org.activemath.studentmodel2.assessment
Interface IBeliefModel

All Known Implementing Classes:

IRTTransferableBeliefModel, SimpleBeliefModel, TransferableBeliefModel

public interface IBeliefModel

This interface allows the usage of different belief models, or better assessment strategies. They are meant to derive a decision on the competency for an item based on the available evidence. Possible models may be: - Bayesian Reasoning / Networks (bayes) - Transferable Belief Model (tbm) - Simple heuristic (simple) - Upper Lower Bound Probabilities (ulp) - etc.

Method Summary

IBeliefContainer	estimateConceptMastery(Collection<IBeliefContainer> masteries) Computes a complete mastery (value in [0, 100]), given masteries for all competencies
IBeliefContainer	estimateMastery(Collection<Evidence> evidences) Calculate the beliefs and estimate the mastery based on the beliefs.
IBeliefContainer	estimateMastery(Collection<Evidence> directEvidences, Collection<Evidence> indirectEvidences) Calculate the beliefs and estimate the mastery based on the beliefs.
String	getName() Get the name of the belief model in use
boolean	isPositiveEvidence(Evidence evidence) Determines whether the given exercise is a positive evidence or a negative one - needed to determine the direction of propagation of indirect evidence.

Method Detail

estimateMastery

IBeliefContainer estimateMastery(Collection<Evidence> evidences)

Calculate the beliefs and estimate the mastery based on the beliefs.

Parameters:

evidences - - A list of evidences to be taken into account

Returns:

- BaliefContainer with corresponding belief values

estimateMastery

IBeliefContainer estimateMastery(Collection<Evidence> directEvidences,
                                 Collection<Evidence> indirectEvidences)

Calculate the beliefs and estimate the mastery based on the beliefs. This method can differentiate between direct and indirect evidence.

Parameters:

evidences - - A list of evidences to be taken into account

Returns:

- BaliefContainer with corresponding belief values

isPositiveEvidence

boolean isPositiveEvidence(Evidence evidence)

Determines whether the given exercise is a positive evidence or a negative one - needed to determine the direction of propagation of indirect evidence.

Parameters:

evidence -

Returns:

True if it is a positive evidence, false otherwise

getName

String getName()

Get the name of the belief model in use

Returns:

- The name of the model, like bayes or tbm

estimateConceptMastery

IBeliefContainer estimateConceptMastery(Collection<IBeliefContainer> masteries)

Computes a complete mastery (value in [0, 100]), given masteries for all competencies

Parameters:

masteries - - a collection containing the different masteries as List of BeliefContainers for each competency

Returns:

A BeliefContainer, that contains the Mastery in [0,100] for a concept