emotion in animated pedagogical agents performing as virtual social actors

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Page 1: Emotion in Animated Pedagogical Agents Performing as Virtual Social Actors
Page 2: Emotion in Animated Pedagogical Agents Performing as Virtual Social Actors

Outline of Presentation

• Introduction to Animated Pedagogical Agents • Perceptual User Interface Design • Emotionality Expressive Pedagogical Agents • Conclusions and Future Considerations • Acknowledgements • References

Presenter
Presentation Notes
The presentation today will have the following outline: First, I will provide a brief overview on animated pedagogical agents including their definition, characteristics as interface agents and character building qualities. These will be follow by the a synopsis on perceptual user interface design explain the connection between this type of interface design and to the design and development of animated pedagogical agents. These topic will lead us to the design of emotionally expressive agents. With special consideration for facial expression of emotions followed by the integration of the Face Reader software for a possible adaptive animated pedagogical agent – user interaction. Then I will take you through my final remarks, future research considerations and references.
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Introduction

What is an animated pedagogical agent?

Presenter
Presentation Notes
To this start this presentation I think is important to point out what is the purpose of this presentation…in one single sentence…the purpose is to present a strategy that could assist in the design and development of emotionally expressive animated pedagogical agents performing as virtual actors in interactive instructional environments. Now you might ask yourself what exactly are animated pedagogical agents? Simply put, in non-instructional environments are call avatars, however life-like computerized characters that facilitate learning in interactive environments are call animated pedagogical agents. These agents create the illusion of human to human interaction. They incorporate intelligent tutoring systems that present intellectual knowledge that can satisfy the information thirst of the learner.
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Characteristics

B. Laurel, “Interface Agents: Metaphors with Character,” in The Art of Human Computer Interface Design, B. Laurel, Ed. Readings, MA: Addison-Wesley Publishing, 1990, pp. 355-365.

•Playing against •Playing with •Performing

•Coaching •Tutoring •Help

•Reminding •Programming •Scheduling •Advising

•Navigation •Browsing

• Informational Retrieval • Sorting

•organization • Filtering

Information Work

Entertaining Learning

Presenter
Presentation Notes
Now, There is a basic construct under which all interface agents must be based. It provides the framework that will later be modified to make the agents more suitable for interactive instructional environments. The first characteristic, and perhaps the most important one, is agency. It is important to give special consideration to this characteristic because it determines the overall function of the agent. Agency refers to the task that the agents might perform on behalf of the user. There are four main agency types: information, work, learning and entertaining. In the case of animated pedagogical agents the main agency types are learning and entertaining.
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Characteristics

Animation Gestures

Communication Personality Emotions

Agency

Responsiveness

Competence

Accessibility

Presenter
Presentation Notes
The second characteristic of an interface agent refers to its responsiveness. �This refers to the ability of the agent to be responsive to the user. These �responses can be explicit or implicit [1]. Explicit responses are those made� based on commands provided by the user, whereas implicit responses� refers to the agent’s ability to adapt its actions based on previous interactions� with the user. In addition to agency and responsiveness, interface agents must be �accessible. This implies that all of the agent’s qualities and tendencies �are available to the user. Another important characteristic of interface agents is �competence. Agents must be competent on the domain of their application �and/or in the task that they will perform.
Page 6: Emotion in Animated Pedagogical Agents Performing as Virtual Social Actors

Character Building Qualities

Herman The Bug

Presenter
Presentation Notes
Now, in order to evolve from simple interface agents to life-like characters, pedagogical agents must additionally have a number of characteristics that, when integrated, provide the illusion that users are interacting with a social intelligent counterpart like another human. These character building qualities are animation, gestures, communication, emotions and personality. An example of an animated pedagogical agent that embeds most of the character building qualities is Herman the Bug. Herman resides within the interactive environment Design-A-Plant. This agent can perform numerous unique animations like running, jumping, walking, flying, shrinking, expanding, swimming, fishing, bungee jumping, teleporting, and other types of animations. Also, as you an see he can point, gaze and provide other types of gestures. He communicates with the learners through speech (audio) and provides the appearance of emotion through a smiley face or neutral expression. Because of his ability to properly combine these character building qualities Herman The Bug is one of the few animated agents that has been experimentally obtain a persona effect meaning that learner perceive it a believable character that is a positive element towards the learning experience. To ensure that character building qualities are applied properly it is strongly advised that the design and development of animated pedagogical agents follows guidelines for the design of perceptual user interfaces.
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Perceptual User Interfaces

B. Reeves and C. Nass, “Perceptual Bandwidth,” Communications of the ACM, vol. 43, no. 3, pp. 65-70, 2000. M. Turk and G. Robertson, “Perceptual User Interfaces,” Communications of ACM, vol. 43, no. 3, pp. 65-70, 2000.

