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What’s Next for Education in 2018?

According to a recent report by Google, KPMG, online education in India will see approximately 8x growth in the next five years, says a recent report by Google, KPMG.

By Reetika Bose Feature Writer

The rapid increase in internet connectivity has been an important catalyst for the growth of e-learning. A proliferation of edtech platforms in the Indian landscape is slowly eliminating barriers in the access to quality education. With 400 million K-12 students, upcoming startups can expect to effectively mobilise their content by creating micro-learning facilities for self-learning, while, simultaneously, engendering employment opportunities. According to a recent report by Google, KPMG, online education in India will see approximately 8x growth in the next five years, says a recent report by Google, KPMG. This will have a significant impact on the edtech market that has a potential to touch $1.96 billion by 2021.

Virtual reality and gamification

Do you know that passive teaching methods lead to a concept retention rate of less than 30 percent? On the other hand, participatory techniques generate retention rates of up to 90 percent. Where our traditional education system fails is that we remain largely focussed on outworn practices that keep student engagement passive, and retention at the bare minimum.

The aforementioned issue is being actively addressed and tackled by technology. Augmented reality, virtual reality, and gamification are giving students an immersive, first-hand experience through graphical simulation, and, thereby, extending the concept of experiential learning. This has the effect of boosting both engagement and retention, while the use of animation ensures that students understand complicated theories easily. Such technologies are more likely to be a game-changer in time, with visible developments taking place from 2018.

Data analytics

Big data and data analytics are phenomenal in that they enable educators with new teaching methodologies. Existing data points are being extracted to gain deeper insights that affect the overall academic growth of a student. Despite being fragmented in many cases, data scientists were able to derive critical observations through these records. They included an optimal book-to-pupil ratio – drawing on the optimal pupil-to-teacher ratio.

The study also hinted towards lower engagement rate of girls between 11 and 14 years. Further, the analysis was quick to find that the dropout rate amongst this demographic gets reduced with the introduction of separate toilets for them.

These are some of the interesting takeaways from the collaborative attempt, and were generated through leveraged technology in spite of the complex and disjointed data sets available. With increasing digitisation and availability of more enriched data points to process, these insights will lead to more solutions to longstanding problems in the sector.

Cloud-based technology in education

Improved IT capabilities and enterprise infrastructure at schools are needed to create a successful digital learning experience. While the technology exists in some forms, the real challenge comes in terms of scalability. The biggest advantage of cloud technologies is that they create a centralised repository of knowledge for students and teachers to access. This is taking the student-teacher collaboration beyond traditional classroom interaction.

Cloud-based technology in education has become such a phenomenon since it ensures sustained academic learning irrespective of the student’s geographical positioning. Moreover, it ensures that the desired data is centrally available for processing and deriving deeper insights for a more effective learning experience. Cloud-based technology also enables educators to boost their reach without making any significant infrastructural spends. This, in turn, benefits end-users by reducing the cost of services, while simultaneously adding value to their education.

Machine learning and artificial intelligence

People might ask how artificial intelligence actually affects a student’s learning capabilities and boosts human intelligence. Well, AI is turning pedagogical training right on its head. AI-driven algorithms create behavioural models by studying individual data sets. Based on these models, the algorithms develop a deeper understanding of a student’s strengths and weaknesses and devise a unique personalised learning curve.

Machine learning, a constituent technology of AI, enables the system to learn individual actions and skills without explicitly being programmed. The system automatically establishes the relationship of different learning methodologies with respect to different behavioural models, progress reports, and annual results. They, moreover, create personalised training paths that exact the needs of each and every student. The student ultimately benefits by learning at an optimal speed – delivering the best results.

The increasing influence of technology in education is, thus, offering us a glimpse into a gradually evolving realm of unconstrained learning. Today, if we are able to deliver despite an outmoded education system, imagine what wonders the next generation will accomplish, once it has been trained with advanced pedagogical methods. And since these systems are witnessing increased adoption with every passing year, we won’t have to wait much longer to see the results.

 

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