Giving Eyesight to the Blind: Towards Attention-Aware AIED

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• 作者：Sidney K. D'Mello
• 关键词：Attentional computing ; Attentional awareness ; Attention ; aware learning ; Eye tracking ; Mind wandering
• 刊名：International Journal of Artificial Intelligence in Education
• 出版年：2016
• 出版时间：June 2016
• 年：2016
• 卷：26
• 期：2
• 页码：645-659
• 全文大小：458 KB
• 参考文献：Anderson, J. R. (2002). Spanning seven orders of magnitude: a challenge for cognitive modeling. Cognitive Science, 26(1), 85–112.CrossRef
  Baker, R., Corbett, A., Koedinger, K., & Wagner, A. (2004). Off-task behavior in the cognitive tutor classroom: When students “game the system”. Proceedings of ACM CHI 2004: Computer-Human Interaction Conference (pp. 383–390). New York: ACM.
  Bixler, R., & D’Mello, S. (2014). Toward fully automated person-independent detection of mind wandering. In V. Dimitrova, T. Kuflik, D. Chin, F. Ricci, P. Dolog, & G.-J. Houben (Eds.), Proceedings of the 22nd International Conference on User Modeling, Adaptation, and Personalization (pp. 37–48). Switzerland: Springer International Publishing.
  Bixler, R., & D’Mello, S. K. (2015). Automatic gaze-based detection of mind wandering with metacognitive awareness. In F. Ricci, K. Bontcheva, O. Conlan, & S. Lawless (Eds.), Proceedings of the 23rd International Conference on User Modeling, Adaptation, and Personalization (UMAP 2015) (pp. 31–43). Switzerland: Springer International Publishing.CrossRef
  Blanchard, N., Bixler, R., & D’Mello, S. K. (2014). Automated physiological-based detection of mind wandering during learning. In S. Trausan-Matu, K. Boyer, M. Crosby, & K. Panourgia (Eds.), Proceedings of the 12th International Conference on Intelligent Tutoring Systems (ITS 2014) (pp. 55–60). Switzerland: Springer International Publishing.
  Bondareva, D., Conati, C., Feyzi-Behnagh, R., Harley, J. M., Azevedo, R., & Bouchet, F. (2013). Inferring learning from gaze data during interaction with an environment to support self-regulated learning. In K. Yacef, C. Lane, J. Mostow, & P. Pavlik (Eds.), Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED 2013) (pp. 229–238). Berlin: Springer.
  Boys, C. V. (1895). Soap bubbles, their colours and the forces which mold them: Society for promoting christian knowledge.
  Bristow, D., Frith, C., & Rees, G. (2005). Two distinct neural effects of blinking on human visual processing. NeuroImage, 27(1), 136–145.CrossRef
  Brockmole, J. R., & Boot, W. R. (2009). Should I stay or should I go? Attentional disengagement from visually unique and unexpected items at fixation. Journal of Experimental Psychology: Human Perception and Performance, 35(3), 808.
  Brockmole, J. R., & Henderson, J. M. (2005). Object appearance, disappearance, and attention prioritization in real-world scenes. Psychonomic Bulletin & Review, 12(6), 1061–1067.CrossRef
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  Cherry, E. C. (1953). Some experiments on the recognition of speech, with one and with two ears. The Journal of the Acoustical Society of America, 25(5), 975–979.CrossRef
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  Conati, C., Aleven, V., & Mitrovic, A. (2013). Eye-tracking for student modelling in intelligent tutoring systems. In R. Sottilare, A. Graesser, X. Hu, & H. Holden (Eds.), Design recommendations for intelligent tutoring systems—Volume 1: Learner modeling (pp. 227–236). Orlando: Army Research Laboratory.
  Currie, C. B., McConkie, G. W., Carlson-Radvansky, L. A., & Irwin, D. E. (2000). The role of the saccade target object in the perception of a visually stable world. Attention, Perception, & Psychophysics, 62(4), 673–683.CrossRef
  D’Mello, S. K., Olney, A. M., Blanchard, N., Samei, B., Sun, X., Ward, B., & Kelly, S. (2015). Multimodal capture of teacher-student interactions for automated dialogic analysis in live classrooms. Paper presented at the Proceedings of the 2015 ACM on International Conference on Multimodal Interaction (ICMI 2015), New York.