Presenter
Presentation Notes
Perceptual User Interfaces are user interfaces that maximizes the bandwidth of communication between a user and a computer, using multimedia to capitalize on all the user’s senses, and using multiple input modalities as well as perceptive information that allow computers to have human-like qualities so they are aware of what the users’ face, body, and hands are doing. This enables a user experience that is more like the way that people interact with the real world, taking full advantage of human perceptual capabilities. Research on perceptual user interface has focused on the perception of motion, novelty, size and media content, faces (stereotypes) and audio (voices). This research can help improve all the character building qualities of animated pedagogical agents (i.e. animation, gestures, communications, and personality). Investigators of perceptual user interfaces lack extensive knowledge on the development of affective human-computer interaction more specifically affective human-agent interaction in instructional interactive environments.
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Emotionality Expressive Pedagogical Agents

Why integrate emotion in animated pedagogical agents?

Presenter
Presentation Notes
You might wonder why is it important to integrate emotion to human agent interaction? Well, prior research from neuroscience, cognitive science, and psychology indicate that emotions have a critical role in attention, planning, reasoning, learning, memory, and decision making. Additionally, emotions serve as a strong motivator that influences perception, cognition, coping, and creativity. Other researchers have also stated that emotions contribute to quality interactions and that they impact humans’ ability to interact intelligently. Therefore, having engaging, life-like pedagogical agents that can exploit a rich repertoire of emotive behaviors to advise, encourage, and empathize with the learners could have a strong motivating effect on the learning experience. How is it exactly can emotion be integrated into animated agents? Researchers on the theory of emotions for humans have yet to agree on how and when emotions are produced. However, three of the most popular theories of emotion (i.e. attitude or expressive motor theory, body reaction theory, and cognition-arousal theory) agree that in addition to the sensory and neural systems, expressive motor behaviors are critical elements in adding feeling to experience. For pedagogical agents, developers would be unable to recreate the sensory and/or neural components of an emotion system. However, it is possible to enable visual affective behavior that mimics the expressive motor components that humans experience.
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Facial Expression of Emotions

Presenter
Presentation Notes
In humans, visual affective behavior is gather from four specific sources: the face, the tilts of the head, the total body posture, and the skeletal muscle movements of the arms, hands, legs, and feet. However, it has been confirmed that the face provides emotion charged information with far more precision than the rest of the human body because the facial signals send emblematic messages that a non-verbal equivalent of a common word or phrase, in the case of emotions the emblematic message will be a facial representation of how we are feeling in that specific moment. There are arrays of emotional expressions that can be described through words, however investigators have found that the vocabulary of emotions associated with facial expressions can be limited to six major emotions [18]. These emotions are happiness, sadness, surprise, fear, anger, and disgust. Prior research has deciphered enough facial expression information on the previous emotions that it can be effortlessly simulated in facial expressions of pedagogical agents. These include specifics on eyebrow, chin, cheeks, and other facial muscle movements. Of course, believability will not only be reached by integrating facial expressions to the agents. There are rules that should be adhered to when designing an emotionally expressive pedagogical agent. The three main rules are: 1) clearly define the emotional states of the character, 2) show the emotion of the character as it is going through its thought processes because the learner must see the emotions in how the character acts as its “thinking” is influenced by its emotional state, and 3) time the emotions wisely so learners can get a full grasp of the emotional states of the character.
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Technology for Perception of Emotion

