Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and accelerate progress towards SDG 4. According to a Forbes article published in March 2023, generative-relevant use cases of AI in the education industry already present a significant enterprise opportunity, with an estimated market of $2.6 billion in 2023 which is expected to grow at a rate of 32.0% until 2026.
As with previous disruptive technologies, such as calculators, computers, and the internet, generative AI technologies will become another tool in the education ecosystem. It is time to rethink how to learn, grow, and develop in a world where generative AI is commonplace and be prepared for further transformations.
Further, educators see opportunities to use AI-powered capabilities such as speech recognition to increase the support available to students with disabilities, multilingual learners, and others who could benefit from greater adaptivity and personalization in digital tools for learning. They are further exploring how AI can enable writing or improving lessons, as well as their process for finding, choosing, and adapting material for use in their lessons.
Applications of AI in the Education Sector
The first and foremost applications of AI in the education industry involve freeing up the time of the educators from the administrative tasks saving them from potential exhaustion and burnout. According to a study conducted by McKinsey & Company teachers can devote only 49.0% of their time in direct interaction with students. AI can help in automating routine administrative tasks, streamlining their workflows, and redirecting their efforts towards interacting with the students fostering learning and development.
AI can improve teacher productivity across areas such as lesson planning and differentiation, grading and providing quality feedback, teacher-parent communication, and professional development. It can also help educators identify children’s literacy levels, uncover where students are struggling, and deepen their personalized learning experiences.
Furthermore, AI can expand the scope of learning beyond the boundaries of the traditional classroom setup. It would allow the school, society, and enterprises to organically integrate so that students can get a more open and diversified educational experience.
AI robots are redefining the processes across a variety of industries and education is no exception. They can effectively add interest in the classroom, stimulate students’ innovative ability, and rely on information technology to enhance students’ knowledge and the ability to obtain information. They can also perceive changes in student emotions and grasp their learning effects which is conducive to teaching students in accordance with their aptitude.
The World of Intelligent Teaching Systems
The most direct result of the application of AI in education is the Intelligent Teaching System (ITS). It emerged based on computer-assisted teaching. It is an open human-computer interaction system formed by student-centered, computer-based, and computer-simulated thinking processes of teaching experts. At present, the intelligent teaching system has become the main form of AI application in education.
They can aid in the abstraction of the learning environment. This can be done by simulating a realistic working environment in which the student can learn the task. This can reduce the possible danger of training using the actual equipment. It also provides for the lack of domain experts who can devote their expensive time to training novices. Therefore, a realistic simulated learning environment can reduce both the cost and the risks of training. Advanced Cardiac Life Support (ACLS) Tutor is one such system in which a student takes the role of team leader in providing emergency life support for patients who have had heart attacks. The system not only monitors student actions but also runs a realistic simulation of the patient's condition and maintains an environment that is reasonably faithful to the real-life situation. This helps the educators to test the knowledge of the students and the students to gain experience. The Design for Manufacturing Tutor is another such system.
Contrary to the simulation systems are the knowledge systems that impart lessons in a decontextualized manner. These systems provide problems for the learner to solve without trying to connect those problems to a real-world situation and are designed to teach abstract knowledge that can be transferred to multiple problem-solving situations.
Another great way in which AI can revolutionize the education industry is through the development of cognitive tutors. The core of this lies in the psychology of human skill acquisition. For instance, SHERLOCK has tutorial actions associated with each state in the effective problem space. Similarly, the LISP tutor is another such system based on cognitive psychology.
AI also aids collaborative learning to make the learning experience more enjoyable and promote healthy competition. This involves students working in groups to solve problems. These environments are beneficial, both cognitively and socially. In these situations, the focus of the interactions is not typically between the teacher and the learners, as students can teach each other without input from the instructor. Although collaborative learning is in its infancy, there have been some efforts in this direction. For instance, Belvedere provides a set of tools to help groups of students construct theories such as on evolution, also allowing them to critique these theories later.
Government and Institutional Initiatives to Incorporate AI in the Education Industry
The greatest step in the direction of incorporation of AI in the field of education is Sustainable Development Goal 4 (SDG 4) by UNESCO. It aims to achieve the Education 2030 Agenda while ensuring that its application in educational contexts is guided by the core principles of inclusion and equity. It intends to address current inequalities regarding access to knowledge, research, and the diversity of cultural expressions and to ensure AI does not widen the technological diversities within and between countries.
Furthermore, UNESCO has developed within the framework of the Bejing Consensus a publication aimed at fostering the readiness of education policymakers in artificial intelligence. This publication namely Artificial Intelligence and Education: Guidance for Policy-makers, aims to generate a shared understanding of the opportunities and challenges that AI offers for education, as well as its implications for the core competencies needed in the AI era. It aims to enhance human capacities and protect human rights for effective human-machine collaboration in life, learning, and work, and sustainable development.
