Find My Match

About this idea

Students face a life changing decision when choosing what university is most appropriate to their needs. In the short term their decision may be constrained by cost of tuition and living expenses, proximity to their hometown or the availability of good sports facilities and social life. In the long term, the quality of lectures and the prestige of the institution play a paramount role in their employability prospects. Nowadays students are forced to spend a significant amount of time perusing university rankings and surveys, and manually trawling through data (living expenses, tuition fees, transport costs, to name a few) and web pages to make an informed decision.

 

Much like Skyscanner and Momondo do for air travel, the application described here integrates the data publicly available into a single tool that allows users to specify the particular criteria that are of importance to them and to apply individual filters and constraints. The app then displays clearly the options available to the student, significantly reducing the time required to narrow down their choices, and allowing for quick comparison of different scenarios.

 

The data available comes from reputable sources such as The Higher Education Statistics Agency and Unistats, via an API, the National Public Transport Access Nodes and the Times Higher Education Survey. Most of the data is originated by governmental bodies and is updated regularly, hence guaranteeing the sustainability and continuity of the application in the future.

 

Universities will be incentivised to publish their data so that they can reach a greater student audience. For example, publishing data on their catering and restaurant facilities that can be incorporated as a selection criteria into the app may incline the balance to their favour for the student foodies out there.

 

I anticipate that the main challenges that I will encounter in the development of the app are threefold. First, efficiently carrying out the data mining necessary to feed the app; second, sourcing data that may be available but not open, and finally, presenting the data in the most efficient, user friendly and informative way to the users.

 

Data mining does not present a technical challenge per se, but it is a rather time consuming process. The expert’s support offered as part of the award will be instrumental to knock down the other two challenges. The monetary support will allow me to attend conferences to put me in contact with experts in the world of open data, where I could share my ideas and receive their invaluable opinions and insight.

 

Far from being a one hit wonder, the application offers potential for future development; in addition to incorporating new criteria as new data becomes available, the usage of the app will enable to identify what is most important for students when choosing a university, and this will allow to identify trends and to segment the market to provide targeted products and apps to the different market participants.