TERMIUM Plus^®

Fiche 1,  Justifications,  Anglais

Record number: 1, Textual support number: 1 CONT

Brown et al. (1982) reflect on the use of quantitative simulation for making inferences and see it as a double-edged sword. On the one hand, the simulation provides a lot of leverage to the inference process, because large amounts of knowledge are encoded in the model and brought to bear via the simulation. On the other hand, this embedded knowledge is often based on implicit assumptions and empirical decisions on the part of the model's designers, which may be very subtle. For instance, the formulas used to run the simulation may only be valid for certain classes of inputs. If these assumptions are not made "explicit and checkable", they can easily be violated when the simulation involves faults. For teaching purposes, the main drawback of quantitative simulation is its inability to give a full account of the causality underlying its inferences. Causality is pedagogically important because it is the main ingredient of the kinds of explanations human students can understand. In a troubleshooting context, causality, more than information content, drives the diagnostic reasoning and the decision to perform measurements.  1, fiche 1, Anglais, - quantitative%20simulation

Fiche 1,  Justifications,  Français

Record number: 1, Textual support number: 1 OBS

Voir simulateur quantitatif. Comparer à simulation qualitative.  1, fiche 1, Français, - simulation%20quantitative

Fiche 1,  Justifications,  Espagnol