AUTOMATIC DETECTION OF LEARNER'S AFFECT FROM GROSS BODY LANGUAGE

REFERENCES

• Aist , G. , B. Kort , R. Reilly , R.W. Picard , and J. Mostow . 2002 . Experimentally augmenting an intelligent tutoring system with human supplied capabilities: Adding human-provided emotional scaffolding to an automated reading tutor that listens . In: Proceedings of the 6th International Conference on Intelligent Tutoring Systems (ITS2002) , Biarritz, France and San Sebastian, Spain, June 2–7, 2002 .
   Google Scholar
• Ang , J. , R. Dhillon , A. Krupski , E. Shriberg , and A. Stolcke . 2002. Prosody-based automatic detection of annoyance and frustration in human-computer dialog. In: Proceedings of the International Conference on Spoken Language Processing 2037–2039.
   Google Scholar
• Barrett , L. F. 2006 . Are emotions natural kinds? Perspectives on Psychological Science 1 : 28 – 58 .
   Web of Science ®Google Scholar
• Bernstein , N. 1967 . The Co-Ordination and Regulation of Movement . London : Pergamon Press .
   Google Scholar
• Bianchi-Berthouze , N. and C. L. Lisetti . 2002 . Modeling multimodal expression of users affective subjective experience . User Modeling and User-Adapted Interaction 12 ( 1 ): 49 – 84 .
   Google Scholar
• Bianchi-Berthouze , N. , P. Cairns , A. Cox , C. Jennett , and W. Kim . 2006 . On posture as a modality for expressing and recognizing emotions . In: Emotion and HCI Workshop , British Computer Society HCI September 12, 2006, London .
   Google Scholar
• Bull , E. P. 1987 . Posture and Gesture . Pergamon Press : Oxford .
   Google Scholar
• Campbell , D. T. and D. W. Fiske . 1959 . Convergent And discriminant validation by the multitrait-multimethod matrix . Psychological Bulletin 56 : 81 – 105 .
   PubMed Web of Science ®Google Scholar
• Cohen , J. 1960 . A coefficient of agreement for nominal scales . Educational and Psychological Measurement 20 : 37 – 46 .
   Web of Science ®Google Scholar
• Conati , C. 2002 . Probabilistic assessment of user's emotions in educational games . Journal of Applied Artificial Intelligence 16 : 555 – 575 .
   Web of Science ®Google Scholar
• Coulson , M. 2004 . Attributing emotion to static body postures: Recognition accuracy, confusions, and viewpoint dependence . Journal of Nonverbal Behavior 28 : 117 – 139 .
   Web of Science ®Google Scholar
• Craig , S. D. , A. C. Graesser , J. Sullins , and B. Gholson . 2004 . Affect and learning: An exploratory look into the role of affect in learning . Journal of Educational Media 29 : 241 – 250 .
   Google Scholar
• de Meijer , M. 1989 . The contribution of general features of body movement to the attribution of emotions . Journal of Nonverbal Behavior 13 : 247 – 268 .
   Web of Science ®Google Scholar
• Dempster , A. P. , N. M. Laird , and D. B. Rubin . 1977 . Maximum Likelihood from incomplete data via the EM algorithm . Journal of the Royal Statistical Society 39 : 1 – 38 .
   Google Scholar
• de Rosis , F. 2002 . Toward merging cognition and affect in HCI . Applied Artificial Intelligence 16 : 487 – 494 .
   Web of Science ®Google Scholar
• De Vicente , A. and H. Pain . 2002 . Informing the detection of students' motivational state: An empirical study . In: Proceedings of the 6th International Conference on Intelligent Tutoring Systems (ITS2002) , Biarritz, France and San Sebastian, Spain, June 2–7, 2002 .
   Google Scholar
• D'Mello , S. K. , S. D. Craig , B. Gholson , S. Franklin , R. Picard , and A. C. Graesser . 2005 . Integrating affect sensors in an intelligent tutoring system. Affective interactions: The computer . In: The Affective Loop Workshop at the 2005 International Conference on Intelligent User Interfaces . New York : AMC Press .
   Google Scholar
• D'Mello , S. K. , S. D. Craig , J. Sullins , and A. C. Graesser . 2006 . Predicting affective states through an emote-aloud procedure from autotutor's mixed-initiative dialogue . International Journal of Artificial Intelligence in Education 16 : 3 – 28 .
