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SmartData Collective > Analytics > How Data Analytics Reshape the Ed-Tech Industry
AnalyticsBig DataExclusive

How Data Analytics Reshape the Ed-Tech Industry

Data analytics has proven to be remarkably important in the world of education.

Amber Harris
Last updated: June 9, 2021 4:23 pm
Amber Harris
6 Min Read
data analytics in education
Shutterstock Photo License - By Rawpixel.com
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Just as the internet revolutionized consumer commerce, data analytics has dramatically transformed the world of online education. Apart from the business impact that data analytics has on ed-tech businesses, it has also empowered students to handle two critical aspects:  understanding their stronger or weaker points and guiding them in exploring new opportunities.

Contents
BYJU’sUdemyTestbookConclusion

Tony Sheehan, a senior data analyst at Gartner, observes that the pandemic boosted the process of educational institutions investing in and adopting ed-tech as most weren’t prepared to handle such a large-scale disruption in regular face-to-face teaching. The Higher Education Global CIO survey conducted in 2021 shows that 86% of global CIOs expect the demand for newer and improved digital products and services to continue.

For the success of ed-tech adoption, educational institutions shall have to evolve their capacity, capabilities, and culture rapidly to support the new methodology. The pivot to success lies in the use of data to form insights into institutions and their students. In this article, we analyze how the ed-tech majors are using data to power their missions.

BYJU’s

BYJU’s has separated its data into qualitative and quantitative. During product development, they analyze the qualitative metrics to incorporate information from research and student feedback into the process of product designing. It is followed by BYJU’s delving into quantitative metrics to study student satisfaction at a large scale after the product has been launched. This is one major example of how big data is pivotal to the world of education.

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Ranjit Radhakrishnan, the chief product officer at BYJU’s, says that they consider student feedback while designing the app. Therefore, it addresses the students’ needs, and it takes them on a fascinating journey of learning, supporting a personalized approach while making learning fun.

Personalized learning paths have been designed for the students with the right blend of technology and data. While solving the learning challenges of each student, the app offers very helpful and relevant recommendations.

BYJU’s personalization method stands on the pillar of the learning profile developed for each student. Certain variables are considered: subject affinity and proficiency, trending topics, knowledge profile, etc., while designing the recommendations for the students. It’s these recommendations that create a personalized learning path for every student.

Udemy

To make instructors aware of emerging topics, Udemy uses data analytics. The learners look for relevant content by analyzing the search data of learners in the site to locate trending topics and new areas of learning. Irwin Anand, MD, Udemy India, makes a special mention of the Marketplace Insight tool. This tool helps instructors design new courses after helping them locate growth areas and new topics.

Udemy has put in place sophisticated matching and recommendation algorithms to make sure that students find access to relevant content from a suitable instructor right when they need it. Udemy puts to use machine learning and data analytics in studying the data points of billions of learners to gauge preferences which have helped them offer engaging and in-demand courses that are relevant for their students.

Testbook

Testbook recommends competitive exams where the chances of success are the maximum using data analytics and machine learning based on the student’s competence in certain subjects. Plans are afoot to use this mechanism for employees as well, where a candidate’s job skills will be calibrated to match job requirements and raise performance levels.

A proprietary algorithm is designed using the data of a student’s attempts and data related to their preparation which is matched against the improvement data of the previous batch. The information gathered is used to prepare a personalized and adaptive learning path to help students achieve success. Changes will be made to the path and the content as the student moves along in the journey of their preparation.

The increasing adoption of ed-tech has probably crept into your home as well. You might have taken to online learning readily to deal with the pandemic. In such a scenario, you should be mindful of your security. We suggest that you use a Virtual Private Network (VPN) to safeguard your online activities. A VPN hides your IP from cybercriminals and online trackers by establishing an encrypted connection between the device and the server. It helps prevent IP-based tracking, which might also help you find courses for better prices.

Conclusion

The significance of online learning has risen rapidly after the outbreak of Covid-19. Big data has played a pivotal role to create algorithms helping design niche apps and websites, assess student performance, and measure their performance. The future of education is all set for a significant transformation, and we require an integrated learning strategy to unlock the potential of our institutions, ensuring success for students.

TAGGED:analytics educationbig data in educationdata analytics education
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