Continuing the work of Liquid Movies, we introduce Liquid Learning, an extension for not simply recommending videos but encouraging people to efficiently explore the sea or reservoirs of educational video content.
Currently, there are an overrepresented amount of computational decision-making systems in service of providing recommendations to keep people returning and engaged on some given platform. However, at this unprecedented time where the content on these platforms far exceeds our ability to find the information most relevant to us, we become susceptible to our incomplete intuitions and assumptions about the world, which demonstrably leads us astray in assessing truth and distilling knowledge.
To meet this challenge, Liquid Learning scans the web for visual material related to a topic and organizes it so one can compose a movie on demand or travel through a knowledge space exploring diverse topic presentations. For example, the Bayes theorem can be described through examples, with equations (Bayes formula), graphically (tree diagrams), or geometrically (e.g., Venn diagrams). Unfortunately, it is also connected to typical human biases and reasoning flaws. Liquid Learning finds these explanations, analyzes them, parses them, and provides an interactive space to explore a topic that matches one’s backgrounds, learning styles, and intentions.