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  D'Mello, S., Olney, A., Williams, C., & Hays, P. (2012). Gaze tutor: a gaze-reactive intelligent tutoring system. International Journal of Human-Computer Studies, 70(5), 377–398.CrossRef
  Drummond, J., & Litman, D. (2010). In the zone: Towards detecting student zoning out using supervised machine learning. In V. Aleven, J. Kay, & J. Mostow (Eds.), Intelligent tutoring systems. (Vol. 6095) (pp. 306–308). Berlin: Springer-Verlag.CrossRef
  Egeth, H. E., & Yantis, S. (1997). Visual attention: control, representation, and time course. Annual Review of Psychology, 48(1), 269–297.CrossRef
  Engbert, R., Nuthmann, A., Richter, E. M., & Kliegl, R. (2005). SWIFT: a dynamical model of saccade generation during reading. Psychological Review, 112(4), 777.CrossRef
  Forbes-Riley, K., & Litman, D. (2011). When does disengagement correlate with learning in spoken dialog computer tutoring? In S. Bull & G. Biswas (Eds.), Proceedings of the 15th International Conference on Artificial Intelligence in Education (pp. 81–89). Berlin: Springer.
  Franklin, M. S., Smallwood, J., & Schooler, J. W. (2011). Catching the mind in flight: using behavioral indices to detect mindless reading in real time. Psychonomic Bulletin & Review, 18(5), 992–997.CrossRef
  Gluck, K. A., Anderson, J. R., & Douglass, S. A. (2000). Broader bandwidth in student modeling: What if ITS were “eye” TS? In C. Gauthier, C. Frasson, & K. VanLehn (Eds.), Proceedings of the 5th international conference on intelligent tutoring systems (pp. 504–513). Berlin: Springer.CrossRef
  Graesser, A., Lu, S., Olde, B., Cooper-Pye, E., & Whitten, S. (2005). Question asking and eye tracking during cognitive disequilibrium: comprehending illustrated texts on devices when the devices break down. Memory and Cognition, 33, 1235–1247. doi:10.​3758/​BF03193225 .CrossRef
  Hegarty, M., & Just, M. (1993). Constructing mental models of machines from text and diagrams. Journal of Memory and Language, 32(6), 717–742.CrossRef
  Hoffman, J. E., & Subramaniam, B. (1995). The role of visual attention in saccadic eye movements. Attention, Perception, & Psychophysics, 57(6), 787–795.CrossRef
  Jaques, N., Conati, C., Harley, J. M., & Azevedo, R. (2014). Predicting affect from gaze data during interaction with an intelligent tutoring system. Paper presented at the Intelligent Tutoring Systems.
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  Kardan, S., & Conati, C. (2012). Exploring gaze data for determining user learning with an interactive simulation. In S. Carberry, S. Weibelzahl, A. Micarelli, & G. Semeraro (Eds.), Proceedings of the 20th International Conference on User Modeling, Adaptation, and Personalization (UMAP 2012) (pp. 126–138). Berlin: Springer.CrossRef
  Kinchla, R. A. (1992). Attention. Annual Review of Psychology, 43, 711–743.CrossRef
  Knoblich, G., Öllinger, M., & Spivey, M. J. (2005). Tracking the eyes to obtain insight into insight problem solving. In G. Underwood (Ed.), Cognitive processes in eye guidance (pp. 355–375). Oxford University Press.
