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How Big Data Can Revolutionize Education

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Big data is helping schools to better analyze performance, assess student learning and plan for the future.

Big data has been driving revolutionary changes in education. There hardly remains an area in education not impacted by big data. The changes are evident in the ways educational institutions are governed, course quality is managed and student participation and performance are managed. Compared to the education system in the past, the changes represent a radical shift in paradigm. Data is at the core of the revolution. Analytics is helping educational institutions to better manage course quality, student performance and behavior, and overall administration. Still, some are asking if such changes will improve absorption of lessons by students and encourage higher practical applications of the lessons learned.

Education System Before Big Data

The education system can be understood in terms of how its different areas worked before big data was introduced.


For the purpose of this article, coaching is defined as the methods applied to teach students. Coaching was provided both in the classroom and distance formats (and it still is). In the classroom, students would attend classes or lectures, attend practical or laboratory sessions and take tests. The defining features of classroom coaching and, to a lesser extent, the distance education format, were the interaction and the relationship between the teacher and the student. In the distance education format, students would receive course materials sent by the educational institution, study, take periodic evaluations, and depending on the course, possibly also attend a few classes. (For more on distance learning, see Can Online Education Really Make the Cut?)

Student Evaluation

Students were evaluated based on their performance in various tests. Usually, the test scores would reveal the inclinations of students towards disciplines. Teachers would give feedback on the behavior of students, although there would not be any mechanism of objectively storing feedback. Though a student's behavior would be observed over a period of time and feedback provided, it was based purely on observation, gut feeling and other feedback.


Course Materials

All students of a particular program were required to study the same syllabus and take the same tests. The course materials would be in the form of books, charts, various supplies depending on the stream, and audio and video content. Other than tests, quizzes or interactions, there was no way to determine how well the students were absorbing the lessons.


Institutes would be administered mostly based on planning, trial and error and experience. For example, the choice of extracurricular activities would be determined based on votes, suggestions, experience and other factors, but not data.

Education System With Big Data

To understand the impact of big data on education, let us examine how the different areas have been impacted.

School Administration and Achievements

Schools have been able to objectively evaluate their achievements against their targets such as academic results, student discipline, teacher performance, quality of course materials, teacher-student interactions and grievance redresses. A number of software tools, which help schools do the same, are available in the market. One such tool is Eduvant, with a mission, according to its website, “to help schools continuously improve student outcomes through intelligent daily data use.”

A middle school in the U.S. found that the number of students punished for misbehavior has been increasing. When the school investigated the incidents with the help of analytics, it discovered that the rise in misbehavior coincided with a reduction in the number of school excursions, such as sledding and ice skating trips. When the excursions were increased, misbehavior among students reduced. That was a real-life example of how data could solve problems in educational institutions.

Lesson Absorption

It is being increasingly realized that application of data mining and analytics can help provide customized, intelligent course materials to students. Ability to absorb lessons varies across students and it is important to deliver course materials based on an individual student’s aptitude and capacity. For example, while one student may be able to grasp theoretical descriptions of the laws of physics, another may need a lot of examples to understand the same. (For more on data mining, see 7 Steps for Learning Data Mining and Data Science.)

Using data, you can get answers such as the following:

  • Is the student ready to move to the next lesson?
  • What student actions indicate higher satisfaction and engagement?
  • What student actions indicate better learning?

Learning analytics can help institutions improve student performance by taking such steps as collecting data from online learning systems, predicting future performance, displaying data on dashboards and providing coaching precisely according to student aptitude.

Reduce Cheating and Plagiarism

A number of tools and technologies are being offered to help educational institutions to detect, predict and prevent cheating and plagiarism in examinations. One such tool is Proctortrack. Proctortrack installs webcams and microphones in examination halls to help identify incidents of cheating. The tool can store data on the habitual offenders and sporadic offenders and create a profile, based on which prediction patterns can be created. Educational institutions can examine the analytics and take steps. A number of experts, though, consider such tools to be excessively intrusive and unacceptable. Security researcher Jake Binstein, for example, published tips on getting around the Proctortrack system.

Personalized Learning

Unlike standard syllabi, a number of tools are now providing personalized learning experiences to students. As stated earlier, learning abilities and aptitudes vary and that is what forms the basis of such tools. The tools take into account the natural aptitude, learning patterns and motivation of individual students and create tailored courseware. Such courseware is usually delivered through computers and tablets and is self-paced.

Case Study

There are several case studies to prove how data has transformed how schools are run across the U.S.

In the Menomonee Falls School District in Milwaukee, the staff is constantly analyzing data. The cafeteria supervisor tracks data on student, teacher and parents’ preferences on food. The janitor monitors cleanliness in the bathrooms.

It also appears that students are developing a special liking for data-driven lessons. Alyssa Walter, a student at Riverside Elementary School, has been keeping track of her progress in art class. According to Alyssa, “I like that it makes school more fun, and I like that you get to keep track of goals. Makes me feel proud of myself.”


Without a doubt, big data represents the next wave in education and it has the potential to transform education. However, one should not lose sight of the fact that amidst this data onslaught, the old-fashioned interaction between teachers and students and concepts like group learning still stand. While online learning is getting bigger, nothing still beats the effectiveness of practical applications or experiential learning. While data promises to provide a better learning experience, some experts still wonder if this will guarantee better absorption of lessons. These experts believe that for all the knowledge delivered by the online platform, nothing beats the experience and wisdom of the classroom teacher.


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Kaushik Pal
Technology writer
Kaushik Pal
Technology writer

Kaushik is a technical architect and software consultant with over 23 years of experience in software analysis, development, architecture, design, testing and training. He has an interest in new technologies and areas of innovation. He focuses on web architecture, web technologies, Java/J2EE, open source software, WebRTC, big data and semantic technologies. He has demonstrated expertise in requirements analysis, architectural design and implementation, technical use cases and software development. His experience has covered various industries such as insurance, banking, airlines, shipping, document management and product development, etc. He has worked on a wide range of technologies ranging from large scale (IBM…