Throughout history, a constant drive for innovation to surpass what has already been discovered or achieved has remained the cornerstone of human intelligence. Each age has been defined by significant advancements that have propelled society forward. The evolution of technology, especially in the 21st century, has brought the human race to this point where it would not be exaggerated to call the times we live in the ‘Age of Artificial Intelligence and Data Sciences’.
With the advancements made in artificial intelligence (AI) and machine learning (ML) and the way it has revolutionised various industries and several aspects of our lives in recent years, no sector has remained aloof from its influence, including the field of education. Just as the invention of computers and the internet revolutionised how information is accessed and shared, the integration of AI and ML in education has the potential to transform education in numerous ways.

Taking knowledge gain beyond geographical boundaries:
Only recently has the education sector needed to catch up in adopting digitalisation and using data and AI to accelerate learning. However, the post-COVID period saw the need and rise of online and blended learning in education systems, as it gave us the liberty to overcome the limits of geographical boundaries or physical presence to gain quality education from faculty.

As the means of personalised learning:
Today’s times call for a personalised or competency-based learning approach. Every student has different skill sets and interests, so they should be mentored according to their abilities and pace of learning. But, simultaneously, it is also easier said than done because of the shortage of trained teachers/faculty members and the required human hours.
The biggest asset AI and ML bring to the table is personalisation. Here, various tools and algorithms of artificial intelligence and machine learning/data analytics can be employed to analyse students’ learning patterns and customise the curriculum or instruction practices according to their needs, abilities, past progress, and personal goals. This targeted approach can make the educational content more resourceful and effective. Teachers/educators can use the overall learning progress and larger inferences through a dashboard to modify their in-class pedagogy whenever needed.
Furthermore, the predictive model of data analytics and machine learning can also identify patterns of student engagement or attention, such as reduced participation in online discussions, inconsistent attendance, sporadic assignment submissions, or a sudden dip in grades etc. Informed by robust data-driven evidence, it can provide real-time feedback to comprehensively understand each student’s unique learning profile and learning outcomes.

Helping automate the administrative tasks:
Besides providing opportunities for students to manage the process of their learning and aid a personalised journey of their professional transformation, the AI & ML-based models can also benefit the educators/faculty members by saving their time spent on the arduous tasks of assignments grading, reports and metrics analysis, attendance tracking, schedules creation, and so on, by offering automation of these administrative tasks so that they can focus on creating high-quality teaching pedagogy, new instructional methods, learning materials for face-to-face sessions, and providing individual student support.
Besides these, institutions can incorporate AI-driven chatbots that are available 24/7 to provide quick answers to frequently asked questions related to admissions, course details, campus facilities, etc. These virtual assistants can also be proactive by sending reminders about assignment deadlines, fee submissions, or upcoming events. This can lead to greater efficiency and cost savings for educational institutions, enabling them to allocate resources more effectively.

Expanding interactive E-learning and immersive virtual laboratories:
While the significance of one-to-one and on-campus education cannot be replaced, the possibilities provided by AI, AR & VR technologies can effectively enhance students’ learning experiences who may not be able to pursue or afford in-person education/degrees/immersive field visits.
For example, imagine students at a rural school being able to understand geography/environmental studies subjects by seeing Amazon forests or glaciers with AR/VR and starting to think about solutions to some of the pressing climate change problems. Similarly, they can immerse and explore ancient civilisation sites in one of the history classes, all from the safety and comfort of their classroom, and become fascinated to gain more knowledge about them. The use of such technologies can enhance retention and comprehension considerably.
A good case in point is also the “Virtual Labs” project, an initiative of the Ministry of Education (MoE), Government of India, under the aegis of the National Mission on Education through Information and Communication Technology (NMEICT) through a consortium of twelve participating institutes. It is a commendable example of ICT-based education, in which more than 100 Virtual Labs with about 700+ web-enabled experiments have been designed for remote operation and simulation-based viewing by students, educators, and researchers of schools and Science and Engineering Colleges who do not have access to good lab facilities and instruments or want to collaborate. It can also encourage students to pursue STEM by arousing curiosity and enabling them to learn at their own pace.
In management education, interactive learning tools, virtual business simulations, cross-continental and interdisciplinary collaborative projects, business intelligence analytical software, and data analytics enable students to apply theoretical knowledge to real-world scenarios.

Challenges:
While the potential of AI and ML in education is vast, and it is the road ahead, we must also address concerns about data security, privacy, and ethical considerations. Forming robust protocols is the need of the hour to safeguard student data, preserve teacher-student interactions, and ensure transparency and fairness in AI algorithms. While the technology-enabled operations address the shortage of quality teachers/faculty, we also need effective teacher training to train educators to use AI-powered solutions to fill the gaps and provide quality education.
Additionally, we also need to ensure equitable access to AI-powered educational tools, necessary hardware, and internet connectivity and reduce the digital accessibility gap for students and institutions with limited financial resources to harness the potential of these technologies seamlessly.

Intrinsically linked new-age education:
Despite challenges, integrating AI, ML, Data Analytics, and AR/VR technologies in education can provide tremendous opportunities and significantly transform how students learn and educators teach. They can foster a holistic environment where traditional pedagogy intertwines seamlessly with cutting-edge technology to nurture today’s agile, adaptable minds and empower them to reach their full potential in today’s evolving and ever-expanding global landscape.

Views expressed by Prof Bharat Bhasker, Director, IIM, Ahmedabad.