AI and School and Higher Education:A Unique Opportunity

Rajeev Sangal

Abstract

AI has arrived on the world scene with a bang! It needs to be handled carefully so that it can have a positive impact on education. Our education should actively engage with AI not just in its use but also in its creation - for diverse applications suited to India’s needs. In this sense, education system can have a major impact on the development of AI systems in India.

AI has three major elements: data, machine learning, and applications. Each of these three need to be engaged with. Students can create local data (through community sourcing), development of algorithms and applications.

We need to have activity in four major areas: (1) personalized education, (2) real-life experiential education, (3) technology education, and (4) humane education. This would make our education system less bookish and more real-life, which can also rejuvenate student interest in studies. Our teachers will have to become mentors to students, rather than remaining only as blackboard teachers. If we are able to do this, AI would have helped our education system to transform and also connect with economy and livelihoods.

1. Background

As technologies based on Artificial Intelligence (AI) have suddenly burst on the scene, they have raised concerns as well as possibilities about their impact on education. Concerns are, if the students start using AI technologies to submit their home assignments, when would they learn the skills. For example, if ChatGPT, Gemini or Claude are used to produce answers to questions, to write summaries etc., the students would never develop the skills of writing - building an argument, drawing conclusions, etc. affecting the development of critical thinking itself. Banning the use of these technologies is not workable, and many argue, not even desirable. Use of handheld devices and social networking has already reduced real friendships and caused isolation among people. With AI entering into social networking, the effects might be even more damaging. Mitigation strategies need to be adopted in education to handle all this.

This concept note addresses some of the mitigation strategies, but focuses more on the new vistas that open up in education because of AI. It outlines how education can take advantage of the new possibilities to make learning more effective and more linked to real-life, including with livelihoods. This applies to both K-12 school education as well as higher education over a continuous spectrum.

2. Approach

AI can be used to personalize the learning of the student. It can hopefully provide specific and pointed answers to the queries of the student. However, it would remain a tool and not replace the teacher, despite the over-enthusiastic claims.

While preparing students for AI, it is important to link education with real life. AI opens up new possibilities. Development of AI technologies primarily relies on (a) data and (b) machine learning, leading to (c) applications. One would like to include all three in education, with the applications coming from different domains or subject areas.

Data which can be used in AI in the Indian context needs to be collected in myriads of areas. Today, the data is largely collected and owned by a small number of multi-national corporations (MNCs), however, it is in a few narrow domains, mostly related to user’s personal preferences. Education, on the other hand, has a vast domain of activity through which public data can be collected and curated at a large scale. However, unlike the MNCs, the data would not be collected passively on the user, but actively by the user on reality around him/her.

Education must teach how to collect data, how to do machine learning, and how useful applications are built. The data collection process itself aids education, as it connects learners to real life, and provides a new opportunity. When the data is analyzed based on school subjects, it leads to a deeper understanding. The analysis can itself be done in creative ways. Thus, analysis of data related to their school subjects provides another important learning opportunity in school education. This would also prepare students for livelihoods in new areas.

The increasing digital addiction to mobile devices and consequent isolation of students from their friends, needs to be addressed urgently. With AI technology coming into our life through the handheld devices, addiction will become worse. This needs to be addressed through humane education, where the teacher becomes a mentor to students, and encourages the formation of positive peer groups.

Let us look at all these in more detail.

3. Changes to Education

School and higher education can be impacted positively, if AI is integrated creatively. Some of the elements in education would be new, whereas some others are old that have now become possible. AI has the potential to impact education in four different dimensions:

1. Personalized education

2. Experiential education

3. Technology education

4. Humane education

They are described below.

3.1 Personalized Education

There is a good possibility that AI will be able to help students with personalized help. The parts they did not understand, they can ask questions and get personalized answers. With a large amount of knowledge available over the net, AI will be able to retrieve and present it in answer to prompts or questions that the student might give. These skills will, of course, need to be learnt.

AI is also expected to help students in their learning style, so that the learning will be effective and easier. Such benefits, though, have yet to prove themselves. However, it will not remove the need of a human teacher – who incidentally would need to expand his/her role with students.

