The Discrete Optimization MOOC, An Exploration in Discovery-Based Learning

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Coffrin, Carleton; Van Hentenryck, Pascal


2014-02-10


Journal Article


eLearning Papers


Lausanne, Switzerland


37


51-56


The practice of discrete optimization involves modeling and solving complex problems, which have never been encountered before and for which no universal computational paradigm exists. Teaching such skills is challenging: students must learn, not only the core technical skills, but also an ability to think creatively in order to select and adapt a paradigm to solve the problem at hand. This paper explores the question of whether teaching of such creative skills translates to massive open online courses (MOOCs). It first describes a discovery-based learning methodology for teaching discrete optimization, which that has been successful in the classroom for over fifteen years. It then evaluates the success of a MOOC version of the class via data analytics enabled by the wealth of information produced in MOOCs.


Data61; NICTA; education; optimization; MOOC


http://openeducationeuropa.eu/en/article/The-Discrete-Optimization-MOOC%3A-An-Exploration-in-Discovery-Based-Learning?paper=136477


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English


1887-1542


nicta:7483


Coffrin, Carleton; Van Hentenryck, Pascal. The Discrete Optimization MOOC, An Exploration in Discovery-Based Learning. eLearning Papers. 2014-02-10; 37:51-56. http://hdl.handle.net/102.100.100/221051?index=1



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