  Kopp, K., D’Mello, S., & Mills, C. (2015). Influencing the occurrence of mind wandering while reading. Consciousness and Cognition, 34(1), 52–62.CrossRef
  Mathews, M., Mitrovic, A., Lin, B., Holland, J., & Churcher, N. (2012). Do your eyes give it away? Using eye tracking data to understand students’ attitudes towards open student model representations. In S. A. Cerri, W. J. Clancey, G. Papadourakis, & K.-K. Panourgia (Eds.), Proceedings of the 11th International Conference on Intelligent Tutoring Systems (pp. 422–427). Berlin: Springer.CrossRef
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  Muir, M., & Conati, C. (2012). An analysis of attention to student–Adaptive hints in an educational game. In S. A. Cerri, W. J. Clancey, G. Papadourakis, & K. Panourgia (Eds.), Proceedings of the International Conference on Intelligent Tutoring Systems (pp. 112–122). Berlin: Springer.CrossRef
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  Ponce, H. R., & Mayer, R. E. (2014). Qualitatively different cognitive processing during online reading primed by different study activities. Computers in Human Behavior, 30(1), 121–130.CrossRef
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• 作者单位：Sidney K. D’Mello (1)
  
  1. University of Notre Dame, Notre Dame, IN, USA
  
• 刊物类别：Artificial Intelligence (incl. Robotics); Educational Technology; User Interfaces and Human Computer
• 刊物主题：Artificial Intelligence (incl. Robotics); Educational Technology; User Interfaces and Human Computer Interaction; Computers and Education;
• 出版者：Springer New York
• ISSN：1560-4306

文摘

There is an inextricable link between attention and learning, yet AIED systems in 2015 are largely blind to learners’ attentional states. We argue that next-generation AIED systems should have the ability to monitor and dynamically (re)direct attention in order to optimize allocation of sparse attentional resources. We present some initial ideas towards achieving this goal, starting with a 2 × 2 (direction of attention × content of thoughts) organizational framework that encapsulates a range of attentional states including overt inattention, covert inattention, zone outs, tune outs, and focused, alternating, and divided attention. We then sketch out a three component attentional computing architecture consisting of: (1) devices to monitor where attention appears to be directed; (2) mechanisms for real-time attentional state diagnosis; and (3) interventions to dynamically (re)direct attention. We describe two closed-loop attention-aware AIED systems to serve as concrete renditions of these ideas. We conclude by arguing that AIED can achieve the dual goals of advancing basic research on the science of learning while simultaneously developing highly-effective AIED systems by “attending to attention.”

Keywords Attentional computing Attentional awareness Attention-aware learning Eye tracking Mind wandering Page %P Close Plain text Look Inside Reference tools Export citation EndNote (.ENW) JabRef (.BIB) Mendeley (.BIB) Papers (.RIS) Zotero (.RIS) BibTeX (.BIB) Add to Papers Other actions Register for Journal Updates About This Journal Reprints and Permissions Share Share this content on Facebook Share this content on Twitter Share this content on LinkedIn Related Content Supplementary Material (0) References (61) ReferencesAnderson, J. R. (2002). Spanning seven orders of magnitude: a challenge for cognitive modeling. Cognitive Science, 26(1), 85–112.CrossRefBaker, R., Corbett, A., Koedinger, K., & Wagner, A. (2004). Off-task behavior in the cognitive tutor classroom: When students “game the system”. Proceedings of ACM CHI 2004: Computer-Human Interaction Conference (pp. 383–390). New York: ACM.Bixler, R., & D’Mello, S. (2014). Toward fully automated person-independent detection of mind wandering. In V. Dimitrova, T. Kuflik, D. Chin, F. Ricci, P. Dolog, & G.