Abstract
We investigate the utility of an eye tracker for providing information on users’ affect and reasoning. To do so, we conducted a user study, results from which show that users’ pupillary responses differ significantly between positive and negative affective states. As far as reasoning is concerned, while our analysis shows that larger pupil size is associated with more constructive reasoning events, it also suggests that to disambiguate between different kinds of reasoning, additional information may be needed. Our results show that pupillary response is a promising non-invasive avenue for increasing user model bandwidth.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
VanLehn, K.: Student modeling. Foundations of Intelligent Tutoring Systems, 55–78 (1988)
Klein, J., Moon, Y.: This computer responds to user frustration: Theory, design, results, and implications. Interacting with Computers 14, 119–140 (2000)
Aleven, V., Koedinger, R.: An effective metacognitive strategy: learning by doing and explaining with a computer-based cognitive tutor. Cognitive Science 26(2), 147–179 (2002)
D’Mello, S.K., Picard, R.W., Graesser, A.C.: Towards an affect-sensitive autotutor. IEEE Intelligent Systems 22(4), 53–61 (2007)
Burleson, W.: Affective Learning Companions: Strategies for Empathetic Agents with Real-Time Multimodal Affective Sensing to Foster Meta-Cognitive Approaches to Learning, Motivation, and Perseverance. Ph.D thesis, MIT (2006)
Gluck, K., Anderson, J.: Cognitive architectures play in intelligent tutoring systems? In: Cognition and Instruction: Twenty-Five Years of Progress, pp. 227–262 (2001)
Qu, L., Johnson, L.: Detecting the learner’s motivational states in an interactive learning environment. In: 12th International Conference on Artificial Intelligence in Education, pp. 547–554 (2005)
Conati, C., Merten, C.: Eye-tracking for user modeling in exploratory learning environments: an empirical evaluation. Knowledge Based Systems 20(6), 557–574 (2007)
Chi, M., Basssok, M., Lewis, M., Reimann, P., Glaser, R.: Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science 13, 145–182 (1989)
Marshall, S.P.: Identifying cognitive state from eye metrics. Aviation, Space, and Environmental Medicine 78, 165–175 (2007)
Van Gerven, P.W.M., Paas, F., Van Merrinboer, J.J.G., Schmidt, H.G.: Memory load and the cognitive pupillary response in aging. Psychophysiology 41(2), 167–174 (2004)
Vo, M.L.H., Jacobs, A.M., Kuchinke, L., Hofmann, M., Conrad, M., Schacht, A., Hutzler, F.: The coupling of emotion and cognition in the eye: Introducing the pupil old/new effect. Psychophysiology 45(1), 130–140 (2008)
Partala, T., Surakka, V.: Pupil size variation as an indication of affective processing. Int. Journal of Human-Computer Studies 59(1-2), 185–198 (2003)
Iqbal, S., Zheng, X., Bailey, B.P.: Task-evoked pupillary response to mental workload in human-computer interaction. In: CHI 2004 extended abstracts on Human factors in computing systems, pp. 1477–1480 (2004)
Schultheis, H., Jameson, A.: Load in adaptive hypermedia systems: Physiological and behavioral methods. In: Adaptive hypermedia. Interacting with Computers, pp. 225–234 (2004)
Conati, C., Muldner, K., Carenini, G.: From example studying to problem solving via tailored computer-based meta-cognitive scaffolding: Hypotheses and design. Technology, Instruction, Cognition and Learning (TICL) 4(2), 139–190 (2006)
Muldner, K., Conati, C.: Evaluating a decision-theoretic approach to tailored example selection. In: IJCAI 2007, 20th International Joint Conference in Artificial Intelligence, pp. 483–488 (2007)
VanLehn, K.: Analogy events: How examples are used during problem solving. Cognitive Science 22(3), 347–388 (1998)
VanLehn, K.: Rule-learning events in the acquisition of a complex skill: An evaluation of cascade. The Journal of the Learning Sciences 1(8), 71–125 (1999)
Muldner, K.: Tailored Support for Analogical Problem Solving. Ph.D thesis, University of British Columbia (2007)
Dragon, T., Arroyo, I., Woolf, B.P., Burleson, W., el Kaliouby, R., Eydgahi, H.: Viewing Student Affect and Learning through Classroom Observation and Physical Sensors. In: Woolf, B.P., Aïmeur, E., Nkambou, R., Lajoie, S. (eds.) ITS 2008. LNCS, vol. 5091, pp. 29–39. Springer, Heidelberg (2008)
Ercisson, K., Simmon, H.: Verbal reports as data. Psychological Review 87(3), 215–250 (1980)
Craig, S., D’Mello, S., Witherspoon, A., Graesser, A.: Emote aloud during learning with autotutor: Applying the facial action coding system to cognitive-affective states during learning. Cognition and Emotion 22(5), 777–788 (2008)
Van Gerven, P., Paas, F., Van Merrienboer, J., Schmidt, H.: Memory load and the cognitive pupillary response in aging. Psychophysiology 41(2), 167–174 (2001)
Cardinal, R., Aitken, M.: ANOVA for the Behavioural Sciences Researcher. Routledge, London (2006)
Mauss, I., Robinson, M.: Measures of emotion: A review. Cognition & Emotion 23(2), 209–237 (in press)
Levens, S., Phelps, E.: Emotion processing effects on interference resolution in working memory. Emotion 8(2), 267–280 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Muldner, K., Christopherson, R., Atkinson, R., Burleson, W. (2009). Investigating the Utility of Eye-Tracking Information on Affect and Reasoning for User Modeling. In: Houben, GJ., McCalla, G., Pianesi, F., Zancanaro, M. (eds) User Modeling, Adaptation, and Personalization. UMAP 2009. Lecture Notes in Computer Science, vol 5535. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02247-0_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-02247-0_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02246-3
Online ISBN: 978-3-642-02247-0
eBook Packages: Computer ScienceComputer Science (R0)