Learning Programming at Scale: Philip Guo’s research

September 11, 2017 at 7:00 am Leave a comment

I love these kinds of blog posts.  Philip Guo summarizes the last three years of his research in the post linked below.  I love it because it’s so important and interesting (especially for students trying to understand a field) to get a broad explanation of how a set of papers relate and what they mean.  Blog posts may be our best medium for presenting this kind of overview — books take too long (e.g., I did a book to do an overview of 10-15 years of work, but it may not be worth the effort for a shorter time frame), and few conferences or journals will publish this kind of introspection.

My research over the past three years centers on a term that I coined in 2015 called learning programming at scale. It spans the academic fields of human-computer interaction, online learning, and computing education.

Decades of prior research have worked to improve how computer programming is taught in traditional K-12 and university classrooms, but the vast majority of people around the world—children in low-income areas, working adults with full-time jobs, the fast-growing population of older adults, and millions in developing countries—do not have access to high-quality classroom learning environments. Thus, the central question that drives my research is: How can we better understand the millions of people from diverse backgrounds who are now learning programming online and then design scalable software to support their learning goals? To address this question, I study learners using both quantitative and qualitative research methods and also build new kinds of interactive learning systems.

Source: Learning Programming at Scale | blog@CACM | Communications of the ACM

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