Education

Reflecting their student populations, universities have long been bastions of oodles of consumer technology. We are awash in mobile phones, laptops, tablets, gaming consoles, and the like. If one combines mobile consumer technology with Big Data analytics, one gets a host of new possibilities ranging from new ways of providing students with basic support to new ways of getting students to learn what the faculty needs them to learn. If we can get the right information flowing through the minds of students, perhaps we can improve their success. We can potentially help transform the classroom from the 19th century to the 21st. The byproducts of all this data are the new insights that can drive decision making in new ways. When one adds into the mix advanced data visualization capabilities, one gets something different for university administrators and faculty: better and approachable insight into university operations and even the minds of the students. Higher education is at the cusp of gathering an unprecedented amount of information using affordable tools and techniques. The possibilities are numerous and succinctly expressed in the following statement:

Sample Architecture

IMPROVE STUDENT RESULT

The overall idea of leveraging big data within the educational system is to improve the student results. Currently, the only measurement of the performance of students is the answers to assignments and exams. However, during his or her life, each student generates a unique data trail. Analyzing this data trail in real-time will help gain a better understanding of the individual behavior of students, and in creating an optimal learning environment for the students. With big data in the education sector, it is possible to monitor student actions, such as how long they take to answer a question, which sources they use for exam preparation, which questions do they skip, etc. These and similar to these questions can be answered automatically and instantly, giving each student instant feedback.

CUSTOMIZE PROGRAMS

With the help of big data, customized programs for each individual student can be created. Even if colleges and universities have lakhs of students, customized programs can be created for each of these students. This is possible with the help of what is called as 'blended learning' - a combination of online and offline learning. This gives students the opportunity to follow classes that they are interested in and also work at their own pace, while still having the possibility for offline guidance by professors. We already see this happening in the case of MOOCs that are developed and delivered around the world now. For example, when the Machine Learning class at Stanford University was taught by Andrew Ng, only 400 students participated. However, when the same course was delivered as a MOOC, it attracted 100,000 students.

REDUCE DROPOUTS

As big data in the education sector would help improve student results, dropout rates at schools and colleges would also reduce. Educational institutions can use predictive analytics on all the data that is collected to give them insights on future student outcomes. Such predictions can also help run scenario analysis on a course program before it is introduced into the curriculum; minimizing the need for trial-and-error. In fact, big data can also be used to monitor how students are performing in the job market after graduating from college. This would also help the future students in choosing the right college and course.

TARGETED INTERNATIONAL RECRUITING

With big data in the education sector, institutions can more accurately predict applicants and also analyze the possible factors that affect the application process. Such knowledge will allow institutions to adjust their recruitment strategies and allocate funds accordingly. Such an influx of data will also help students analyze information about schools around the world, speeding up the search and application process for international students too.