Presenter
Presentation Notes
Now, in order to create an adaptive affective interaction is also important for the animated agent to receive emotion information from the learner. One application that could possibly assist in the development of affective interaction is the Noldus Face Reader© which uses facial expressions of the user to detect emotional states. Through a networked camera the face reader collects live video feed of the face of a user. The software uses the video feed to model the face and obtain facial expression information (i.e. cheek muscles, eyebrow muscles, lips). The emotions that can be detected through facial expressions in the Face Reader© are neutral, happy, sad, angry, surprised, scared, and disgusted. In order to develop an emotionally adaptive behavior for the pedagogical agent, it is proposed that data from the Face Reader© application is synchronized to the interactive learning environment in which the pedagogical agent resides. Consequently, as the user interacts with the emotionally expressive pedagogical agent the Face Reader© can sync information to the interactive learning environment and the agent can modify its emotion based on the perceptual data received from the user. This leads to the creation of a loop of information exchange between the Face Reader© application and instructional interactive environment.
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Conclusions and Future Research

Presenter
Presentation Notes
In conclusion, I have presented an initial intellectual framework that could assist in the development of more natural affective interaction between animated pedagogical agents and learners. First, the design and development of animated agents should follow guidelines from the design or perceptual interface design, 2nd animated agent should provide the appearance of emotion through the integration of facial expressions, special considerations should be given to the six more commonly use facial expressions, designers must ensure proper design rules are follow when integrating facial expressions and last, the face reader could possibly serve as a tool for an adaptive affective avatar-learner interaction. Two recommendations for future research is the experimental validation of facial expression on animated agents to understand how this could affect the learning experience and perhaps learner’s level of performance, engagement and sense of realism. Another recommendation for future research is testing of the integration of data from a Face Reader software to the emotional behavior of the pedagogical agent for an adaptive affective interaction. And my last recommendation is the validation of the face reader emotion readings to ensure accuracy of the information provided.
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Conclusions and Future Research

Six commonly recognized

facial expressions

Perceptual User Interface

Design

Integration of facial

expressions

Presenter
Presentation Notes
In conclusion, I have presented an initial intellectual framework that could assist in the development of more natural affective interaction between animated pedagogical agents and learners. First, the design and development of animated agents should follow guidelines from the design or perceptual interface design, 2nd animated agent should provide the appearance of emotion through the integration of facial expressions, special considerations should be given to the six more commonly use facial expressions, designers must ensure proper design rules are follow when integrating facial expressions and last, the face reader could possibly serve as a tool for an adaptive affective avatar-learner interaction. Three recommendations for future research is the experimental validation of facial expression on animated agents to understand how this could affect the learning experience and perhaps learner’s level of performance, engagement and sense of realism. Another recommendation for future research is testing of the integration of data from a Face Reader software to the emotional behavior of the pedagogical agent for an adaptive affective interaction. And my last recommendation is the validation of the face reader emotion readings to ensure accuracy of the information provided.
Page 13: Emotion in Animated Pedagogical Agents Performing as Virtual Social Actors

Conclusions and Future Research

Six commonly recognized

facial expressions

Experimental investigation

Validation of Face Reader

readings

Perceptual User Interface

Design

Integration of facial

expressions

Integration of Face Reader

to behavioral space

Presenter
Presentation Notes
In conclusion, I have presented an initial intellectual framework that could assist in the development of more natural affective interaction between animated pedagogical agents and learners. First, the design and development of animated agents should follow guidelines from the design or perceptual interface design, 2nd animated agent should provide the appearance of emotion through the integration of facial expressions, special considerations should be given to the six more commonly use facial expressions, designers must ensure proper design rules are follow when integrating facial expressions and last, the face reader could possibly serve as a tool for an adaptive affective avatar-learner interaction. Three recommendations for future research is the experimental validation of facial expression on animated agents to understand how this could affect the learning experience and perhaps learner’s level of performance, engagement and sense of realism. Another recommendation for future research is testing of the integration of data from a Face Reader software to the emotional behavior of the pedagogical agent for an adaptive affective interaction. And my last recommendation is the validation of the face reader emotion readings to ensure accuracy of the information provided.
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Acknowledgements

Special thanks to:

A2-T2 and the Traumatic Brain Injury & Hearing Rehabilitation Team for sharing

access to the Noldus Face Reader® application

Presenter
Presentation Notes
Special thanks to a2-t2 for sharing access to the Noldus Face Reader application.
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References [1] B. Laurel, “Interface Agents: Metaphors with Character,” in The Art

of Human Computer Interface Design, B. Laurel, Ed. Readings, MA: Addison-Wesley Publishing, 1990, pp. 355-365.