-J. Houben (Eds.), Proceedings of the 22nd International Conference on User Modeling, Adaptation, and Personalization (pp. 37–48). Switzerland: Springer International Publishing.Bixler, R., & D’Mello, S. K. (2015). Automatic gaze-based detection of mind wandering with metacognitive awareness. In F. Ricci, K. Bontcheva, O. Conlan, & S. Lawless (Eds.), Proceedings of the 23rd International Conference on User Modeling, Adaptation, and Personalization (UMAP 2015) (pp. 31–43). Switzerland: Springer International Publishing.CrossRefBlanchard, N., Bixler, R., & D’Mello, S. K. (2014). Automated physiological-based detection of mind wandering during learning. In S. Trausan-Matu, K. Boyer, M. Crosby, & K. Panourgia (Eds.), Proceedings of the 12th International Conference on Intelligent Tutoring Systems (ITS 2014) (pp. 55–60). Switzerland: Springer International Publishing.Bondareva, D., Conati, C., Feyzi-Behnagh, R., Harley, J. M., Azevedo, R., & Bouchet, F. (2013). Inferring learning from gaze data during interaction with an environment to support self-regulated learning. In K. Yacef, C. Lane, J. Mostow, & P. Pavlik (Eds.), Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED 2013) (pp. 229–238). Berlin: Springer.Boys, C. V. (1895). Soap bubbles, their colours and the forces which mold them: Society for promoting christian knowledge.Bristow, D., Frith, C., & Rees, G. (2005). Two distinct neural effects of blinking on human visual processing. NeuroImage, 27(1), 136–145.CrossRefBrockmole, J. R., & Boot, W. R. (2009). Should I stay or should I go? Attentional disengagement from visually unique and unexpected items at fixation. Journal of Experimental Psychology: Human Perception and Performance, 35(3), 808.Brockmole, J. R., & Henderson, J. M. (2005). Object appearance, disappearance, and attention prioritization in real-world scenes. Psychonomic Bulletin & Review, 12(6), 1061–1067.CrossRefBrockmole, J. R., & Henderson, J. M. (2008). Prioritizing new objects for eye fixation in real-world scenes: effects of object–scene consistency. Visual Cognition, 16(2–3), 375–390.CrossRefCherry, E. C. (1953). Some experiments on the recognition of speech, with one and with two ears. The Journal of the Acoustical Society of America, 25(5), 975–979.CrossRefConati, C., & Merten, C. (2007). Eye-tracking for user modeling in exploratory learning environments: an empirical evaluation. Knowledge-Based Systems, 20(6), 557–574. doi:10.​1016/​j.​knosys.​2007.​04.​010.CrossRefConati, C., Aleven, V., & Mitrovic, A. (2013). Eye-tracking for student modelling in intelligent tutoring systems. In R. Sottilare, A. Graesser, X. Hu, & H. Holden (Eds.), Design recommendations for intelligent tutoring systems—Volume 1: Learner modeling (pp. 227–236). Orlando: Army Research Laboratory.Currie, C. B., McConkie, G. W., Carlson-Radvansky, L. A., & Irwin, D. E. (2000). The role of the saccade target object in the perception of a visually stable world. Attention, Perception, & Psychophysics, 62(4), 673–683.CrossRefD’Mello, S. K., Olney, A. M., Blanchard, N., Samei, B., Sun, X., Ward, B., & Kelly, S. (2015). Multimodal capture of teacher-student interactions for automated dialogic analysis in live classrooms. Paper presented at the Proceedings of the 2015 ACM on International Conference on Multimodal Interaction (ICMI 2015), New York.Damrad-Frye, R., & Laird, J. D. (1989). The experience of boredom: the role of the self-perception of attention. Journal of Personality and Social Psychology, 57(2), 315.CrossRefDeubel, H., & Schneider, W. X. (1996). Saccade target selection and object recognition: evidence for a common attentional mechanism. Vision Research, 36(12), 1827–1837.CrossRefD'Mello, S., Olney, A., Williams, C., & Hays, P. (2012). Gaze tutor: a gaze-reactive intelligent tutoring system. International Journal of Human-Computer Studies, 70(5), 377–398.CrossRefDrummond, J., & Litman, D. (2010). In the zone: Towards detecting student zoning out using supervised machine learning. In V. Aleven, J. Kay, & J. Mostow (Eds.), Intelligent tutoring systems. (Vol. 6095) (pp. 306–308). Berlin: Springer-Verlag.CrossRefEgeth, H. E., & Yantis, S. (1997). Visual attention: control, representation, and time course. Annual Review of Psychology, 48(1), 269–297.CrossRefEngbert, R., Nuthmann, A., Richter, E. M., & Kliegl, R. (2005). SWIFT: a dynamical model of saccade generation during reading. Psychological Review, 112(4), 777.CrossRefForbes-Riley, K., & Litman, D. (2011). When does disengagement correlate with learning in spoken dialog computer tutoring? In S. Bull & G. Biswas (Eds.), Proceedings of the 15th International Conference on Artificial Intelligence in Education (pp. 81–89). Berlin: Springer.Franklin, M. S., Smallwood, J., & Schooler, J. W. (2011). Catching the