2. Cognitive Reasoning to Respond Affectively to the Student Patrícia A. Jaques Magda Bercht Rosa M. Vicari UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL BRASIL

3. Overview Context –Background and Motivation Bercht´s work Jaques’ work Conclusion

4. Education Computer Science Psychology and Cognitive 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].

5. 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.

6. 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

7. . Emotions are elicited on the person’s subjective evaluation (appraisal) of a situation, event or object

8. Context - Background and Motivation Agents and Mental States BDI ( Beliefs, Desires, Intentions ) Desires Beliefs Intentions basic 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

9. 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.

10. 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

11. Student Model PERCEPTIONPERCEPTION INTERFACEINTERFACE Intellectual Schema Affective Schema Actions Kernel Global State of Student Environment

12. 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.

13. Berth's work

14. Components factors of Motivation Confidence Model Independence Model

15. Components factors of Motivation Effort Model

16. 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

17. 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

18. 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.

19. 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.

20. 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

21. 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

22. 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.

23. 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.