[2] C.E. Heckman and J.O. Wobbrock, “Put Your Best Face Forward: Anthropomorphic Agents, E-Commerce Consumers, and the Law,” in Proceedings of the Fourth International Conference on Autonomous Agents, 2000, pp. 435-442.

[3] B. Reeves and C. Nass, “Perceptual Bandwidth,” Communications of the ACM, vol. 43, no. 3, pp. 65-70, 2000.

[4] M. Turk and G. Robertson, “Perceptual User Interfaces,” Communications of ACM, vol. 43, no. 3, pp. 65-70, 2000.

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References [5] Y. Kim, A.L. Baylor and E. Shen, “Pedagogical Agents as Learning

Companions: The Impact of Agent Emotion and Gender,” Journal of Computer Assisted Learning, vol. 23, pp. 220-234, 2007.

[6] S.D. Craig, B. Gholson and D.M. Driscoll, “Animated Pedagogical Agents in Multimedia Educational Environments: Effects of Agent Properties, Picture Features, and Redundancy,” Journal of Educational Psychology, vol. 94, no. 2, pp. 428-434, 2002.

[7] L. Johnson, E. Shaw and R. Ganeshan (1998) Pedagogical Agent on the Web. Available: http://www.isi.edu/isd/ADE/papers/its98/ITS98-WW.htm

[8] W. L. Johnson, J.W. Rickel, and J.C. Lester, “Animated Pedagogical Agents: Face-to-Face Interaction in Interactive Learning Environments.” International Journal of Artificial Intelligence in Education, vol. 11, 47-78, 2000.

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References [9] A.B. Adcock, M.H. Duggan, E.K. Nelson and C. Nickel, “Teaching

Effective Helping Skills at a Distance: The Development of Project CATHIE,” The Quarterly Review of Distance Education, vol. 7, no. 4, pp. 349-360, 2006.

[10] T.W. Bickmore and R.W. Picard, “Establishing and Maintaining Long-term Human Computer Relationships,” ACM Transaction of Computer-Human Interaction, 12(2), 293-327.

[11] J.C. Lester, S.A. Converse, S.E. Kahler, S.T. Barlow, B.A. Stone and R.S. Bhogal, “The Persona Effect: Affective Impact of Animated Pedagogical Agents,” in Proceedings of 1997 Conference on Human Factors in Computing Systems, 1997.

[12] R.K. Atkinson, “Optimizing Learning from Examples Using Animated Pedagogical Agents,” Journal of Educational Psychology, vol. 94, no. 2, pp. 416-427, 2002.

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References [13] B. Reeves and C. Nass, The Media Equation: How People

Treat Computers, Television, and New Media Like People and Places. New York: Cambridge University Press, 1996.

[14] J. Bates, “The Role of Emotions in Believable Agents,” Communications of ACM, vol. 37, no. 7, pp. 122-125, 1994.

[15] R.W. Picard, Affective Computing. Cambridge, MA: Addison-Wesley Publishing.

[16] P. Ekman, Emotions Revealed. New York, NY: Holts Paperbacks. 2007.

[17] H. Leventhal, “A Perceptual-Motor Processing Model of Emotion,” in Perception of Emotions in Self and Others, vol. 5, P. Pliner, K.R. Blankstein and I.M. Spinel, Ed. New York: Plenum.

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References [18] P. Ekman and W.V. Friesen, Unmasking the Face: A Guide to Recognizing

Emotions from Facial Expressions. Cambridge, MA: Malor Books, 2003. [19] F. Thomas ad O. Johnson, Disney Animation: The Illusion of Life.

New York: Abbeville Press, 1981. [20] B.E. Barbat and R. Cretulscu., “Affordable Affective Avatars:

Persuasion, Emotions and Language,” in Proceedings of the First Balkan Conference in Informatics, 2003.

[21] J.C. Lester, S.G. Towns and P.J. Fitzgerald, “Achieving Affective Impact: Visual Emotive Communication in Lifelike Pedagogical Agent.” International Journal of Artificial Intelligence in Education, vol. 10, 278-291, 1999.

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Questions, comments and/or suggestions?

For more information: [email protected]

Presenter
Presentation Notes
Questions, comments or suggestions?