There are also many concerns on the dangers to learning because of the AI technology. It is feared that students will become lazy, cheat in home assignments and exams, thus affecting learning adversely. Digital addiction might become worse with mindless browsing, driven further by AI algorithms. Some of the strategies outlined below, address these concerns by doing some entirely new things in education such as relating education with real life, addressing teacher-student relationship, etc.

3.2 Real-Life Experiential Education

AI provides a new learning opportunity through real-life experiments and experience. Schools students can collect local data appropriate to their age and class. The data may pertain to three broad areas (Some of the ideas described here are taken from Socionity project executed by IIIT Hyderabad in 2012-14):

1. Geographical and natural,

2. Cultural and social, and

3. Livelihood related.

Geographical and Natural: Data may be collected on village ponds, quality of water, common grazing areas, forests, wild life in the forests including birds, monkeys, civets, etc. documenting the state of city roads, and other infra-structure. Such data could connect with teaching of science (geometry, biology, chemistry, geography, etc.) and social studies (history, sociology, economics, local governance, etc.). Thus, AI will get connected with the teaching of various subjects, provided they change their learning methods to be based more on life.

As an example, consider an AI system which can predict the change in ground water levels next month for a village. It would require meteorological data, conditions of local ponds and lakes, local usage patterns, crops planted currently and their water needs, etc. Such data collection would be a part of geography and biology, and would relate with those subjects. Predictions based on this data for the local area would be superior to predictions made by a large regional model, because it simply lacks local data.

Cultural and Social: Data may be collected related to sociological or economic aspects of the urban ward or village and surrounding area. These would be done as part of projects which would naturally connect with the subject of social science, history, etc. Data could also be collected on history of the city, stories of grandmother, establishment of major buildings or landmarks, etc. Again the data collections would be a part of projects which connect with the subjects of language, history, literature and the art of story telling, precision in documenting, etc.

As another example, consider the creation of digital content in Indian languages. Such content can be made by translating existing content from other languages into a concerned language, or by writing originally. The content might be objective and informational, or subjective and scholarly. These would give a big push to increase in digital content in Indian languages. If done by communities or schools, I call it community-sourcing rather than crowd-sourcing. Such content creation effort would naturally connect with the subject of the concerned language; it would be a part of the language teaching supervised by language teachers. Contests may also be organized at the district, state, or national level to encourage students to take up this work.

Livelihood Related: Livelihood related aspects would mean connecting with local people who possess skills such as plumbing, electric repair, pump upkeep, etc. besides, of course, farming, handicrafts, and cottage industry. It could also develop entrepreneurship related to arts and crafts, processing of agro raw materials, energy and water utilization, and beyond.

The collection of such data and doing its analysis can be a great learning experience, and can link all school subjects with real-life. Such data and its analysis would become a treasure trove for research carried out by researchers in higher education.

Of course, suitable checks would have to be built, so that the quality of data is good. Many mechanisms can be put in place for achieving it through project checks, supervision by teachers, evaluation of data, and awards to students who do a great job. The quality of data would slowly improve.

Moreover, the data so collected will become the property owned by the local village or an urban ward. So, there would be a possibility of monetizing on the data, which will provide income to the school and its students who have collected the data. New monetization models can be developed.

3.3 Technology Education

Under machine learning (ML), students would learn about different algorithms and packages, and how to apply them to data.

In school education, particularly in the higher classes, students would learn to run pre-prepared packages on new data, and see what AI can do using the data that they have seen, even collected.

In higher education, the emphasis would shift to development of algorithms for ML, applying them to different domains, evaluating the ML algorithms, etc. Often it would mean analysing the data and using the results of such analysis to improve ML. After all, for ML to be effective with the smaller quantity of data, many innovative tasks would need to be done. It would raise research questions in AI as well, for example, how ML can take place based on distributed data, or utilization of domain knowledge along with data, etc.

There is already a problem in ML that it uses a high amount of energy and compute power. This challenge is likely to be solved by using knowledge - analysis of data based on a theory, and incorporating that analysis in ML. It would also open up possibilities of creating ML algorithms which use knowledge, and not just data.

