“The pandemic accelerated investment and adoption of ed-tech in education. Few traditional higher education institutions were prepared for such disruption, resulting in evolution of technology-based teaching models more frequently aligned to migration of face to face teaching than ‘digital-first’ design,” said Tony Sheehan, Senior Director Analyst, Gartner.
Gartner’s higher education global CIO survey for 2021 suggests 86% of global CIOs expect continued demand for new digital products and services this year, but institutional capacity, culture and capabilities must all evolve rapidly to support ed-tech adoption. Leveraging data to provide insights on students and institutions is pivotal to success.
Let’s see how Indian Ed-Tech majors have been using the power of data
Udemy
Udemy uses data analytics to inform instructors of emerging topics where learners may be looking for more content by analyzing learner search data across the site to find trending topics and new areas where learners are looking for additional courses.
“Through our Marketplace Insights tool, instructors can find growth areas and topics and develop new courses to meet learners’ demand. Marketplace Insights has proven to be a very popular and powerful tool for our instructors,” said Irwin Anand, MD, Udemy India.
To ensure learners get the right content from the right instructor at the right moment, the company has also employed sophisticated matching and recommendation algorithms as well as ratings and reviews. Udemy uses machine learning and data science to analyse billions of learner data points around preferences and effectiveness, to serve the largest selection of in-demand, fresh, and engaging courses to individuals and businesses
Testbook
The platform uses ML and data analytics to help recommend the most relevant competitive exams to any student where given his current level of subject understanding, the chances of selection are highest. The company is now working to expand this to skills and private Job opportunities where it will map its calibrated students to the right opportunities based on the requirement of the job and the current knowledge level of the student.
“We are building a proprietary algorithm to use student’s attempt data along with preparation and improvement data of the previous batch of students to help build a completely personalized and adaptive learning path for our students to help them clear their exams. The path and the content in itself will also keep adapting as the student progresses in his/her preparation journey.,” said Ayush Varshney – CTO, Testbook.
“We are providing personalization in the exams, tests, courses we recommend already. But we are also working to create a completely adaptive learning curriculum for the student based on the large amount of data we already have,” he added.
BYJU’s
BYJU’s keeps a track of data in two parts, namely – quantitative and qualitative data. It studies qualitative metrics during the product development stages when it incorporates its research and student feedback into the product design process. The company then moves on to study quantitative metrics once the product is rolled out. This is how it tracks students’ satisfaction with its product offerings at a much larger scale.
“We incorporate this feedback to enable the BYJU’S learning app to act as an engaging teacher, a personal coach and an encouraging friend. The app hence understands the student thoroughly and takes them on the fascinating process of learning in a truly fun and personalized manner,” said Ranjit Radhakrishnan, Chief Product Officer, BYJU’S.
“The right blend of technology and data in our systems enables us to create personalised learning paths for our students, offer highly relevant recommendations and predict & solve their ‘real’ learning challenges. The backbone of BYJU’S’ personalization engine is the rich learning profile that is built for every student. Our mechanism to offer recommendations is also highly evolved and takes into account several signals such as subject affinity, chapter recency, knowledge profile, proficiency, topic trending in the region, and so on. Based on these variables, the app’s recommendation mechanism then creates a tailor-made ‘learn journey’ for every single student, ensuring a seamless learning experience,” he added.
Ed-tech has democratized education to a great extent. Owing to the wave of COVID-19, the significance of online learning and ed-tech has gained a rapid stride. The future of education is already transforming, forming more fluid roles that will positively impact learning.
Data has definitely played the biggest role in this sphere; from online algorithms that are used to create niche websites and applications, to assessment, to measuring results, everything has been influenced by big data. The ed-tech sector continues to innovate rapidly, but an integrated learning data strategy will be pivotal to unlocking institutional efficiency, targeting appropriate change, and delivering student success.
