Computing Education Research (CER) is the study of how people learn to use programmable and/or trainable technologies. It includes computer science education, as well as other contexts where people learn how to boss computers around to pursue their own interests. Accountants learning to program macros in Excel, biologists learning Python to crunch their data, and children creating interactive stories in Scratch are all people and activities that CER attends to. So are experienced software engineers learning to weave machine learning into their applications, CS graduate students getting their heads around dependent types, and teachers figuring out how to integrate computing into their courses. CER studies learning, and how to support it, using a variety of methods, including design.
This graduate seminar will provide students with a broad understanding of the history and state of the field, including classic systems and research as well as emerging areas of inquiry. We will read and discuss papers from CER, statistics education, science education, and the learning sciences. Students will write a research proposal that charts how we could deepen our collective knowledge about how people learn computing.