Data Visualization & Analytics Will Transform Education sector

February 6, 2017 By 0 Comments

Introduction

Education sector is one of the most dynamic and vital realms of human development where new innovations and experiments are essential for accelerating the pace of progress. Technology is no exception to this.

Adopting Data Visualization technology, schools, colleges and universities will now gain deep insights about a number of aspects. These include student behavior, testing results, careers developments of students as well as educational needs based on changing societies.

Adoption of technology in Education sector

Data Visualization & Analytics allow for very exciting changes in the educational field that will revolutionize the way students learn and teachers teach. The overall goal within the educational system is to improve student results. Better students are good for society, organizations as well educational institutions. Currently, the answers to assignments and exams are the only measurements on the performance of students. During his or her student life however, every student generates a unique data trail. This data trail can be analyzed in real-time to deliver an optimal learning environment for the student as well to gain a better understanding in the individual behavior of the students.

It is possible to monitor every action of the students. How long they take to answer a question, which sources they use or which questions they skipped. Also, how much research was done, what the relation is to other questions answered, which tips work best for which student etc. Answers to questions can be checked instantly and automatically give instant feedback to students.

In addition, Data Visualization & Analytics can help to create groups of students that prosper due to the selection of who is in a group. Students often work in groups where the students are not complimentary to each other. With algorithms it will be possible to determine the strengths and weaknesses of each individual student based on the way a student learned online, how and which questions were answered, the social profile etc. This will create stronger groups that will allow students to have a steeper learning curve and deliver better group results.

Conclusion

All this data will also help to create a customized program for each individual student. Data Visualization allows for customization at colleges and universities, even if they have 10000’s of students. This will be created with blended learning; a combination of online and offline learning. It will give students the opportunity to develop their own personalized program, following those classes that they are interested in, working at their own pace, while having the possibility for (offline) guidance by professors. Providing mass customization in education is a challenge, but thanks to algorithms it becomes possible to track and assess each individual student.

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