Artificial intelligence—unlike conventional beliefs—has often been structured around supplementing human effort and capability. Right from simplistic desktop assistants to advanced machine learning protocols found in supercomputers, the primary function of artificial intelligence has prioritized the removal of brain fog in its human operators by carrying out cognitively laborious yet monotonous tasks. As a result of committed AI development over the last few decades, the arrival of generative artificial intelligence has kicked off renewed debates among businessmen and educationists alike. The stupendous improvement in language models and their enhanced ability to understand human language has rekindled the demand and prospects of adaptive learning among other AI-supported technologies. With all the clamor surrounding the presence of AI and AI-generated content in education, AI tutors are among the rare minority that has so far missed public attention, unlike their other counterparts. While this is partly due to skepticism, widespread concerted efforts toward tapping into this potential academic niche might still take some time to gain traction.
That being said, AI tutoring and intelligent tutoring systems are in no way recent, and their conceptualization goes back to the early 1980s. The primary goal of these systems is to provide lessons and human-like insights into subjects of study without the presence of a teacher. Considering the concept has existed for over four decades, the recent uptick in interest and public participation in AI and associated systems might just rekindle intrigue in AI tutoring. While the field of research in this specific area has been far from abandoned, recent events might just kick-start a revolution in creating intuitive educational solutions that might change the face of academics as we know it.
Understanding AI Tutors and How They Work
Intelligent tutoring systems can be key components of adaptive learning technologies.
AI tutors and tutoring systems are computer-based intelligent and autonomous models that are capable of administering lessons and key educational concepts to students with little to no human intervention. It is interesting to note that AI tutors and the concept of automated tutoring systems have been around for a considerable period. The first of its kind, the LISP tutor was developed in 1983 to allow students to learn and improve their programming skills. Interestingly, despite this prolonged history of conceptualization and development, widespread implementation and upscaling have still not seen the light of day. With the arrival of complex language model artificial intelligence, this lull in AI tutoring and its development might be about to end for good. The recent pandemic catapulted entire institutions into a state of remote learning and blew open a pandora’s box—only for both academicians and students to discover numerous challenges in the new model. Following the return to brick-and-mortar institutions, it is evident that many students have grown to prefer remote learning. This rise in demand presents the tech industry with opportunities to develop tutorial AIs in the online tutoring space.
AI tutors will essentially be able to assess and remark upon student performance in addition to providing lessons. While most current models remain limited to platforms that point out errors and potential areas for improvement after online student assessments, the future of AI tutoring will become highly specific and nuanced to the individual student. Apart from AI-based scoring models, the core purpose of intelligent tutoring will remain on students who expect individual attention and learning adapted to their unique objectives. This can work in several ways where machine learning algorithms are deployed efficiently to study emerging patterns and data from student usage analytics. While the AI tutoring system will analyze and compile academic material into an easily-understandable format, the intelligent tutor will also keep track of the questions asked and expected responses. With the help of data analytics, AI tutors will then predict student questions and frequent doubts to efficiently remodel the course material and adapt to common student concerns. This malleability of the intelligent tutoring system can set the stage for the future of AI in education.
The Functions of AI Tutors in Higher Education
AI tutoring has great potential provided it is deployed effectively in conventional educational environments.
AI tutoring can have several implications for higher education. The consistent movement in the AI industry will invariably translate into tangible progress in the world of education technology. Apart from conventional tutoring, intelligent systems can also help with the augmentation of concepts and topics to suit students’ unique needs. Often, books and other study materials showcase only between one and three examples and case studies. Conversely, AI tutors can be equipped with robust machine learning protocols to synthesize a vast array of examples exhibiting the same core concept, allowing students to understand topics better. Moving beyond chatbots, AI tutors are capable of being higher up on the interactivity quotient, allowing the student to engage better and the system to adapt to the student’s behavioral and learning patterns. Moreover, personalized feedback and tips are a key part of intelligent tutoring systems that allow students to reflect on their performance and balance their strengths in future assessments. This can also become the basis for the future of testing in higher education.
The utilization of multimedia accessories and support in enhancing learning outcomes is another advantage as it paves the way for easier conceptualization and visual understanding of key topics. Generative artificial intelligence has made this easier by slowly bringing to light the ease of creating images, video, and text on command. This has been quite the spectacle in recent times ever since ChatGPT’s launch and subsequent success. Lastly, intelligent tutoring systems can be made capable of deep learning and analytical insight to allow them to predict emerging patterns in student learning and performance.
Future Prospects of AI Tutoring
AI tutors hold the potential to change the landscape of modern education
AI tutoring is one among the many prospects of artificial intelligence technology that might see emerging trends and newfound growth. As the integration of artificial intelligence with educational tools gains prominence, intelligent tutoring systems might be prioritized to deliver support to students that require academic assistance to fulfill their ambitions. However, it must be understood that AI tutors are in no way a replacement for human teachers, and human relationships remain central to the process of learning. Traits like intuition and critical thinking can only be honed via prolonged processes and exposure to real-life situations in academia. As in most cases, AI tutoring, too, serves only to support existing human structures and professions and does not seek to replace them. Eventually, education systems might need a revamp to better accommodate these novel technologies and student support tools.