3.4 Humane Education

Finally, most importantly, the advent of digital technology has brought many ill-effects among our students. Virtual connections with people have led to digital contacts which are not relationships. This in turn has caused isolation of the individual, resulting in depression among young people. With the coming of AI technology on social media on digital devices, it can become worse. AI technology has greater power than before to mesmerize the user, leading to greater mental health problems.

The question is how to counter the above ill effects? How can a student use these technologies for learning, and at the same time build relationships with fellow students and others. This is where the human teacher has to become a friend of the student so that the student is willing to share his/her difficulties, whether academic or otherwise. Group discussions around Universal Human Values should be incorporated in school education. These address the pressures felt by the student related to show-off, comparision with others, consumerism, money, one-upmanship, and the resulting negative peer pressure (Gaur et al., 2010). It instills self-esteem and self-confidence, how to control anger, etc. Learning how to give rather than only take, development of relationships are a part of it.

The teacher will have to be trained to deal with all this which is beyond the specific subject that he/she might be teaching, and is able to guide the student. In other words, the teacher has to become a friend, philosopher and guide, where he/she is more of a mentor and a guru, rather than being limited to only a (blackboard or powerpoint) subject teacher.

4. Conclusions

AI comes to education with dangers related to digital addiction, further isolation of students from others, and cheating in home assignments; but it also has a silver lining. It can open up our education from bookish knowledge to real-life learning, personalized help to students, and combining technology with Indian local needs. The teachers have to rise up to become mentors to students. An entire rejig of education is possible, both at school level as well as in higher education, if AI is used as an opportunity. Massive training programs for preparing teachers would be necessary so that they can (1) teach their subject connected with real-life, as well as (2) mentor students with issues of life faced by them, based on Human Values.

References

1. Gaur, RR, Rajeev Sangal, and GP Bagaria, A Foundation Course in Human Values and Professional Ethics, Excel Books, New Delhi, 2010.

2. Dharampal, “Essays on Tradition, Recovery, and Freedom", Dharampal Collected Writings, Vol. V, Other India Press, Goa, and SIDH, 2016 (first published 2007).

3. Sangal, Rajeev, Pradeep Ramancharla, NC Karmaka, Mentors’ Manual for Universal Human Values 1 (for Student Induction Program), AICTE, New Delhi, 2019.

4. Sangal, Rajeev, “Between Humans and Machines: Explainable Artificial Intelligence", The Hindu, 2 June 2019a, OpEd Page. (https://www.thehindu.com/opinion/ open-page/between-humans-and-machines/article27399826.ece)

5. Sangal, Rajeev, Laws of Robotics and Human Consciousness, Journal Dialog on Knowledge in Society, PPST, India, October 2023. (https://www.ppstindia.in/post/laws-of-robotics-and-human-consciousness)

6. AI and Human Consciousness & Society, Rajeev Sangal, Institute Lecture, IIT Delhi, 16 Oct 2024 (https://www.youtube.com/watch?v=YVqxIB8prpg (from: 00:23:30))

7. “AI and Education: Challenges and Opportunities" lecture by Prof Rajeev Sangal, Malaviya Mulya Anusheelan Kendra, BHU, Varanasi, 4th Apr2026. (https://www.youtube.com/watch?v=pz2a6kMEP0U)

Prof. Rajeev Sangal is the former Director of IIT(BHU) Varanasi (2013-18) and founding Director of IIIT Hyderabad (2002-13). He is a Fellow of Indian National Academy of Engineering and of Computer Society of India. His research spans Natural Language Processing, Machine Translation, and Artificial Intelligence over 40+ years, starting from faculty position at IIT Kanpur (1982-99). He conceptualized Mission Bhashini, the language translation mission of Meity, Govt. of India, and oversaw its implementation as the founding Chairman of its Executive Committe (2021-26). Prof. Sangal designed and implemented the Universal Human Values course as a regular part of academic curricula in engineering education. He designed the Student Induction Program in technical education, and was the founding Chairman, National Coordination Committee, Student Induction Program, AICTE (2017-19). Prof. Sangal can be reached at sangal@iiit.ac.in

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