. The field of artificial intelligence (AI) is growing exponentially, and it has become an integral and invisible part of our life (Akshabi et al., 2011). For instance, the SIRI app helps us with direction, phone calls, sending texts, and playing music (Assefi et al., 2015). Google Home and Alexa are for the news update, music, and to control smart devices in our home and apple watch can keep track of fitness and health, news updates, text messages, phone calls, and the list goes on. Data is continuously being collected, analyzed, and used for various purposes, including predicting human behavior and providing unsolicited advice every time we use the web.
AI, deep learning (neural networks), and machine learning (supervised, unsupervised, and reinforcement learning) algorithms shape education technology. Artificial Intelligence in Education (AIED) is changing the way we teach and learn quickly. Companies like Google, Apple, and Amazon have invested millions of dollars in creating software applications related to AIED. Computer-assisted programs using AI begin to penetrate the educational landscape to engage students in meaningful learning at their pace. With the rapid advancement of technology, intelligent tutoring systems are continuously evolving, transforming, and expanding to various fields, including K-12 education.
AI has a profound impact on various sectors, which is evident in recent trends, such as digitization and automation. Innovation in the field of AI has transformed the workforce and labor market. Middle-skills jobs that require a more routine-oriented and repetitive task are more susceptible to automatization and can save a considerable amount of money to employers. Many jobs with some degree of automation are moving from partial to full automatization. Furthermore, to meet the workforce's demand in the current scenario and for future disruptions, the educational institute must integrate AI to prepare students for future jobs (Shiohira & Keevy, 2020).
Development in AI is continuously evolving and expanding; however, it is still in infancy in the education industry. The United Nations Educational, Scientific, and Cultural Organization (UNESCO) suggested countries to develop policies regarding the implementation of AI to enhance educational innovations. The United States, Singapore, and India have initiated new educational reform strategies to research, develop, and implement AI technology in education (Yufeia et al., 2020). Intelligent, adaptive, and personalized learning approaches are gaining popularity in schools and universities globally. A massive amount of student data is used to improve learning and teaching capabilities. The K-12 school system faces challenging tasks to maintain the privacy of these valuable data.
The Intelligent Tutoring Systems (ITS) are computer-based programs designed to replicate one-on-one human tutoring using AI. ITS are highly adaptive, interactive, and able to customize students' learning by providing individualized instructions and immediate feedback without human teachers' intervention (Erümit & Çetin, 2020). ITS uses various computational models related to cognitive sciences, AI, computational linguistics, and mathematics. ITS have been developed for different domains, including language learning (Tafazoli et al., 2019), reading comprehension (Wijekumar et al., 2017), physics (Graesser et al., 2004), algebra (Phillips et al.,2020), law (Pinkwart et al., 2009), physiology (Alqahtani & Ramzan, 2019), and meta-cognitive skills (McCarthy et al., 2018).
The use of AI to support SWDs is still in its infancy and can impact their education in a positive way. Some studies explored ITS's effectiveness in educating students with disabilities and have found that the integration of ITS, based on artificial intelligence, has been promising (Alkhatlan & Kalita, 2018; Mondragon et al., 2016). As the school system faces a shortage of teachers, investing in AI technology will provide students with intelligent tutors and solve teacher attrition (Edwards & Cheok, 2018). This book chapter discusses the role of AI technology in K-12 classrooms and its possibilities and challenges in teaching students with and without disabilities.