Foundation for Learning Equality

License: MIT license

Web Page: https://learningequality.org/ka-lite/user-guides/gsoc-ideas-list-2015

Mailing List: https://groups.google.com/a/learningequality.org/forum/#!forum/dev

The Foundation for Learning Equality (FLE) is a non-profit organization that is committed to enabling every person in the world to achieve a quality basic education, through supporting the creation and distribution of open educational resources, and facilitating their use inside and outside of classrooms around the world.

Over the past 2 years, FLE has been developing and supporting the deployment of KA Lite (https://learningequality.org/ka-lite/), an open-source, cross-platform learning platform that provides access to Khan Academy educational materials -- including videos, exercises, and coach reporting tools -- to users in offline settings, on low-cost hardware. KA Lite has been installed in over 140 countries around the world (https://learningequality.org/ka-lite/map/), and is being used by hundreds of US-based and international organizations as part of their educational initiatives. More recently, FLE has been working with its partners to extend KA Lite into a more general offline content distribution platform, and adapting it to serve the needs of teacher training programs in countries with limited ICT infrastructure.

Projects

• Improve accessibility of the KA Lite platform In line with one of core values of FLE, “Design for Everyone”, this project aims to improve the accessibility of KA Lite, an offline version of Khan Academy, by exploring the experience of diverse learners through user testing, and letting the results of those tests guide the technical solutions. Project will use the Website Accessibility Conformance Evaluation Methodology (WCAG-EM) to determine compliance with WCAG 2.0, and try to integrate a11y into the automated test workflow of KA Lite.
• Performance optimization of KA Lite for low-powered servers Ka-lite is an open-source, cross-platform learning platform that provides access to Khan Academy educational materials to users in offline settings, on low-cost hardware. While as we are going to serve an increasing number of content, the performance bottleneck appears. Therefore in this project, we are going to address the performance bottleneck and optimize that as far as we can.
• Recode Khan Academy videos into a low-bandwidth vector format Khan Academy videos are essentially a series of pen-strokes on a simple background image. If we could accurately identify the operations being performed (like drawing, erasing) and the visual objects being drawn, we can convert the video into a vector-based representation which will contain almost the same amount of information but would require a very low storage space. We also need a system to create new videos using this vector-based approach and the playback capability.