How Big Data is Transforming the Education Sector
Big Data in Education
As the amount of information grows, education systems in many countries suffer from the inability to process and analyze it properly. As a result, the level of education suffers as well. Students are often unable to cope with the volume of tasks assigned, buy college essays online, cheat on tests. At the same time, teachers and professors do not have time and opportunities to check the flow of data manually.
The education system has actually always generated a significant amount of data. The only question was how to start working with these data at the system level: analyze the information and make decisions based on the data received.
There are five main types of data distinguished in the education domain:
- Personal data
- Data on the interaction of students with electronic learning systems (e-textbooks, online courses)
- Data on the effectiveness of learning materials
- Administrative (system-wide) data
- Projection data
Fortunately, there are modern solutions that can help to automate and enhance the process of data gathering and analysis.
Let’s review how various educational establishments already leverage the benefits of Big Data tools nowadays, and what operations can it alter in the modern system on education.
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Big Data in Education Sector
Below are the advantages of big data in education field:
1. Choosing a Future Career
Six technological universities in South Carolina has a new program on obtaining a new profession called SC ACCELERATE. It is focused on people over 25 and veterans. Data analysis allows participants to choose an education and career that best matches their experience and personal qualities. The CareerChoice GPS program conducts predictive data analysis and helps to determine the choice of career. The service examines the character traits of the student, his academic results, the experience of previous work. Candidates apply to the most suitable universities — and the latter only benefit from this. It is also profitable for the employees as they get trained professionals who are ready to work.
2. Personalized Education
One of the popular strategies for personalizing learning is to offer an additional online course to students lagging behind. As the participant answers questions, the platform will be able to predict the student’s readiness for new topics. The University of Advancing Technology in Arizona, for example, needed to develop a new Math course as students had to prepare for the exam for a whole year. After having used additional courses based on the Knewton platform, about half of the students were able to take the exam at least a month earlier.
Predictive modeling is another area of application of Big Data. The U.S. colleges and universities send their letters of request to prospective students, inviting them to enroll in a particular institution. Each university seeks to invite the most promising students who are likely to apply. To facilitate the work of the admission committee, analysts from ForecastPlus have collected and analyzed several types of student data: ethnicity, performance in a number of subjects, final papers, and grades. ForecastPlus predictive modeling has proved its effectiveness in more than a hundred U.S. campuses. Thus, Creighton University in the state of Nebraska was able to exclude 35000 not the most promising students and not to send them letters. This allowed saving more than 30 thousand dollars.
3. Enhancing the Quality of Teaching
More and more schools are starting to use technology, producing a huge flow of data. At Roosevelt Elementary School near San Francisco, teachers use a software called DIBELS while giving reading assignments. This program helps to identify students who are lagging behind and offer them some help. This allows teachers to quickly prepare and adapt their lessons to students’ needs. Assessing the quality of teaching with tests cannot be really effective: in the end, teachers simply train students on a particular type of activity. By analyzing the data about the learning process, school management can better assess teachers and apply changes if necessary.
4. Big Data and Economy
According to statistics, 400,000 students are expelled from the universities of the United States every year. Many students take loans to get a higher education. For them, dropping out is not only significant risk of debt failure but also a severe worsening of the whole credit history. The students’ dropout also has a negative impact on the institutions themselves: the more students drop out, the less profitable they are, and the less government financial support they receive.
In addition to the economic factor, the percentage of first-year students moving to the next course affects the position of the college in the national ratings.
To address this issue, Virginia Commonwealth University, together with a research company called Education Advisory Board, conducted a survey to identify students at risk and help them. Students who started missing classes or receiving poor grades were the most likely to leave the educational establishment. A platform was created for the university to aggregate all student grades and find problems. Staff can work with them individually. For example, teachers can offer a student, a tutor or other assistance. Within one semester, the number of students who completed the course increased by 16%, and the number of students who proceeded to the next course increased by 8%.
Ball State University in Indiana uses Big Data to analyze students’ participation in a variety of campus activities. This parameter is considered to be a key one in terms of academic success. The university monitors the frequency of visiting campus and diverse activities with the help of identification cards. If a student’s involvement is decreasing, the university staff can identify the cause and can offer assistance. Sometimes students also buy college essay and are unable to cope with the number of tasks assigned.
These were all the benefits of big data in education industry. If you want to add any other benefits, do mention in the comment section.