Personalized Learning

Demo

Email: demo
Password: demo

Inspiration:

We all believe that the current focus in higher education is valuing the “college living experience” over the learning experience while attending school.

How Personalized Learning Works:

Our Hackathon idea is called Personalized Learning, with the goal to create a personalized learning environment for every student across the nation. To do this we plan on utilizing individual students’ personality and preferred learning styles to assist in their class registration process.

To do this we have created a website that will survey each student when they register. Each student will take an aptitude test along with a personality test, their results will be show and the profile they have now created will be assigned 2 colors representing their personality and preferred learning style.

Next by utilizing the Echo 360 program offered at UML and other programs from different schools. We will monitor and analyze different professors on how they conduct their classroom and how they emphasize their students learn. The professor will then be assigned a color on their results. The student will now be able to see when selecting a class what professors’ color best matches their own.

Once the student is given their unique colors, they will be able to search for their classes through the schools data base and view the list of professors. When looking at the list of possible classes the teaching styles of each professor will be displayed with their corresponding color. The student will now be able to search for professors’ and select the best fit for them and their unique learning style.

What’s our next step?

Next we plan on integrating our website into the existing course catalog at U-Mass Lowell to gather real time data on the interaction between students and professors. Once we have a foundation we will begin to implement the additional features such as: interactive professor profiles, video recordings of lectures, student feedback matching system, course suggestion algorithms, and additional aptitude tests.

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