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Hacking Education Showcase

The 25 awesome apps and analyses that wowed our judges and staff!

« Back to the winning entries

Grant Kot, Joey Dong, Akarshan Kumar


A dynamic visualization of donation-flows over time, helping the viewer grasp both the short-term and long-term trends that exist in the data. For more details, click on the "i" information button on the visualization.

(Categories: Data Analysis, JavaScript, Wildcard)

Vincent DiBartolo


Allows runners to use the miles they run to fund classroom projects of their choosing. Runners can create their own personal pledge drive and share the drive on social networks, and their friends and family can pledge money against each mile recorded on Nike+.
Requirements: Nike+ account

(Categories: JavaScript, PHP, Wildcard)

Alejandro Crosa


Allows you to find local projects in need in funding. You can discover projects that inspire you, give to a specific project right from the app, and keep up with all the latest news from

(Categories: Wildcard)

Paul Fryzel

Provides location-based discovery of nearby classroom projects and integrates with FourSquare to provide project recommendations based on places you've been.

(Categories: Data Analysis, JavaScript, Wildcard)

Ben Sheldon

Print and Share

Enables teachers to easily create professional and printable handouts to more readily promote their classroom projects to friends and neighbors.

(Categories: PHP, Wildcard)

Howie Liu


An iPad app for browsing classroom photos and projects. You can drag photos around, toss them across the screen, and scatter them by shaking the device. Also features a real-time layer to see what other people are browsing.

(Categories: JavaScript, PHP, Wildcard)

Katherine Leipper

Macs for Classrooms

A study of the trend of classroom requests for technology resources with a focus on Apple products; includes household income and WalkScore data.

(Categories: JavaScript, PHP)

Conroy Whitney

DonorsChoose Hacking Education QR Codes

Creates a QR Code for a given classroom project and integrates with CafePress so the user can purchase schwag featuring the QR Code. For the time that the project is active, it acts as a fund-raising tool. After the project is complete, it acts as a memento to a job well-done.

(Categories: JavaScript, PHP, Ruby, Wildcard)

Gregory Belmont

Donors Challenge

Enables any sponsor -- a mayor, a venue owner, a brand marketer, a blog author, or any other individual or organization -- to challenge their customers, supporters, or friends by pledging a contribution to a specific classroom project or group of projects based on the outcome of an event and/or upon the completion of a group goal.

(Categories: PHP, Wildcard)

Kevin Leong

Pledge for America Schools

An Android app that engages local merchants to participate in fundraising for classroom projects.

(Categories: Wildcard)

Dhananjay Ragade and Greg Spurrier


A LinkedIn plugin that allows users to showcase classroom projects they support on their LinkedIn profiles, to search for projects to fund, and to see which projects are supported by people in their network.
Requirements: Users must be whitelisted by the app authors to view. See screenshots.

(Categories: JavaScript, Ruby, Wildcard)

Tyler Schroeder


Analyzes a user's Facebook profile data (currently only location) to recommend classroom projects.

(Categories: JavaScript, .NET)

Madhu Mudigonda

Projects Near Me

Makes discovering local classroom projects easy by detecting the user's location, displaying projects on a map, and providing graphical break-downs of the projects by subject, poverty level, etc.

(Categories: JavaScript)

Joe Larson

DonorsChoose Geographic

A user-friendly wizard helps prospective donors find classroom projects of interest and then displays them on a map.

(Categories: JavaScript)

Matthew Heston

Donors Choose for Facebook

Analyzes a user's Facebook profile to recommend classroom projects of interest and then encourages project sharing with friends.

(Categories: .NET)

Kevin Marshall


Generates classroom project recommendations for any Twitter user based on what that person is saying on Twitter.

(Categories: Python, Wildcard)

Ken Miller


Ranks the largest cities in the US based on classroom project and donation data, then displays live projects in those cities with photos and maps.

(Categories: .NET)

Jason Radford

Predicting Project Completion

An algorithm that uses statistical regression methods to predict the probability of success for most classroom projects within 2-7% accuracy.

(Categories: Data Analysis, Python)

Allie Walker and Jason DeRoner

[Make It Yours]

A data-backed proposal to use Facebook to provide relevant classroom project recommendations.

(Categories: Data Analysis)

David Joerg

Tips For Success, By the Numbers

Uses 10 years of project funding data to provide highly actionable tips for teachers on how to author classroom projects that are more likely to be funded.

(Categories: Data Analysis, Wildcard)

Robert Allison Graph Samples

16 visual analyses of classroom project and funding data, including graphs and narrative from the author.

(Categories: Data Analysis, Wildcard)

Tanay Jaipuria

DonorsChoose An Analysis

An analysis of the effect of various classroom project variables, such as location, poverty level of classroom, resource use, and type of resource, to ascertain what motivates donors to give.

(Categories: Data Analysis, Python, Wildcard)

Michelangelo D'Agostino

In It Together

Maps showing how communities have responded to classroom project requests over the years, displaying both the schools that have posted classroom projects and the origin of the donations to those schools.

(Categories: Data Analysis, Wildcard)

Rem Koning and Jacob Model

Infectious Innovation: Understanding when teachers post creatively and when they do not

A study of the effect of classroom innovation and how it spreads to nearby teachers and schools.

(Categories: Data Analysis)

Jennifer Berk, Rick Cavolo, and Sarah Young Data Mining

Analysis to help identify trends and predict project funding in order to give teachers and a better understanding of what projects, schools, topics, and titles/essays are most likely to be funded.

(Categories: Data Analysis, Wildcard)

« Back to the winning entries