The Indian government is also taking initiatives in the field with the New Education Policy (NEP). As per the policy, the school children will be exposed to crucial skills such as digital literacy, coding, and computational thinking from a young age, through the teaching of contemporary subjects such as AI and design thinking, 3-D machining, big data analysis and machine learning. In addition, colleges may also offer targeted training in low-expertise tasks for supporting the AI value chain such as data annotation, image classification, and speech transcription.
One such initiative is taken by Telangana Public Schools to deploy AI tools to automate several processes such as formative assessments, marking attendance, and logging mid-day meal data, among others. It is also taken as a medium to teach English and other languages.
Further, the application named Learning Matters’ Tara is being designed to improve teacher’s vocabulary. Tara is a dynamic, two-way interactive, personalized teacher assistant that works on Amazon's Echo Dot, Google Home, and smartphones. It uses voice-assisted technology to incorporate the four critical components of language learning - listening, speaking, reading, and writing (LSRW). Tara mimics a human teacher by listening, responding to the learner's utterances, providing feedback and correcting grammatical mistakes, repeating lessons, and conversing with learners tirelessly. This helps learners learn at their own pace.
The policy of the Indian government is evident in yet another initiative that is used to identify the potential school dropout rate. In December 2015, the Andhra Pradesh Government signed a memorandum of understanding with Microsoft to use AI technology to address the issue of the rise in school dropout rate. By using Microsoft's Azure machine learning platform, an application was developed that helped the state education department in predicting school dropouts. The application processes complex data sets that include details about enrolment, student performance, gender, socio-economic demographics, school infrastructure, and teachers' skills to find predictive patterns. This will help the government to take the necessary steps to confide with SDG 4.
Additionally, the National Research Foundation (NRF) envisions the use of AI-powered solutions for the attainment of its goals of a multilingual as well as holistic education. Multilingualism among the school students will be promoted by the use of Natural Language Processing (NLP) capabilities for India's diverse languages. Additionally, AI will be used to track and record the life skills training of a child, to prepare a holistic report card.
Challenges to AI in Education
The core of AI lies in the stimulation of the thinking activities and behavior patterns of human beings according to the amount of data collected. However, the greatest challenge lies in the collection of ideal representative sample data that is not biased, for the training of the AI models. The simulated intelligence of machines is different from the natural intelligence of human beings. The intelligence of a machine is that the problem is formalized by man and that the computer can do the calculation. Then, Human intelligence is acquired through learning and practice and has initiative. However, the intelligence of the machine does not have the intelligence of the human mode of thinking.
AI has great limitations in applied education at present. Education involves inspiring each other with the acquired knowledge, however, ITS is far from reaching this level. Also, machines cannot communicate with students as human teachers can. Machines only judge students' input information and master students' learning situations. AI follows a formal teaching module, rather than adapting to the specific situation of each student. In the long run, it is not conducive to the personalized development of students.
Furthermore, it should be noted that not all subjects are suitable for AI, and the current AI education systems are not able to cover the learning of all subjects. There are obvious differences among various disciplines that lead to the natural differences in teaching and learning of different disciplines. Thus, the same AI models are not competent enough to capture, process, and impart diversified data.
Additionally, educators recognize that AI can automatically produce output that is inappropriate or wrong. They are wary that the associations or automation created by AI may amplify unwanted biases. They have noted new ways in which students may represent others' work as their own. They are well aware of teachable moments and pedagogical strategies that a human teacher can address but are undetected or misunderstood by AI models. They worry whether recommendations suggested by an algorithm would be fair. Educators' concerns are manifold.
In addition, the key intelligence of the ITS lies in its decision-making and reasoning mechanism, that is, the teaching strategy module makes flexible decisions through reasoning according to the specific situations of different students. This decision is based on the knowledge level and cognitive characteristics of the students provided by the student module and learning styles, and these cannot be fully formalized. At the same time, with the continuous updating of educational concepts and the continuous improvement of teaching models and teaching methods, the ability of the teaching strategy modules used by the system to evaluate and judge the learning process of students is limited.
The potential of the education market is huge, and the development potential of AI is also unpredictable. However, it is essential to ensure that people use the technology rationally to create value and avoid technical risks. Teachers must be trained in how to educate students on ethical principles, how to use AI tools appropriately, and how to mitigate the potential risk of AI to reduce human connection and belonging and increase loneliness. However, efforts are being made to not only change people’s study, work, and life but also bring new opportunities to the innovative development of future education.