Robert Legenstein’s research while affiliated with Graz University of Technology and other places

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Publications (1)


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

April 2016

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227 Reads

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8 Citations

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Robert Legenstein

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One-digit multiplication errors are one of the most extensively analysed mathematical problems. Research work primarily emphasises the use of statistics whereas learning analytics can go one step further and use machine learning techniques to model simple learning misconceptions. Probabilistic 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.

Citations (1)


... Students' errors provide a unique window into the mind, as error responses may reflect the cognitive processes-such as applied strategies-activated during problem solving. This fundamental understanding has spawned decades of research, from classifications of errors (Ben-Zeev, 1998;Straatemeier, 2014), and cognitive models aimed at explaining errors (Braithwaite et al., 2017;Buwalda et al., 2016), to the diagnosis of observed errors (Taraghi et al., 2015;Taraghi et al., 2016). In this contribution to the field of errors in learning, we propose a model for the latter. ...

Reference:

Tracing Systematic Errors to Personalize Recommendations in Single Digit Multipli- cation and Beyond
Bayesian modelling of student misconceptions in the one-digit multiplication with probabilistic programming
  • Citing Conference Paper
  • April 2016