Using Big Data to Drive Educational Decisions

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The concept of using large amounts of data to help make decisions that can transform education has become very popular now. This has also been called “data-driven decision making”. There are many ways in which “big data” is used to improve day-to-day educational experiences and make better decisions. For example, everything about a student can be understood from the data they generate, analyzed, and used to decide how to guide them better. This way, a teacher can modify or optimize their teaching strategies or modules keeping in mind the big data generated from just one student or from their entire class of students.

There are so many other ways in which big data can be applied in ordinary and less-than-ordinary situations in schools and colleges. Big data can be used at the level of the teacher to guide the students or it can be used at the level of the school management or board to guide the entire school towards the optimal development of its full potential.

With regards to the teacher-student level, big data can be used to analyze the effectiveness of a lecture, a presentation, a field trip, an experiment, etc. It can be used to analyze an online lesson or course. The big data generated from it can be used to improve the course or to remove elements that are not being helpful to students. Big data can also help analyze a student’s performance to determine the chances of their success. If the data can help teachers reach students who are at risk of failing, from a very early stage and intervene with strategies to help them improve, it can lead to greater success for the student and also for the school. Big data can also be used to analyze what is working, what is leading to good grades among students, and replicate that across other courses.

Big data can be used by schools to assess and determine if their students are being prepared adequately for college, and if not, where they are lacking and how they can overcome these lacks or gaps in education. The one-size fits all learning may not work for every single student, and big data helps to find out what makes for optimal teaching for each student and helps to reach them by modifying the course modules as needed. The instruction style can also be changed based on the big data collected from students.

Big data is collected from a variety of sources, such as attendance records, disciplinary records, grades, etc. This is called system wide data. Inferred student data is when you analyze test results and test questions to determine how much better questions can be formulated to get better results from students. Inferred content data is when content is analyzed to determine how well students understand it or respond to it.

When big data is properly utilized, analyzed, and understood, it can lead to the full potential of students, teachers and schools unfolding.