Automating Exercise Generation: A Step towards Meeting the MOOC Challenge for Embedded Systems

Dorsa Sadigh, Sanjit A. Seshia, and Mona Gupta. Automating Exercise Generation: A Step towards Meeting the MOOC Challenge for Embedded Systems. In Proc. Workshop on Embedded Systems Education (WESE), October 2012.

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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 <i>automated exercise generation</i>. 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.

BibTeX

@inproceedings{sadigh-wese12,
  author    = {Dorsa Sadigh and Sanjit A. Seshia and Mona Gupta},
  title     = {Automating Exercise Generation: A Step towards Meeting the {MOOC} Challenge for Embedded Systems},
 booktitle = {Proc. Workshop on Embedded Systems Education (WESE)},
 month = "October",
 year = {2012},
 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  
{\it 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.},
}