Cognitive Reasoning to Respond

Affectively to the StudentPatrícia A. Jaques

Magda Bercht

Rosa M. Vicari

UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL BRASIL

Overview

• Context– Background and Motivation

• Bercht´s work• Jaques’ work• Conclusion

Education

Computer Science

Psychology andCognitive Science

Context - Background and Motivation

Multidisciplinary Area

Intelligent Tutoring Systems

programs that

adopt teaching

strategies in

accordance with

the student’s

model that was

built based on

the interaction

with the student

[Vicari, 92].

Context - Background and Motivation

Pedagogical Agents:

•educational system (ITS) implemented using the agent paradigm;

• a software agent is an entity that functions independently and continuously in a particular environment that is always inhabited by other agents and processes.

These agents can be modelled as:

(1) co-operative/ competitive software entities that work in one background as part of the architecture of the educational system, or as;

(2) personal and animated characters that interact with the user.

Context - Background and Motivation

Affectivity , Emotions :

Why:

•The affectivity is the motor of the intellectual activity.

Energy [Piaget,89].

• Vygotsky considers the unit between the intellectual, evolutive and affective processes [Vygotsky, 78].

Theoretical basis:

•Cognitive Approach of Emotions:•Emotions require cognitive processes to generate or to retrieve preferences or meaning. •They are activated by an individual’s interpretations in relation to the pleasant or disappointing aspects of an event.

OCC Model

OCC Model.

Emotions are elicited on the person’s subjective evaluation

(appraisal) of a situation, event or object

Context - Background and Motivation

Agents and Mental States BDI ( Beliefs, Desires, Intentions )

Desires

Beliefs

Intentionsbasic mental states to model agents according to intentional approach to describe and preview behaviour [Bratman,89]

Software tool:

X-BDI by Michael Móra [Móra, 2000] to specify and

develop cognitive agents

Context - Background and Motivation

BDI Architecture : why ?

• The mentalistic approach is appropriate because we follow the cognitive approach of emotion [Ortony,CloreCollins, 1999] [Scherer, 1999] .

• According to cognitive approach of emotion :Emotions are elicited by a cognitive evaluation that a person

makes about the personal significance of an agent, object or action.

• The implementation of the pedagogical agent using BDI makes possible to verify, in a simple manner, the relationship among the tutor’s actions and the mental states inferred about the student.

Bercht’s work

• It approaches part of the human emotional-intellectual

process involved in a teaching and learning situation

• Development of a student model that takes into account

factors that build emotions developed in a situation of

interaction with educational computing systems

• Implementation of an affective student model using BDI

approach

Student ModelPERCEPTION

INTERFACE

Intellectual Schema

Affective Schema

Actions

Kernel

GlobalState

ofStudent

Environment

Bercht’s works

Building the Student Model

• The student’s affectivity is inferred by his instrumental observable behaviour and stored as beliefs the tutor has about the student

• The first version of the prototype constructs a representation of the student by two dimensions: affective and intellectual

• The affective dimension is modelled :

– by considering the student’s motivation on three factors: effort (E), independence ( I) and confidence (C), and

– by considering the student’s dislike emotion inferred according to the OCC theory.

Berth's work

Components factors of Motivation

Situation Type of help Confidence

None respond Asks for help -1

correct With help +1

correct Without help +2

Wrong Without help -1

Wrong With help -2

Confidence

Model

State of Help Type of Help Independence

Suggested - -1

Given Generic -1

Given Specific -2

Not used - +1

Denied - +1

Rejected - +2

Independence Model

Components factors of Motivation

State of Task Steps Help Effort

Give up None - None

Give up Few With help Minimum

Give up Few Without help Short

Realized Few With help Short

Realized Few Without help Medium

Give up Many With help Medium

Give up Many Without help Big

Realized Many With help Big

Realized Many Without help Maximum

Effort Model

bel(tutor, mean_student_performance(7))).bel(tutor, student_confidence(7)).bel(tutor, student_independence(4)). bel(tutor, student_effort(mean)).bel(tutor, student_dislike(4)).

des(tutor, encourage_independence).

(1) (not_put_help_available (Y) , send_message(X)) causes

(bel(tutor, encourage_indep) , bel(tutor, displease_student(N))) if

bel(tutor, indicator_development(wait)),

(2) bel(tutor, student_asks_help (Y, X)) ,

bel(tutor, ind_affective(encourage_independence)),

bel(tutor, displease_student(N1)), N is N1 + 1.

Bercht’s work tutor agent´s kernel in operation

Tutor beliefs about the student after time observation

Candidate desire to current tutor´s intention

Actions taken if triggers (2) becomes concrete

Belief about student´s dislike

• An animated pedagogical tutor that aims at promoting a positive mood in the student more ideal to learning.

• It catches the student's affective state, by his observable behaviour, and applies tactics in accordance with student's affectivity, i. e., promotes actions that aim to adequate the system to the student's affective state.

Jaques’s work

Jaques’ works

Identifying Student’s Emotions

• Mediating Agent catches the student’s emotions by his observable behaviour and has an affective model to store this information. We chose this method because it seems the most natural way for the student to interact with the educational system.

• Which emotions?– Satisfaction and Disappointment

• based on OCC model– Motivation:

• based on Bercht’s work.

Jaques’ work

How to recognise satisfaction and disappointment emotions?

• The OCC model considers that emotions of satisfaction and disappointment are elicited when events of the world are appraised according to their desirability with respect to the user’s goals.

• To determine the student’s emotions:

– Define student’s goals;– Determine events that happens in the

educational environment;

– Define if this events are desirable or undesirable according to student´s goals.

• Events:

– performance in exercises

– tutor’s feedback

• All events in the system will be evaluated according to its desirability in function of student’s goals.

Jaques’ work

Tutor Beliefs about student’s emotions

bel (tutor, student_goal (rewards))

bel (tutor, event (task_not_accomplished))

bel (tutor, event (task_not_accomplished, undesirable)) if

bel (tutor, student_goal (rewards))

bel (tutor, student_emotion(disappointment)) if

(event (x, undesirable));

Tutor knows student´s goal: obtain rewards

Event: student didn’t accomplished the task

Tutor knows that the event is undesirable for

student

Tutor knows that students is disappointed when event

is undesirable

Emotion = Disappointment

Jaques’ work

Definition of Pedagogical Tactics

• Domain tactics:

– Tactics for performance and competence that are handled by another agent of the tutoring system;

• Affective tactics:

– (1) pedagogical tactics to motivate and encourage the student or

– (2) emotional behaviour to promote the student's positive mood, more appropriate to learning.

Work in progress

Conclusions obtained benefits

Multi-agent approach:

In the case of Bercht’s and Jaques´ works, the agent responsible for considering the student’s affectivity are inserted in a multi-agent environment where it interacts with other agents responsible for the whole interaction with the student.

Mentalistic Approach:

It allows easy revision and frequent modification of the student's information [5]. The student's model is built in a dynamic way from each interaction in real time [8].

The tutor built as a cognitive agent with mental attitudes can reason about the student’s appraisal according to OCC model in order to infer his affective states, as well as deciding the best (affective and intellectual) pedagogical tactics to be applied.

Conclusions obtained benefits

Student model based on affective and intellectual dimensions

enable a more precise description from a student’s qualitative

point of view. It makes possible that the student is represented by

values other than performance or based on statistic profiles;

The approach of part of the human intellectual-emotional process

involved in a learning situation. It makes possible to develop

studies that aim at understanding this process. Results and

research may serve Psychology, in special Psychopedagogy.