Big Data in eLearning – Methods of Up-to-Date Education
Remote education is rapidly progressing. In such conditions, the main problem is the timely provision of students with high-quality educational material. But yet another challenge is to identify new, often hidden, relationships between Big Data in eLearning and new knowledge (data mining) that can be used to improve the educational process.
These tasks cannot be solved without analyzing the huge flows of information from the participants in the educational process. A large number of different types of data is difficult to process without modern learning analytics tools.
General Concept of Big Data eLearning
Against the background of the rapid tech development, the education system cannot remain unchanged. And this system generates immense amounts of data. That data can help you capture a complete picture of the performance of each student, their difficulties and preferences. Specifically, the e-learning environment helps acquire the following types of data:
- demographic data;
- Information about the source of obtaining information about the training program;
- Information about the devices used to enter the course;
- Types of browsers and OS with which the learning system interacts;
- Progress, ratings and reviews.
With big data, you can observe students’ work scrupulously and track:
- Parts of the program that they spend more time on or find difficult;
- Topics and sections that they often visit and recommend to friends;
- Preferred styles and training times.
This data helps to understand the real patterns of student behavior much more accurately. In the context of providing e-learning programs and improving their management, this is of great importance.
Benefits of Big Data
The use of technology makes it possible to improve the quality of education, predict user experience scenarios and take action. Predictive analytics gives an objective picture, helps to understand what may happen in the future, and timely optimize the learning process. Knowing the behavioral habits and preferences of students, it is easier to manage the process. You are enabled to identify underperformers and react faster to poor performance.
Other advantages of the technology also include:
- Improved algorithm for identifying and evaluating problems: having a template makes it easier to learn and take action. You have the context and the data you need to pinpoint exactly where, when, and how things are changing. This will help you quickly identify areas of the course that need to be adjusted.
- An easy way to get specific information: you get access to confidential data that will help you establish close contact with the student and “lead” them to the end of the training.
- Flexible user settings: allow you to quickly determine which courses or sections are most popular with students.
- Rapid analysis: based on the identified user patterns, you can develop new courses, learning strategies, and methods for delivering learning content that meets student expectations. You will understand how they adapt to the curriculum and assimilate the material.
- Time savings: big data analysis allows you to quickly evaluate the performance of students ─ your future or current employees.
With this information, training programs can be adjusted to make them more attractive and effective. It will be easier for you to predict academic performance before the start of training. You can start parsing data immediately after completing the course, identify trends, and draw conclusions about the prospects for further initiatives.
Future of Big Data
Experts believe that by 2025 the global volume of big data will grow to 175 zettabytes. This is 26 times more than in 2013! Thanks to technology, there is a unique opportunity to improve corporate training programs and boost the quality of employee education. Companies get the tools to deliver personalized and adaptive training programs. They are changing the approach to learning and development, challenging traditional planning principles.
The use of this technology by HR professionals has become a widespread practice, and it will become the norm for companies in the short term. The most important thing in this process is proactively identifying the training needs of specific employees or teams, as well as providing guidance on when and how they should complete a new training course.
For developers of tutorials and courses, the information that they can get through analytics is important. According to forecasts, by 2026, the global e-learning market will exceed $330 billion in total shares, and the global learning analytics market will grow to $57 billion by 2030 at an average annual growth rate of 15%!
With personalization, learning becomes more personal. We will be able to select our own program for each, give a separate homework, and also provide a check on the assimilation of the content. The method of working in groups will also be different: at Harvard, already now, in one of the courses, students with different answers to the same task are paired up so that they can come to a single solution, defending their point of view in the process of finding the right answer. Students will receive detailed guidance on various topics and have an expanded information space.
The system will select the best places for future students, and by the end of the course, everyone will have a digital portfolio that will help graduates-specialists navigate the labor market, and employers – in the selection of specialists.
The e-learning sector has come to the point where there is no difference between remote and traditional learning. Infrastructure and software solutions have been created to effectively use big data and the latest visualization methods. All this simplifies data processing decision making, financial planning and performance monitoring. Big data allows you to save the learning experience, gives a picture of the learning of each student.
For innovation to become a “natural” part of education, recognized methodologies must be used. If this task seems difficult for you to handle on your own – contact us to hire big data developers with in-depth expertise and experience. We will help you create a productive LMS based on the concept of big data and your own authoring tools of choice.