Position paper: From interest to usefulness with BlockPy, a block-based, educational environment

As block-based environments are used for more mature audiences, the environments must mature themselves. Based on holistic theories of academic motivation, this means making the environment present itself as both interesting and useful, without sacrificing pedagogical power and scaffolding. We present Data Science as a potential context that satisfies all of these constraints, and describe our new block-based programming environment for education that supports data science from day one: BlockPy, available at http://think.cs.vt.edu/blockpy/. BlockPy features a number of powerful, authentic features meant to promote transfer for students to conventional environments as they progress. This includes mutual language translation and interactive feedback, but also powerful tools for getting real-world data and visualizing it. As we have developed the tool, we have identified a number of major research questions that should be answered in order to determine the validity of our hypothesis and the potential of our approach: in particular, how can this environment and context support educators and diverse learners as they progress into conventional environments.