The practice of discrete optimization involves modeling and solving complex combinatorial 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 the teaching of such creative skills translates to massive open online courses (MOOCs). It first describes a methodology for teaching discrete optimization that has been successful on campus over fifteen years. It then discusses how to adapt the campus format to a MOOC version. The success of the approach is evaluated through extensive data analytics enabled by the wealth of information produced by MOOCs.
[1]
Steve Cooper,et al.
Reflections on Stanford's MOOCs
,
2013,
CACM.
[2]
Paul Hyman.
In the year of disruptive education
,
2012,
CACM.
[3]
Judy Kay,et al.
MOOCs: So Many Learners, So Much Potential ...
,
2013,
IEEE Intelligent Systems.
[4]
Chris Piech,et al.
Deconstructing disengagement: analyzing learner subpopulations in massive open online courses
,
2013,
LAK '13.
[5]
Randy L. Bell,et al.
The many levels of inquiry
,
2008
.
[6]
Charles R. Severance.
Teaching the World: Daphne Koller and Coursera
,
2012,
Computer.
[7]
J. Bruner.
The act of discovery.
,
1961
.
[8]
Jaakko Kurhila,et al.
Multi-faceted support for MOOC in programming
,
2012,
SIGITE '12.