Although Big Data seems a very complex term, applied to the learning environment is nothing more than the collection of data obtained from users that interact in some way with the learning content.
What is big data? It is a set of technologies and practices that make it possible to store, process and analyze the huge amounts of data generated in the world. We talk about 1,700 billion bytes per minute.
This data is created automatically while students participate in training. The Big Data includes everything from the progress of the user and their qualifications, to the use made of the forums or social networks. The objective of collecting this data is to analyze it so that developers optimize their content and improve their teaching materials. The more data produced, the easier it is to adjust to the needs of the users and thus guarantee them the best possible experience. That is, to perform a truly personalized training, Big Data is indispensable.
In order for Big Data to work optimally and without much effort on the part of companies, it is necessary to apply Machine Learning. Machine Learning consists of creating systems that learn automatically so that the management and analysis of the data collected would be done instantly. For example, very simple use of Big Data in education is for a training platform to suggest courses based on other courses you have previously taken.
Among other things, Big Data allows identifying patterns of behavior through which it is known which learning styles work best in each target. In addition, it also opens the possibility of adapting the level of the courses to the previous skills and knowledge of each student. According to Big data training in Bangalore, some of the most important advantages that Big Data can bring to Learning:
- It allows content creators to understand how students use different resources and what the learning needs that most appeals to them are. For example, if users tend to see more theoretical content or on the contrary, they prefer the practical ones, if they see the complementary materials, download the texts, etc.
- Detects if necessary improvements to existing content. This can be discovered if, for example, most users remain “stuck” for a long time in a particular module or if they leave the course when they have a certain percentage of progress.
- It provides information on what content, courses or materials are most visited, as well as what they share among students. That is, analyze which aspects of the training are most successful among students
- It allows data to be collected more or less immediately (depending on each system), thus making it easier to analyze and evaluate the results without having to wait long periods of time.
- Analyzing the progress of students in their learning, it is possible to predict in which activities they will stand out in future courses and which will cost them more.
Of course, there is still a long way to go to successfully implement Big Data in education. For this, it is necessary to invest in exploring new possibilities and the involvement of computer developers that automate and improve the analysis and collection processes. But what seems clear is that it will have a great impact on the future of education, especially when it comes to personalized training.