mind in flight: using behavioral indices to detect mindless reading in real time. Psychonomic Bulletin & Review, 18(5), 992–997.CrossRefGluck, K. A., Anderson, J. R., & Douglass, S. A. (2000). Broader bandwidth in student modeling: What if ITS were “eye” TS? In C. Gauthier, C. Frasson, & K. VanLehn (Eds.), Proceedings of the 5th international conference on intelligent tutoring systems (pp. 504–513). Berlin: Springer.CrossRefGraesser, A., Lu, S., Olde, B., Cooper-Pye, E., & Whitten, S. (2005). Question asking and eye tracking during cognitive disequilibrium: comprehending illustrated texts on devices when the devices break down. Memory and Cognition, 33, 1235–1247. doi:10.​3758/​BF03193225.CrossRefHegarty, M., & Just, M. (1993). Constructing mental models of machines from text and diagrams. Journal of Memory and Language, 32(6), 717–742.CrossRefHoffman, J. E., & Subramaniam, B. (1995). The role of visual attention in saccadic eye movements. Attention, Perception, & Psychophysics, 57(6), 787–795.CrossRefJaques, N., Conati, C., Harley, J. M., & Azevedo, R. (2014). Predicting affect from gaze data during interaction with an intelligent tutoring system. Paper presented at the Intelligent Tutoring Systems.Just, M. A., & Carpenter, P. A. (1980). A theory of reading: from eye fixations to comprehension. Psychological Review, 87, 329–354.CrossRefKardan, S., & Conati, C. (2012). Exploring gaze data for determining user learning with an interactive simulation. In S. Carberry, S. Weibelzahl, A. Micarelli, & G. Semeraro (Eds.), Proceedings of the 20th International Conference on User Modeling, Adaptation, and Personalization (UMAP 2012) (pp. 126–138). Berlin: Springer.CrossRefKinchla, R. A. (1992). Attention. Annual Review of Psychology, 43, 711–743.CrossRefKnoblich, G., Öllinger, M., & Spivey, M. J. (2005). Tracking the eyes to obtain insight into insight problem solving. In G. Underwood (Ed.), Cognitive processes in eye guidance (pp. 355–375). Oxford University Press.Kopp, K., D’Mello, S., & Mills, C. (2015). Influencing the occurrence of mind wandering while reading. Consciousness and Cognition, 34(1), 52–62.CrossRefMathews, M., Mitrovic, A., Lin, B., Holland, J., & Churcher, N. (2012). Do your eyes give it away? Using eye tracking data to understand students’ attitudes towards open student model representations. In S. A. Cerri, W. J. Clancey, G. Papadourakis, & K.-K. Panourgia (Eds.), Proceedings of the 11th International Conference on Intelligent Tutoring Systems (pp. 422–427). Berlin: Springer.CrossRefMills, C., & D’Mello, S. K. (2015). Toward a real-time (day) dreamcatcher: Detecting mind wandering episodes during online reading. In C. Romero, M. Pechenizkiy, J. Boticario & O. Santos (Eds.), Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015). International Educational Data Mining Society.Moss, J., Schunn, C. D., Schneider, W., & McNamara, D. S. (2013). The nature of mind wandering during reading varies with the cognitive control demands of the reading strategy. Brain Research, 1539, 48–60.CrossRefMuir, M., & Conati, C. (2012). An analysis of attention to student–Adaptive hints in an educational game. In S. A. Cerri, W. J. Clancey, G. Papadourakis, & K. Panourgia (Eds.), Proceedings of the International Conference on Intelligent Tutoring Systems (pp. 112–122). Berlin: Springer.CrossRefOlney, A., D'Mello, A., Person, N., Cade, W., Hays, P., Williams, C., . . . Graesser, A. (2012). Guru: A computer tutor that models expert human tutors. In S. Cerri, W. Clancey, G. Papadourakis & K. Panourgia (Eds.), Proceedings of the 11th International Conference on Intelligent Tutoring Systems (pp. 256–261). Berlin/Heidelberg: Springer-Verlag.Olney, A., Risko, E. F., D'Mello, S. K., & Graesser, A. C. (2015). Attention in educational contexts: The role of the learning task in guiding attention. In J. 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Robotics) Educational Technology User Interfaces and Human Computer Interaction Computers and Education Keywords Attentional computing Attentional awareness Attention-aware learning Eye tracking Mind wandering Industry Sectors Aerospace Authors Sidney K. D’Mello (1) Author Affiliations 1. University of Notre Dame, Notre Dame, IN, USA Continue reading... To view the rest of this content please follow the download PDF link above.