an open and inspectable learner modeling with a negotiation mechanism to solve cognitive conflicts...

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Introduction Related Work Our Proposal Demonstration Scenario Final Considerations References An Open and Inspectable Learner Modeling with a Negotiation Mechanism to Solve Cognitive Conflicts in an Intelligent Tutoring System Evandro Costa, Priscylla Silva, Jonathas Magalh˜ aes and Marlos Silva TIPS Group Computing Institute Federal University of Alagoas, Brazil Federal University of Campina Grande, Brazil E. Costa, P. Silva, J. Magalh˜ aes and M. Silva PALE UMAP 2012 1

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Some researchers have developed relevant and diverse proposals for improving the content quality of the learner model in Intelligent Tutoring Systems, mainly reducing its uncertainty. Following this aim, this paper proposes an open learner modeling approach using Bayesian networks, focusing on negotiation mechanism to solve detected cognitive conflicts that can emerge when the learner inspects information of his model inferred by the system. Therefore, we addressed some issues concerning the provision of inspectable model and negotiated updating of this model. Its contribution lies in the fact that the learners attempt to change the learner model is met with a challenge, leading to a decision if the learner claims to know more (or less) than the model represents.

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Page 1: An Open and Inspectable Learner Modeling with a Negotiation Mechanism to Solve Cognitive Conflicts in an Intelligent Tutoring System

IntroductionRelated WorkOur Proposal

Demonstration ScenarioFinal Considerations

References

An Open and Inspectable Learner Modeling with aNegotiation Mechanism to Solve Cognitive Conflicts

in an Intelligent Tutoring System

Evandro Costa, Priscylla Silva,Jonathas Magalhaes and Marlos Silva

TIPS GroupComputing Institute

Federal University of Alagoas, BrazilFederal University of Campina Grande, Brazil

E. Costa, P. Silva, J. Magalhaes and M. Silva PALE UMAP 2012 1

Page 2: An Open and Inspectable Learner Modeling with a Negotiation Mechanism to Solve Cognitive Conflicts in an Intelligent Tutoring System

IntroductionRelated WorkOur Proposal

Demonstration ScenarioFinal Considerations

References

Research Context

Learner modeling tasks in ITS;

High level of uncertainty;

Probabilistic Learner Modeling in ITS;

Opening and Viewing Learner Model;

Presence of Cognitive Conflicts;

Mechanisms for dealing with conflicts;

Negotiating the open learner model.

E. Costa, P. Silva, J. Magalhaes and M. Silva PALE UMAP 2012 2

Page 3: An Open and Inspectable Learner Modeling with a Negotiation Mechanism to Solve Cognitive Conflicts in an Intelligent Tutoring System

IntroductionRelated WorkOur Proposal

Demonstration ScenarioFinal Considerations

References

Research Questions

Q1: What approach should we adopt to deal with uncertaintyfound in a learner model for ITS?

Q2: What is an appropriate way to define and viewing OLM?

Q3: How can we detect cognitive conflicts between the studentand the system concerning problem solving activities?

Q4: How can we effectively address these conflicts?

E. Costa, P. Silva, J. Magalhaes and M. Silva PALE UMAP 2012 3

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References

How those Questions have been addressed?

With respect to Q1 – Representation and Maintenance:

Conati et al. [2];

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Page 5: An Open and Inspectable Learner Modeling with a Negotiation Mechanism to Solve Cognitive Conflicts in an Intelligent Tutoring System

IntroductionRelated WorkOur Proposal

Demonstration ScenarioFinal Considerations

References

How those Questions have been addressed?

With respect to Q2 – OLM and Visualization:

Zapata and Greer [5];

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References

How those Questions have been addressed?

With respect to Q3 and Q4 – Conflicts detection and Negotiation:

Bull et al. [1];

Dimitrova [3];

Thomson and Mitrovic [4].

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Our General Approach

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Page 8: An Open and Inspectable Learner Modeling with a Negotiation Mechanism to Solve Cognitive Conflicts in an Intelligent Tutoring System

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Demonstration ScenarioFinal Considerations

References

The Open Learner Model

E. Costa, P. Silva, J. Magalhaes and M. Silva PALE UMAP 2012 8

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Demonstration ScenarioFinal Considerations

References

The Open Learner Model

The system put a problem to the learner: 13 + 4

3 ;

He declares his belief:

Very unsure = 0.05;Unsure = 0.25;Almost sure = 0.5;Sure = 0.75;Very sure = 0.95.

Then, he submits a solution and the system evaluate it andreturns a grade [0,1].

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Page 10: An Open and Inspectable Learner Modeling with a Negotiation Mechanism to Solve Cognitive Conflicts in an Intelligent Tutoring System

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References

The Open Learner Model

(a) The Ms . (b) The Mt .

Figure: Task-specific part of the Learner Model.

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References

The Open Learner Model

(a) The Ms . (b) The Mt .

Figure: Domain-general part of the Learner Model.

E. Costa, P. Silva, J. Magalhaes and M. Silva PALE UMAP 2012 11

Page 12: An Open and Inspectable Learner Modeling with a Negotiation Mechanism to Solve Cognitive Conflicts in an Intelligent Tutoring System

IntroductionRelated WorkOur Proposal

Demonstration ScenarioFinal Considerations

References

The Open Learner Model

Figure: The Visualization of the Learner Model.

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References

Negotiation Process

The negotiation mechanism depends on the learner’s credibility:

Figure: The DBN of the learner’s credibility.

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References

Negotiation Process

When the learner wants to change the tutor’s belief

Credibility L’s belief < T’s belief L’s Belief > T’s beliefLow Persuasion Persuasion

Medium Persuasion CooperationHigh Persuasion Cooperation

When the tutor wants to change the student’s belief

Credibility L’s belief < T’s belief L’s belief > T’s beliefLow Support Contestation

Medium Support ContestationHigh Support Contestation

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References

Prove Process

During the negotiation:

The system can request that the learner proves his knowledge, or;The learner can request the opportunity of prove.

The proof process consists of:

Two problems and the learner has two chances to solve eachproblem;Then, his model is updated.

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Demonstration Scenario

Figure: Example of Negotiation Dialogue Started by the Learner.

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We are we going next?

Improve the visualization, allowing the visualization of the twoparts of the model;

Put other evidences in the learner model: social characteristics,CV-curriculum of the student, collaborative information;

Perform an experiment in a basic math classroom.

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References

Susan Bull, Paul Brna, and Helen Pain.Extending the scope of the student model.User Modeling and User-Adapted Interaction, 5(1):45–65, 1995.

Cristina Conati, Abigail Gertner, and Kurt Vanlehn.Using bayesian networks to manage uncertainty in studentmodeling.User Modeling and User-Adapted Interaction, 12(4):371–417,2002.

Vania Dimitrova.Style-olm: Interactive open learner modelling.International Journal of Artificial Intelligence in Education,13(1):35–78, January 2003.

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Referencias

David Thomson and Antonija Mitrovic.Preliminary evaluation of a negotiable student model in aconstraint-based its.Research and Practice in Technology Enhanced Learning,5(1):19–33, 2010.

Juan-Diego Zapata-Rivera and Jim E. Greer.Interacting with inspectable bayesian student models.International Journal of Artificial Intelligence in Education,14(2):127–163, 2004.

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Thanks!!

E. Costa, P. Silva, J. Magalhaes and M. Silva PALE UMAP 2012 20

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For more information: http://tip.ic.ufal.br/site/

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