Bayesian modelling of student misconceptions in the one-digit multiplication with probabilistic programming

Research output: Contribution to conferencePaperpeer-review


One-digit multiplication errors are one of the most exten- sively analysed mathematical problems. Research work pri- marily emphasises the use of statistics whereas learning an- alytics can go one step further and use machine learning techniques to model simple learning misconceptions. Prob- abilistic programming techniques ease the development of probabilistic graphical models (bayesian networks) and their use for prediction of student behaviour that can ultimately influence learning decision processes.
Original languageEnglish
Publication statusPublished - 26 Apr 2016
EventSixth International Conference on Learning Analytics & Knowledge - Edingburg, United Kingdom
Duration: 25 Apr 201629 Apr 2016


ConferenceSixth International Conference on Learning Analytics & Knowledge
Country/TerritoryUnited Kingdom

Fields of Expertise

  • Information, Communication & Computing

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