Analytical skills are in high demand today. Every professional has to do some analysis at a certain point of career growth. Globalization and digitalization turn personal lives and work into massive amounts of data.
The world generates information faster than ever. To swim in this torrent of data, people need to embrace everything it offers and use it for their good. To do so, we need collection, systematization, analysis, and predictions based on this analysis. Here the big-data method takes the reins.
What Is Big Data?
The definition of big data (BD) usually means enormous amounts of information. Its primary quality, besides the scale, is the fact that it is unsystematic. Such data usually resides in some digital medium. Yet, big data is too extensive to use traditional means of structuring and analytics.
Each time a student decides to buy concert tickets online or pay for essay, they leave a digital footprint. These actions and the user information become a part of the worldwide dataset. Search engines study their users to teach AI how to make better predictions. This digital footprint will later help show more relevant suggestions.
So, BD also means technologies for the search and processing of unstructured information. It helps get practical knowledge in all areas of human activity, including education.
Do not mistake data analysis (which is every instance of analysis) for working with BD. The latter is a much more complex structure.
Until 2011, the BD technologies were used just for scientific analysis and had no practical application. Yet, the data avalanche grew exponentially, and the problem of immense amounts of unstructured and heterogeneous information became urgent.
How Does This Technology Work?
To put it simply, imagine a supermarket where all goods are placed in an unusual order.
For example, you find bread next to the fruit stand, and tomato paste – on the rack with detergents, avocados, and magazines. Big data is the marketing manager who puts everything in its place and helps find the food you have been looking for. Besides, it tells the price and expiration date and also who buys such products and why. The algorithms could suggest some dishes that include the ingredients in your shopping basket as well.
To add the prefix “big,” the dataset must fall under the three “V” rule.
- Volume – data is measured by physical value and occupied space on a digital medium. When it reaches beyond 150 GB per day, then we can call it big data.
- Velocity – it implies real-time processing and its high capacity.
- Variety – information can come in heterogeneous formats and have little or no structure.
Modern systems add two additional factors to this set.
- Variability – data streams can have peaks and troughs, seasonality, and periodicity.
- Value – this parameter is subjective. To put it short, different types of information need different processing methods and vary by a wide margin.
For example, messages from social networks represent a basic level of data. But secure transactions of a high-performance online paper writing service are from a much higher level.
The task of machines is to determine the degree of importance of the incoming information to structure it as quickly as possible.
Impact on Education
Like any other sphere of life, the educational process generates data. There are five main types of data there:
- forecasts (includes all predictions deriving from the analysis of points 2 through 5);
- personal info (of all students and staff members);
- administrative information;
- data on the use of electronic learning aids like online lectures or digital textbooks;
- reports analyzing the efficacy of the available learning materials.
Today, BD has become the language of communication for educational organizations that seek to improve their strategic and tactical approaches.
Big data technologies help improve and simplify the quality assessment of the educational environment. If done right, digital technologies simplify the process of tracking students’ grades and identifying issues of the learning process.
This method of working with information shortens the response time of colleges and universities to the shifts in society. It prompts the scalability of educational processes and their readiness for a quick change. It also tracks changes and trends in the selected sector. BD’s capabilities are not yet sufficiently used to improve the quality of educational activities.
As we already mentioned, the essential benefit of the big data method is the predictive analysis option. For example, analytics tools can predict the results of strategic decisions. They are essential for improving management efficiency and ensuring a customized approach to all students.
When Theory Meets Practice
In 2013, the University of Nottingham Trent, England, introduced an interactive system displaying students’ performance assessments in the form of a dashboard. It showed info on student engagement in the educational process. The dashboard was designed to reduce student dropout rates, improve attendance, and increase a sense of belonging to the community.
The dashboard was a panel available to students, teachers, and tutors. The board displayed involvement indicators of each student. So, everyone could come up there and evaluate themselves as compared to their classmates. The dashboard featured the following parameters:
- library visits frequency;
- the courses taken by the students;
- extracurricular activities;
- volunteer work;
- classes attendance;
- other educational indicators, including grades.
Thus, any student was able to see their activity in comparison with peers. So, they could determine what aspects demand extra effort.
If a student did not show signs of activity within two weeks, the platform automatically sent notifications to tutors. The latter could quickly contact the student and support them. Three years into the project, the results of the university survey showed that 72% of undergraduates used this student dashboard, and it inspired them to invest more time and effort into the educational process.
Advantages of Performance Analysis
A deep multifactor analysis helps educators better understand their students. There are so many cases describing students left behind because of a low grade in one subject. Some of those individuals suffered from depression, others had family issues, and so on.
A quick analysis of the students’ digital will help avoid aggressive behavior and bullying.
It will be possible to overcome the concept of educational inequality to reduce the barriers to learning for people with disabilities.
Although not every student is a prodigy, bringing them to the average level will become possible. A key is a personalized approach. A teacher will know what learning aids (visual, audio, or interactive materials) give better results.
The pandemic initiated massive shifts in education and its move online. Hopefully, in a couple of years, it will help optimize the learning process. The main aim now is to make it more suitable for both the C-grade and the A-grade students. There are a lot of dependencies when using big data that are not all discovered and used yet. More improvements are yet to come.