Situating Computational Thinking with Big Data
Austin Cory Bart · 2015
As Computational Thinking becomes pervasive in undergraduate programs, new students must be educated in meaningful, authentic contexts that they find both motivating and relatable. I propose working with big data as a novel context for introductory programming, authentic given its importance in diverse fields such as agriculture, history, and more. Big data is considered difficult to use because of its inherent technical obstacles. To overcome these difficulties, I introduce a new project: CORGIS - a "Collection of Real-time, Giant, Interesting, Situated Datasets". The CORGIS project comprises a collection of libraries that provide an interface to big data for students, architectures for rapidly enabling new datasets, and a web-based textbook platform for disseminating relevant course materials. This textbook features an online block-based programming environment, real-time collaborative text editing, and continuous server-side storage. In this poster, I describe the educational theory guiding this work, the novel technolgy created and deployed, and the initial, promising results.