   Google Scholar
• D'Mello , S. K. , R. Picard , and A. C. Graesser . 2007 . Towards an affect sensitive autotutor . IEEE Intelligent Systems 22 : 53 – 61 .
   Web of Science ®Google Scholar
• Dweck , C. S. 2002 . Messages that motivate: How praise molds students' beliefs, motivation, and performance (in surprising ways) . In: Improving Academic Achievement: Impact of Psychological Factors on Education , ed. J. Aronson , pp. 61 – 87 . Orlando , FL : Academic Press .
   Google Scholar
• Ekman , P. and W. V. Friesen . 1969 . Nonverbal leakage and clues to deception . Psychiatry 32 : 88 – 105 .
   PubMed Web of Science ®Google Scholar
• Ekman , P. and W. V. Friesen . 1978 . The Facial Action Coding System: A Technique for the Measurement of Facial Movement . Palo Alto , CA : Consulting Psychologists Press .
   Google Scholar
• Graesser , A. C. , S. Lu , G. T. Jackson , H. Mitchell , M. Ventura , A. Olney , and M. M. Louwerse . 2004 . AutoTutor: A tutor with dialogue in natural language . Behavioral Research Methods, Instruments, and Computers 36 : 180 – 193 .
   PubMedGoogle Scholar
• Graesser , A. C. , B. McDaniel , P. Chipman , A. Witherspoon , S. D'Mello , and B. Gholson . 2006 . Detection of emotions during learning with autotutor . In: Proceedings of the 28th Annual Conference of the Cognitive Science Society . Mahwah , NJ : Erlbaum .
   Google Scholar
• Graesser , A. C. , N. Person , D. Harter , and Tutoring Research Group . 2001 . Teaching tactics and dialogue in reply to: AutoTutor . International Journal of Artificial Intelligence in Education 12 : 257 – 279 .
   Google Scholar
• Grimm , M. , E. Mower , K. Kroschel , and S. Narayan . 2006. Combining categorical and primitives-based emotion recognition. In: 14th European Signal Processing Conference (EUSIPCO), September 4-8, 2008, Florence, Italy.
   Google Scholar
• Kim , Y. 2005 . Empathetic virtual peers enhanced learner interest and self-efficacy . In: Workshop on Motivation and Affect in Educational Software at the 12th International Conference on Artificial Intelligence in Education , July 18–22, 2005 , Amsterdam , the Netherlands .
   Google Scholar
• Klein , J. , Y. Moon , and R. Picard . 2002 . This computer responds to user frustration – Theory, design, and results . Interacting with Computers 14 : 19 – 140 .
   Google Scholar
• Kort , B. , R. Reilly , and R. Picard . 2001 . An affective model of interplay between emotions and learning: reengineering educational pedagogy building a learning companion . In: Proceedings IEEE International Conference on Advanced Learning Technology: Issues, Achievements and Challenges , Madison , WI , pp. 43 – 48 .
   Google Scholar
• Linnenbrink , E. A. and P. Pintrich . 2002 . The role of motivational beliefs in conceptual change . In: Reconsidering Conceptual Change: Issues in Theory and Practice , eds. M. Limon and L. Mason . Dordrecht , the Netherlands : Kluwer Academic Publishers .
   Google Scholar
• Liscombe , J. , G. Riccardi , and D. Hakkani-Tür . 2005 . Using context to improve emotion detection in Spoken dialog systems . In: EUROSPEECH'05, 9th European Conference on Speech Communication and Technology , Lisbon , Portugal .
   Google Scholar
• Lisetti , C. L. and P. Gmytrasiewicz . 2002 . Can a rational agent afford to be affectless? A formal approach . Applied Artificial Intelligence, An International Journal 16 : 577 – 609 .
   Web of Science ®Google Scholar
• Litman , D. J. and K. Forbes-Riley . 2004 . Predicting student emotions in computer-human tutoring dialogues . In: Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics . East Stroudsburg , PA : Association for Computational Linguistics .
   Google Scholar
• Mandler , G. 1984 . Mind and Body: Psychology of Emotion and Stress . New York : Norton .
   Google Scholar
• Matsubara , Y. and M. Nagamachi . 1996 . Motivation systems and motivation models for intelligent tutoring . In: Proceedings of the Third International Conference in Intelligent Tutoring Systems , June 12–14, 1996 , Montreal , Canada .
   Google Scholar
• Mehrabian , A. 1972 . Nonverbal Communication . Chicago , IL : Aldine-Atherton .
