MOOC and Mechanized Grading

Christian Queinnec

2014

Abstract

As many others, we too are developping a Massive Online Open Course or MOOC. This MOOC will teach recursive programming to beginners and will heavily use an already existing infrastructure for mechanical grading (Queinnec, 2010). This position paper discusses how these two components are combined in order to increase students’ involvement.

References

  1. Beck, K. (2000). eXtreme Programming. http://en. wikipedia.org/wiki/Extreme_programming.
  2. Beck, K. and Gamma, E. (2012). The JUnit framework, v4.11. http://junit.org/.
  3. Brygoo, A., Durand, T., Manoury, P., Queinnec, C., and Soria, M. (2002). Experiment around a training en-
  4. gine. In IFIP WCC 2002 - World Computer Congress,
  5. Cen, H., Koedinger, K., and Junker, B. (2006). Learning factors analysis - a general method for cognitive model evaluation and improvement. In Paper presented at the 8th International Conference on Intelligent Tutoring Systems, pages 164-175.
  6. Felleisen, M., Findler, R., Flatt, M., and Krishnamurthi, S. (1998). The DrScheme Project: An Overview. SIGPLAN Notices, 33(6):17-23.
  7. Ferguson, K. (2005). Improving intelligent tutoring systems: Using expectation maximization to learn student skill levels.
  8. Glickman, M. (1995). The Glicko system. Technical report, Boston University. http://glicko.net/glicko.doc/ glicko.html.
  9. Google (2013). CourseBuilder. https://code.google.com/p/ course-builder/.
  10. Graepel, T., Herbrich, R., and Minka, T. (2007). TrueSkillTM: A bayesian skill rating system. Technical report, Microsoft. http://research microsoft.com/ en-us/projects/trueskill/.
  11. Heiner, C., Beck, J., and Mostow, J. (2004). Lessons on using its data to answer educational research questions. In Workshop Proceedings of ITS-2004, pages 1-9.
  12. Jonsson, A., Johns, J., Mehranian, H., Arroyo, I., Woolf, B., Barto, A., Fisher, D., and Mahadevan, S. (2005). Evaluating the feasibility of learning student models from data. In Proceedings of the Workshop on Educational Data Mining at AAAI-2005, pages 1-6. MIT/AAAI Press.
  13. Peschanki, F. (2013). fredokun/mrscheme.
  14. Queinnec, C. (2010). An infrastructure for mechanised grading. In CSEDU 2010 - Proceedings of the second International Conference on Computer Supported Education, volume 2, pages 37-45, Valencia, Spain.
  15. Queinnec, C. (2011). Ranking students with help of mechanized grading. See http://hal.archives-ouvertes.fr/ hal-00671884/.
  16. Striewe, M., Balz, M., and Goedicke, M. (2009). In Cordeiro, J. A. M., Shishkov, B., Verbraeck, A., and Helfert, M., editors, CSEDU (2), pages 54-61. INSTICC Press.
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Paper Citation


in Harvard Style

Queinnec C. (2014). MOOC and Mechanized Grading . In Proceedings of the 6th International Conference on Computer Supported Education - Volume 2: CSEDU, ISBN 978-989-758-021-5, pages 241-245. DOI: 10.5220/0004942102410245


in Bibtex Style

@conference{csedu14,
author={Christian Queinnec},
title={MOOC and Mechanized Grading},
booktitle={Proceedings of the 6th International Conference on Computer Supported Education - Volume 2: CSEDU,},
year={2014},
pages={241-245},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004942102410245},
isbn={978-989-758-021-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Computer Supported Education - Volume 2: CSEDU,
TI - MOOC and Mechanized Grading
SN - 978-989-758-021-5
AU - Queinnec C.
PY - 2014
SP - 241
EP - 245
DO - 10.5220/0004942102410245