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Technological intervention has revolutionised every aspect of our life in the past two decades. But it was right before the turn of the century that Pankaj Agarwal had moved from Jharkhand (then Bihar) to Delhi for his senior secondary education. Keeping consistent in his performance, he was not overwhelmed by the shift from a small-town school to a fancier urban school. In hindsight, he feels that it was the uniformity in pedagogies that had enabled a smooth academic transition.
Those were the days when all learning happened through teacher-student interactions in physical classrooms. It was the universal lack of technologically-aided learning and exposure that united students across the social spectrum—leaving academic success to be determined purely by one’s intellectual aptitude and the teachers’ contributions. This also formed the basis for upward mobility, as in the case of Agarwal who went on to graduate from IIT Kanpur, Seoul National University and Harvard Business School. With the dawn of the tech-dominated 21st century, however, a striking polarity has crept into the education system. The meagre infrastructural provisions of rural schools stand in sharp contrast to the state-of-the-art facilities offered by modern urban schools.
In 2019, after years of living and working in South Korea, Agarwal returned to a government school in Varanasi for the pilot testing of Class Saathi—a smart solution for India’s low-income schools. Describing his visit as “eye-opening”, he recalls how the AI-powered EdTech solution that he had brought seemed misplaced in the primitive school, in the absence of basic infrastructure such as desks. But while the dichotomy was discouraging, it was the students’ big dreams that gave him hope and motivation. His initial doubts were, thus, brushed away with his confidence in the sustainability of tech-led solutions.
It was his desire to give back to his roots in India and his team’s belief in the potential of education technology that led Pankaj Agarwal to create Class Saathi. Funded by Samsung and headquartered in Seoul, Class Saathi by TagHive is an AI-powered quiz platform that aims to impact the world of education with its low-cost technology.
Class Saathi (also marketed as Class Key in Korea) is a quiz-based EdTech solution for in-class and at-home learning. It offers clickers for classroom polling and an AI-powered smartphone app for use by students, teachers, parents, and administrators.
The classroom response system is a combination of a clicker for each student and the offline app for the teacher’s smartphone. It is optimised to complement the existing infrastructure of a modest classroom without the need for computers, projectors, internet or even electricity. The teacher can conduct topic-wise formative assessments to gauge the learning levels of each student. As the students input their quiz response through the Bluetooth clicker, a real-time report is displayed on the teacher’s mobile app. This feedback is then shared with the parents and administrators on their apps, too.
Learning continues for students at home with the AI-powered personalised learning app. All questions have been designed by a team of IIT students, based on the NCERT curriculum. The quiz-based Class Saathi app offers a self-assessment solution for Maths and Science for class 6–10 students. The question recommendations and difficulty levels on the app are fine-tuned to the child’s aptitude and performance.
Class Saathi, meaning ‘companion in the class’, has been customised for the Indian market. “We have chosen the colour of the app as green which represents the green chalkboard of the classroom,” informs Pankaj. Currently available in English and Hindi, its powerful algorithm is scalable across languages and subjects.
It is a multi-stakeholder solution for it connects all parties on a single platform, also increasing accountability. The in-class device and app are a versatile, teacher-centric solution in that it automates tasks such as attendance taking, question framing and report making, hence enhancing teachers’ productivity. Based on iterations and user feedback, Pankaj says, “We have perfected our solution in that it is very intuitive and seamless, and it quietly does its job.”
“Our hypothesis is that kids will learn better by solving questions,” says Pankaj. By making classrooms interactive and learning gamified, Class Saathi encourages the students to engage with the curriculum in ways that traditional pedagogies do not. The clickers give all students, including the shy ones, an equal opportunity to participate in-class quizzes. Participation is also incentivised by the discreet nature of the response, thereby mitigating the shame associated with giving the wrong answer in class.
The home learning app adds new dimensions to the meaning of self-study with its AI-enabled dynamism. “Our objective behind the AI model is that it should give you the same feel or same performance that a personal tutor gives you,” says Pankaj. Illustrating how it simulates the ways of a human teacher, he adds, “If a student gives a wrong answer to a question today, the app shows them the same question again after 3–4 days to see if they can now answer it correctly.” The comparative advantage, however, is that technology doesn’t judge and makes for a softer teacher. “You don’t have a teacher who scolds you for your mistakes—all the personality traits of a human teacher are gone and only the cognitive part is in action.”
The results have been very encouraging. During the pilot tests in government schools in Varanasi, U.P., and Bhopal, M.P., a 10 per cent increase in attendance and an 8 per cent increase in learning outcomes were reported in just one month. The Madhya Pradesh Education department has noted that Class Saathi serves as a data lens to help them see things not possible earlier. Subsequently, there is significant interest from the governments to deploy this technology in the schools, as soon as normalcy returns. The free Android app, which has benefitted over fifty thousand students in less than 6 months, is experiencing heightened interest during the Covid-19 lockdown.
Talking about the prediction capabilities of AI algorithms, Pankaj informs that his team is working on an engine—the “holy grail”—to solve the problems of poor learning outcomes and high dropout rates. This AI engine will use student analytics to predict exam scores and potential dropouts. Advance knowledge of these metrics will be a key driver for reform because it will enable remedial action to be taken well in time: “Doing damage control before damage is done,” in the founder’s words.
Sharing his vision for TagHive, the CEO says that he aims to create a scalable business model to take the company global without losing focus of the government-run schools in India. In addition to projects with the governments of Uttar Pradesh and Madhya Pradesh, the company’s patented technology is being used in over 400 schools in Korea and India. The paying clients will give the leverage to continue to offer it as an affordable technology for the underprivileged children in aided schools.
Also, in the wake of the pandemic, educators are turning to alternate online sources of teaching. And while there has been an unparalleled adoption of virtual methods of teaching and lesson delivery, there are not any reliable digital tools for assessments and performance evaluation. This has opened the opportunity for assessment-based apps like Class Saathi to encourage more schools to partner with them. Upon receiving regular and timely data from student’s apps, the schools will be able to make data-driven decisions even as face-to-face teaching stands dismissed during the lockdown.
We have made huge progress with education technology, but its benefits have only been reaped by select sections of the society. While the digital divide has amplified disparities, it is the affordable, accessible, adaptable, AI-based solutions that have shown the promise to bridge the glaring gaps. Therefore, low-cost and low-maintenance EdTech solutions such as Class Saathi have a big role to play in transforming the education scenario, especially in rural India. The reliable data thus generated will lead corrective action at the school level as well as the policy level.