We examine student difficulties with CS1 concepts by analyzing a dataset containing 266,852 student responses to weekly code-writing problems. We find that conditionals and loops prove particularly problematic, even when considering "second chance" data; and that, while we observe some evidence of improvement, certain straightforward applications of loops continue to be problematic at the end of the term. Our contribution is the corroboration of earlier findings, and a call to use online repositories of student submissions as rich sources of data on the student learning experience.

We present the Python Classroom Response System, a webbased tool that enables instructors to use code-writing and multiple choice questions in a classroom setting. The system is designed to extend the principles of peer instruction, an active learning technique built around discussion of multiplechoice questions, into the domain of introductory programming education. Code submissions are evaluated by a suite of tests designed to highlight common misconceptions, so the instructor receives real-time feedback as students submit code. The system also allows an instructor to pull specific submissions into an editor and visualizer for use as in-class examples. We motivate the use of this system, describe its support for and extension of peer instruction, and offer use cases and scenarios for classroom implementation.