Implementing an Open-Access, Data Science Programming Environment for Learners

• DOI: 10.1109/compsac.2016.132
• Publication Date: 2016-08-25T21:14:00Z
• Authors: Austin Cory Bart; Javier Tibau; Eli Tilevich; Clifford A. Shaffer; Dennis Kafura
• Keywords: 4. Education; 05 social sciences; 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology; 0503 education

A key retention issue when educating computing novices is ensuring that the frustrations of mastering programming fundamentals do not demotivate and discourage students from studying discipline. In particular, non-CS majors often struggle to find relevance in traditional curricula tend either emphasize abstract concepts, focus on non-practical entertainment (e.g., game animation design), or rely decontextualized settings. To address these issues, this paper introduces BlockPy, a block-based environment for Python (http://www.blockpy.com). BlockPy web-based, open-access supports introductory with an emphasis data science. It promotes long-term transfer by scaffolding introduction textual (Python) through view, ideal beginners any background. By supporting latest Learning Tools Interoperability (LTI) standards, designed support both informal learners formal class Specifically, it can be configured provide guiding feedback its interactive problems, so as at their own pace. The results pilot study initial deployment utilization indicate potential many problems faced novice learners.