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The far-reaching impact of AI in education

With the rise of AI, the Indian learning and e-learning landscape have seen considerable change. Here’s how the power of AI is being capitalised in the field of education.

The far-reaching impact of AI in education

Tuesday March 31, 2020 , 5 min Read

Artificial intelligence (AI) is one of the major technological innovations in recent times, set to revolutionise industries across verticals. In simple terms, AI is the capacity of a computer/machine to collect, anticipate, analyse information, recognise patterns and, consequently, perform actions as opposed to natural human intelligence.


AI has permeated industries throughout the years, aiding and executing taxing responsibilities such as customer service (voice assistant services), in automobiles, robotics, etc. Its presence has likewise penetrated the education sector, which can be further corroborated by the surge in edtech startups in India.


ai in education

With the rise of AI, the Indian learning and e-learning landscape have seen considerable change. Here’s how the power of AI is being capitalised in the field of education:

Modernisation of education

AI aids the process of channeling focus on core concepts of all subjects, while embedding interdisciplinary concepts on the same platform. AI has allowed education to be personalised for students to fit their unique needs. It aids the process of designing and developing technology, which facilitates quick resolution of queries with independent support to students as opposed to a teacher teaching a class of 20+ students.

Meeting unique needs

AI also brings value on the table by procuring information on the unique requirements on students, courses, and their syllabi to develop a holistic and robust learning trajectory. Leading and competing players in the e-learning market have harnessed AI’s ability to recognise patterns, and congregate data by mapping online movement/footprints from numerous sources to decipher the finest techniques of learning for students in general and individuals in particular. It has filled the gaps, which a normal classroom lacks, through clever coding, algorithms, and big data, enabling students to choose subjects, concepts that suit them best in accordance with where their interests lie. In this manner, content isn’t imposed on students unlike in schools.


Ultimately, the student excels in their academic goals and paves way for a brighter future. The same ability throws statistics on how quickly or slowly an individual can digest information besides preferences, interests, and degree of involvement to further help e-learning platforms tailor their offerings for them. AI has ensured a personalised learning journey while making education more relevant to students, parents, and teachers.

Feedback that supports growth

AI lends support by monitoring and mapping the learning graph of a student or an individual. Once the data has been acquired on the individual, it’s scrutinised using advanced analytics for insight generation (strengths and weaknesses) to develop tailored plans for an individual to ensure that the person gets the most out of his/her course online.

Learning can be fun

Artificial intelligence can turn learning into an enjoyable experience. One of the newest ways teachers can engage students online or in a classroom is by using simulation. Leading gaming companies have been using simulation to engage their customers for decades. Many medical and flying institutes have started using computer-powered simulations to put candidates/students in a real-life situation wherein students can react and interact, based on which one can be judged.




Breaking geographical barriers

Students can move beyond the geographies of their classroom/room without actually stepping out. AI makes communication with peers on a global scale easier through the Internet. With the help of third-party apps, getting insights on a subject matter of concern to the student is just a click away.

This ability can be further used to enable partnerships on a global scale, similar to an electronic student exchange program, where students or individuals could come together and provide answers to solutions or create a collective craft.

Beyond learning

We have adopted AI in all forms, from chatbots to adtech in our lives, making our life simple and easier. We have embraced a greater scientific approach, which enhances strategy, targeting, insight, creativity, knowledge, and experience. Basic and redundant processes are made easy, like the creation of profiles, which require consolidating information of students, which also, at times requires constant updating. Another understated potential is regular updates to the online alumni community. To that end, a feed framework can be created on a subscription basis, to update students with developments in the field and enable them to take calculated steps to enhance their career curve.

Segmentation framework

Another facet of how AI is used in the edtech industry is in the segmentation framework model. Under this, AI aids the study of different data sources that are available to understand their structures for profiling. The data, which is profiled, addresses different objectives, for instance:


  • Assessment: Whenever an individual poses a question, with the help of advanced analytics, AI can determine the level of understanding of the student/individual. It helps in assessing whether the analytical intelligence of the student/individual is on par with the level of the concept and whether they have a proper understanding of the subject.
  • Cross-selling of content: AI identifies the learning patterns of a student or an individual basis, which it provides them with supplementary learning content to ensure that the individual grasps the concept in its entirety.
  • Dropout: When a student or an individual chooses to opt out of a course or arbitrarily drops out, AI is able to determine the reason by determining how interested the individual was in the subject.


With the baseline data and touch points, educators can then proceed to develop predictive model layers over the data to draw and retrieve inferences, which will form the foundation of all future engagements.


(Edited by Evelyn Ratnakumar)

(Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the views of YourStory.)