An In-depth guide on the Application of Data Analytics in Education Sector

Data analytics is useful in every field. It has shown its importance in many realms. In the education sector, a large amount of data on people is collected, and data analytics can prove beneficial to solve many problems and provide a better experience to teachers and students.

We know that in schools and colleges, teachers have to handle an enormous amount of data related to students. Students have specific qualities, and different socio-economic backgrounds, and teachers have to analyze how to use each set of data in developing the study plans.

Assessment

With the help of assessment data, teachers identify how much students have grasped from a particular lesson and where they are lacking. With the help of assessment data, teachers can modify their future lesson plans as per the understanding of students. It is time-consuming for teachers to grade the assessments. With the help of data analytics, teachers can know how many students were able to earn more than half credit with the help ECDF chart. Bubble charts can provide answers to questions like how many students performed well in Question A and B, and how many performed well in just one and how many were not able to perform well in both.

Statistical Models

Data Analytics consulting can help provide statistical models that can predict the grades of students through the collected parameters. And if it comes that a student will have a low CGPA, the system can trigger a warning to the teacher that the student needs extra attention to pass the exam. In this way, teachers can know that a student is weak in a particular subject, and he can make a study plan for the student accordingly.

Project Data

From time to time, teachers give projects to students to make learning fun. For projects, students are given rubrics. It is difficult for a teacher to fill the data in rubrics unless she has an additional teacher to help her. Data analytics provide solutions that, along with natural language processing and computer vision, provide a hassle-free solution.

Parent/Guardian Data

Unfortunately, it’s not possible for every parent to attend a parent-teacher meeting. The aim of parent-teacher meet up is to discuss the progress of students and how both parents and teachers can help students perform better and help them succeed. If the data is collected about students and parents that didn’t show up and analyzed to identify the similarities among the families that don’t show up to parent-teacher conferences, it can become easy to understand what are the things stopping these families from attending the conferences. So, next time you can send them targeted messages to ensure attendance.

Dropout Rate

Many students around the world drop out of school and college due to different reasons. Predictive models, with the use of data analysis, can help in identifying students who are at a greater risk of dropping out, and teachers can take precautionary measures against it.

Entries on student behavior

Whenever an incident occurs in school, teachers are required to log in to the school system. To analyze the amount of severity, the metric system is used. The whole process is time-consuming for the school staff, and then the discipline staff of the school spends time to read these entries and decide the course of action. In this process, natural language processing can be of use. If the school is a few years old, there will be many log entries to make a severity level classifier. The system saves the time of teachers.

Demographics Student Data

Demographics student data can help teachers understand the various problems faced by students and how particular students lack resources because of economic reasons.

Judging Panels

When students appear for school or university interviews, their CGPAs and entrance test marks are also taken into account. With the help of data analytics, it can be studied if there is any correlation between absentee rates and how it impacts the performance of students in tests.

Virtual Interview

A virtual interview is held with the help of artificial intelligence. A platform that leverages the power of AI to mimic face to face interview is used. It automatically evaluates the candidate’s body language. The technique can be used to identify who is paying attention in the class and who is not.

Final Words

Data analytics can immensely help the education sector. A predictive model can help in getting to know about the probable outcomes and help in taking the steps that can enhance the experience of students as well as teachers. This way, school staff can know which students are struggling, and they can take steps to improve the performance of students. When teachers know which students are struggling, they can make a personalized plan to guide students and give them learning support facilities.