  Student experiences in large undergraduate Computer Science courses are
increasingly impacted by automated systems. Bots, or agents of software
automation, are useful for efficiently grading and generating feedback. Current
efforts at automation in CS education focus on supporting instructional tasks,
but do not address student struggles due to poor behaviors, such as
procrastination. In this paper, we explore using bots to improve the software
engineering behaviors of students using developer recommendation choice
architectures, a framework incorporating behavioral science concepts in
recommendations to improve the actions of programmers. We implemented this
framework in class-bot, a novel system designed to nudge students to make
better choices while working on programming assignments. This work presents a
preliminary evaluation integrating this tool in an introductory programming
course. Our results show that class-bot is beneficial for improving student
development behaviors increasing code quality and productivity.