   Google Scholar
• Montepare , J. , E. Koff , D. Zaitchik , and M. Albert . 1999 . The use of body movements and gestures as cues to emotions in younger and older adults . Journal of Nonverbal Behavior 23 : 133 – 152 .
   Web of Science ®Google Scholar
• Morimoto , C. , D. Koons , A. Amir , and M. Flickner . 1998 . Pupil detection and tracking using multiple light sources . Technical Report , IBM, Almaden Research Center , San Francisco , CA , USA .
   Google Scholar
• Mota , S. and R. W. Picard . 2003 . Automated posture analysis for detecting learner's interest level . In: Workshop on Computer Vision and Pattern Recognition for Human-Computer Interaction (CVPR HCI), June 16–22, 2003, Madison, WI, USA .
   Google Scholar
• Norman , D. A. 1994 . How might people interact with agents? Communication of the ACM 37 : 68 – 71 .
   Web of Science ®Google Scholar
• Paiva , A. , R. Prada , and R. W. Picard . (eds.). 2007 . Affective Computing and Intelligent Interaction . Springer .
   Google Scholar
• Pantic , M. and L. J. M. Rothkrantz . 2003 . Towards an affect-sensitive multimodal human-computer interaction . In: Proceedings of the IEEE, Special Issue on Multimodal Human-Computer Interaction (HCI) 91 ( 9 ): 1370 – 1390 .
   Web of Science ®Google Scholar
• Picard , R. W. 1997 . Affective Computing . Boston , MA : MIT Press .
   Google Scholar
• Picard , R. W. , E. Vyzas , and J. Healey . 2001 . Toward machine emotional intelligence: Analysis of affective physiological state . IEEE Transactions Pattern Analysis and Machine Intelligence 23 : 1175 – 1191 .
   Web of Science ®Google Scholar
• Prendinger , H. and M. Ishizuka . 2005 . The empathic companion: A character-based interface that addresses users' affective states . International Journal of Applied Artificial Intelligence 19 : 267 – 285 .
   Web of Science ®Google Scholar
• Rani , P. , N. Sarkar , and C. A. Smith . 2003 . An affect-sensitive human-robot cooperation – Theory and experiments . In: Proceedings of the IEEE Conference on Robotics and Automation . Taipei , Taiwan : IEEE , pp. 2382 – 2387 .
   Google Scholar
• Robson , C. 1993 . Real Word Research: A Resource for Social Scientist and Practitioner Researchers . Oxford : Blackwell .
   Google Scholar
• Selfridge , O. G. 1959 . Pandemonium: A paradigm for learning . In: Symposium on the Mechanization of Thought Processes . London : Her Majesty's Stationary Office , pp. 511 – 531 .
   Google Scholar
• Shafran , I. , M. Riley , and M. Mohri . 2003 . Voice signatures . In: Proceedings IEEE Automatic Speech Recognition and Understanding Workshop , Piscataway , NJ : IEEE , pp. 31 – 36 .
   Google Scholar
• Shneiderman , B. and C. Plaisant . 2005. Designing the User Interface: Strategies for Effective Human-Computer Interaction. , 4th ed.Reading , MA : Addison-Wesley.
   Google Scholar
• Tan , H. Z. , I. Lu , and A. Pentland . 1997 . The chair as a novel haptic user interface . In: Proc. Workshop of Perceptual User Interface , pp. 56 – 57 .
   Google Scholar
• Tekscan . 1997 . Tekscan Body Pressure Measurement System User's Manual . South Boston , MA : Tekscan Inc .
   Google Scholar
• VanLehn , K. , A. C. Graesser , G. T. Jackson , P. Jordan , A. Olney , and C. P. Rose . 2007 . When are tutorial dialogues more effective than reading? Cognitive Science 31 : 3 – 62 .
   PubMed Web of Science ®Google Scholar
• Walk , R. D. and K. L. Walters . 1988 . Perception of the smile and other emotions of the body and face at different distances . Bulletin of the Psychonomic Society 26 : 510 – 510 .
   Google Scholar
• Whang , M. C. , J. S. Lim , and W. Boucsein . 2003 . Preparing computers for affective communication: A psychophysiological concept and preliminary results . Human Factors 45 : 623 – 634 .
   PubMedGoogle Scholar
• Witten , I. H. and E. Frank . 2005 . Data Mining: Practical Machine Learning Tools and Techniques. , 2nd ed. San Francisco , CA : Morgan Kaufmann .
   Google Scholar