Thursday, April 23, 2015

Predictive Analytics – Primary-level Education

Can we marry predictive analytics with primary-level education and can come up with something better output which helps our kids learn new stuff in a speedier and easier way? 

Yes! We can do. At primary level, what is it that a kid needs to learn? How to write alphabets, pronounce words, read paragraphs, etc., right? 

Nowadays, kids are used to play with video games instead of regular toys; in this case, we can safely assume that they can understand the simple functionalities of software. 

Now, why not we build a software application [should run on a touch-screen tablet!] that teaches kids how to write and read at the same time; besides, it has to apply predictive analytic metrics on the kid’s activity, which helps respective teacher and parents judge his progress. 

For example, if the kid is learning how to write alphabets, then the application acts in the following way: it displays all the alphabets in a lighter mode [watermark!] on the screen. Now, the kid is supposed to write that particular alphabet by tracking it using his stylus [touch screen!]. The application displays the path by showing blinking arrows [showing which direction the stylus has to be moved while writing the alphabet!] to the kid while he is practicing to write the respective alphabet.

Now, based on how the kid learns to write the alphabet, the application records the kid’s activity and using the analytic metrics, displays his score for this activity against the benchmark.

Same thing it does for paragraph reading also. It matches the paragraph content with what the kid is reading, including the words pronunciation, etc., and displays the break-up score, instantly.

The parent/teacher can download all the scores on to a system and display the reports to the concerned persons. 

In summary, based on kid’s yearlong activities, the teacher can judge a kid’s promotion to the next class by using predictive analytics metrics stuff’s projected trends.


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