Digital learning was once an optional channel for education in the Pre-Covid era. Not anymore! Gartner’s 2021 Global CIO survey reinforces this fact. According to it, almost 86% of the CIOs across industries predict sustained demand for new digital products and services. As per Grandview Research, the global EdTech market is reported to exceed $377 billion by 2028.
The role of adopting Data Analytics in the growth, User Experience, and sustenance of Ed-Tech companies is paramount. Right from minimizing student dropouts, improving enrolments, customizing course syllabus to securely hosting online exams, the list is ever-growing.
Applications of Data Analytics in EdTech
Let’s look at some primary areas where leveraging Data Analytics can act as a game-changer for EdTech players.
Predictive Modelling To Improve Student Learning Outcomes
The probability of how well a student will perform can be estimated using parameters like demographics, online interactions, test results, etc. The outcome of these studies is then used to create virtual student personas that enable data-driven insights on future students. When a newly enrolled student showcases similar behavior, the predictive model developed can be employed to customize the curriculum that aids in giving maximum learning outcomes for the new entrant.
Social Learning Analytics
The patterns generated from the online activity and interactions exhibited by students within the learning platform are a gold mine for analytics. For instance, what keywords they search for more in the course and their responses in the discussion forums can be studied. This data will enable you to provide learning content recommendations at the right time for a more enriching educational journey.
Aptitude Based Adaptive Systems
It is imperative to understand that each student has a learning speed. A “One Size Fits All” curriculum can do no good towards students’ progress in most cases. Learning systems need to have a dynamically adapting trait that adjusts the content complexity based on each student’s aptitude.
The curriculum needs to change as per the instructor’s instructions and automated interventions. This is analogous to the recommendation systems based on Machine Learning used in OTT and E-Commerce platforms.
Gauging Student Engagement For Performance Tracking
Card swipes and library activity in Universities are no longer effective methods to track students’ academic engagement. Moving forward, Data Analytics via gathering, aggregating, and assessing data can generate actionable insights to gauge students’ performance. This exercise provides EdTech companies and instructors with details on students’ areas of improvement. That, in turn, can help academically weaker students to prevent falling behind academic benchmarks.
The Road Ahead For EdTech
Since the onset of the pandemic, the role and relevance of EdTech and E-Learning have grown drastically. Data is the oil that drives this industry across the value chain, from the marketing of prospective students to their course completion. With effective leveraging of Data Analytics tools and techniques, EdTech players can improve the learning outcomes and business trajectory like never before!
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