Automating exercise generation: a step towards meeting the MOOC challenge for embedded systems

Abstract

The advent of massively open online courses (MOOCs) poses several technical challenges for educators. One of these challenges is the need to automate, as much as possible, the generation of problems, creation of solutions, and grading, in order to deal with the huge number of students. We collectively refer to this challenge as automated exercise generation. In this paper, we present a step towards tackling this challenge for an embedded systems course. We present a template-based approach to classifying problems in a recent textbook by Lee and Seshia, and outline approaches to problem and solution generation based on mutation and satisfiability solving. Several directions for future work are also outlined.