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Publications about User ModelingAnderson, J. R., Betts, S. A., Ferris, J. L., & Fincham, J. M. (2010). Neural imaging to track mental states while using an intelligent tutoring system. Proceedings of the National Academy of Science, 107(15), 7018-7023. [ Anderson, J. R., Betts, S. A., Ferris, J. L., & Fincham, J. M. (in press). Tracking children's mental states while solving algebra equations. Human Brain Mapping . [ Anderson, J. R. (in press) Tracking problem solving by multivariate pattern analysis and hidden markov model algorithms. Neuropsychologia. [info] Anderson, J. R. & Qin, Y. (2008). Using Brain Imaging to Extract the Structure of Complex Events at the Rational Time Band. Journal of Cognitive Neuroscience, 20 (9) , 1624-1636. [ Anschütz, A., Bernholt, S., Özyurt, J., Lenk, J., Moschner, B., Parchmann, I., Möbus, C., & Thiel, C.M. (2011). Impact of Affective and Informative Feedback on Learning in Children before and after a Reattribution Training An Integrated Approach using Neuroimaging, Educational Research, and Modelling. In J. Özyurt, A. Anschütz, S. Bernholt, & J. Lenk (eds.), Interdisciplinary Perspectives on Cognition, Education and the Brain, Hanse Studies, Vol. 7, Hanse-Wissenschaftskolleg (HWK)(pp. 25-35), Institute for Advanced Study: Oldenburg: BIS-Publisher. [info] Ball, J., Myers, C., Heiberg, A., Cooke, N.J., Matessa, M., Freiman, M., Rodgers, S. (2010). The synthetic teammate project. Computational and Mathematical Organization Theory, 16(3), 271-299. [info] Best, B.J., Furjanic, C., Gerhart, N., Fincham, J. M., Gluck, K. A., Gunzelmann, G., Krusmark, M., (2009). Adaptive Mesh Refinement for Efficient Exploration of Cognitive Architectures and Cognitive Models. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 252), Manchester, United Kingdom. [ Best, B. J. & Lovett, M. (2006). Inducing a cognitive model from examples provided by an optimal algorithm. In Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 56-61). Trieste, Italy. [ Brunstein, A. (2006). Constructing racing cars: Reducing problem complexity for the fastest car ever seen. In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 2452 ) . Vancouver, British Columbia, Canada. [ Cassenti, D.N. (2007). ACT-R model of EEG latency. Proceedings of the Human
Factors and Ergonomics Society 51st Annual Meeting (pp. 812-816). Santa
Monica, CA: Human Factors and Ergonomics Society. [ Corbett, A. T. & Anderson, J. R. (1995). Knowledge tracing: Modeling the acquisition of procedural knowledge. User Modeling and User-Adapted Interaction, 4, 253-278. [ Corbett, A.T., Anderson, J. R., & O'Brien, A.T. (1995). Student modeling in the ACT Programming Tutor. In P. Nichols, S. Chipman and B. Brennan (eds.) Cognitively Diagnostic Assessment. (19-41). Hillsdale, NJ: Erlbaum. [ Das, A., & Stuerzlinger, W. (2007). A Cognitive Simulation Model
for Novice Text Entry on Cell Phone Keypads. In Proceedings of
the European Conference on Cognitive Ergonomics: ECCE 2007
(pp. 141-147). London, UK.
[ Das, A., & Stuerzlinger, W. (2008). Modeling Learning Effects in Mobile Texting. In Proceedings of the International Conference on Mobile and Ubiquitous Multimedia: MUM 2008 (pp. 154-161). Umea, Sweden.
[ Fu, W.-T., Bothell, D., Douglass, S., Haimson, C., Sohn, M.-H., & Anderson, J.
A. (2006), Toward a Real-Time Model-Based Training System. Interacting with
Computers, 18(6), 1216-1230.
[ Fu, W.-T. & Gray, W. D. (2004), Resolving the paradox of the active user: Stable suboptimal performance in interactive tasks. Cognitive Science, 28(6), 901-935.
[ Gluck, K. A., Stanley, C. T., Moore, L. R., Reitter, D., & Halbrugge, M. (2010).
Exploration for understanding in cognitive modeling. Journal of Artificial General Intelligence,2(2), 88-107.
[ Harrison, A. & Trafton, J. G. (2010). Cognition for action: an architectural account for “grounded interaction”. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 246-251). Austin, TX: Cognitive Science Society. [ Heinath, M. (2009). High-level ACT-R modeling based on SGT task models. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 171), Manchester, United Kingdom. [ Heinath, M., Dzaack, J., Wiesner, A. & Urbas, L. (2007). Simplifying the
Development and the Analysis of Cognitive Models. In proceedings of EuroCogSci07. Delphi,
Greece. [ Heinath, M. & Urbas, L. (2007). Simplifying the Development of Cognitive
Models using Pattern-based Modeling. In proceedings of the 10th IFAC/IFIP/IFORS/IEA Symposium on
Analysis, Design, and Evaluation of Human-Machine Systems. Seoul, Korea. [ John, B. E. & Jastrzembski, T. S. (2010). Exploration of costs and benefits of predictive human performance modeling for design. In D. D.
Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International
Conference on Cognitive Modeling (pp. 115-120). Philadelphia, PA: Drexel
University. [ Jones, G., & Ritter, F. E. (2000). Over-estimating cognition time: The benefits of using a task simulation. In Simulating Human Agents, American Association for Artificial Intelligence Fall 2000 Symposium Series (pp. 67-74). Menlo Park, CA: AAAI Press. [info] Juvina, I. & Taatgen, N.A. (2007). Modeling Control Strategies in the N-Back Task. In proceedings of the 8th International Conference on Cognitive Modeling. Ann Arbor, Michigan, USA. [ Kim, J. W., Ritter, F. E., & Koubek, R. J. (2006). ESEGMAN: A substrate for ACT-R architecture and an Emacs LISP application. In Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 375-376). Trieste, Italy. [ Lebiere, C. (2005). Constrained functionality: Application of the act-r cognitive architecture to the ambr modeling comparison. In K. A. Gluck and R. Pew, editors, Modeling Human Behavior With Integrated Cognitive Architectures, Mahwah, NJ: Erlbaum.
[ Lenk, J. C., Möbus, C., Özyurt, J. Margarete, C., & Claassen, A. (2011). From fMRI Data To Cognitive Models: Testing the ACT-R Brain Mapping Hypothesis with an Ex-Post Model. In The Third International Conference on Advanced Cognitive Technologies and Applications (pp. 13-18). Rome, Italy. [HTML] [info] Lindsey, R., Lewis, O., Pashler, H., & Mozer, M. (2010). Predicting Students' Retention of Facts from Feedback during Study. Poster presented at the 32nd Annual Conference of the Cognitive Science Society. Portland, OR. [ Lyon, D. R. & Gunzelmann, G. (2009). Visualizing egocentric path descriptions: A computational model. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 102), Manchester, United Kingdom. [ Marewski, J. N., & Olsson, H. (2009). Beyond the null
ritual: Formal modeling of psychological processes. Zeitschrift für Psychologie/Journal
of Psychology, 217, 49-60.
[ Marewski, J. N. & Olsson, H. (2009). Beyond the Nul Ritual: Formal modeling of pscyhological processes. Zeitschrift für Psychologie / Journal of Psychology, 217(1), 49–60. [info] Myers, C., Gluck, K. A., Gunzelmann, G., & Krusmark, M. (2010). Validating
computational cognitive process models across multiple timescales. Journal of Artificial General Intelligence, 2(2),
108-127.
[ Najjar, M. & Mayers, A. (2006). Retrieving remembrances via a computational cognitive model of knowledge represenation. In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 1868-1869) . Vancouver, British Columbia, Canada. [ Paik, J., Kim, J. W., & Ritter, F. E. (2009). A preliminary ACT-R Compiler in Herbal. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 117), Manchester, United Kingdom. [ Paik, J., Kim, J. W., Ritter, F. E., Morgan, J. H., Haynes, S. R., & Cohen, M. A. (2010). Building large learning models with Herbal. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of ICCM Tenth International Conference on Cognitive Modeling (pp. 187-191). Philadelphia, PA. [ Peebles, D. (2012). A cognitive architecture-based model of graph comprehnsion. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.
[ Peebles, D. & Banks, A. (2010). Modelling dynamic decision making with the ACT-R cognitive architecture. Journal of Artificial General Intelligence, 2(5), 52-68. [ Peebles, D. J. & Cox, A. L. (2006). Modelling Interactive Behaviour with a
Rational Cognitive Architecture. In P. Zaphiris & S. Kurniawan (Eds.).
Human Computer Interaction Research in Web Design and Evaluation. London.
Idea Group Inc. [ Reitter, D. (2010). Metacognition and multiple strategies in a cognitive model of online control. Journal of Artificial General Intelligence, 2(2), 20-37. [ Ritter, F. E., Haynes, S. R., Cohen, M., Howes, A., John, B., Best, B. J., Lebiere, C., Jones, R. M., Crossman, J., Lewis, R. L., St. Amant, R., McBride, S. P., Urbas, L., Leuchter, S., & Vera, A. (2006). High-level behavior represenation languages revisited. Symposium at Trieste:Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 404-407). Trieste, Italy. [ Ritter, F. E., Kukreja, U., & St. Amant, R. (2007). Including a model
of visual processing with a cognitive architecture to model a simple
teleoperation task. Journal of Cognitive Engineering and Decision
Making, 1(2), 121-147. [ Ritter, F. E., van Rooy, D., St. Amant, R., & Simpson, K. (2006). Providing user models direct access to interfaces: An exploratory study of a simple interface with implications for HRI and HCI. IEEE Transactions on Systems, Man, and Cybernetics: Part A, Systems and Humans, 36(3), 592-601. [ Ritter, F. E., & Young, R. M. (2001). Embodied models as simulated users: Introduction to this special issue on using cognitive models to improve interface design. International Journal of Human-Computer Studies, 55, 1-14. [ Rutledge-Taylor, M., Pyke, A., West, R. & Lang, H. (2010). Modeling a Three Term
Fan Effect. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th
International Conference on Cognitive Modeling (pp. 211-216). Philadelphia, PA: Drexel
University. [ Salvucci, D.D., & Lee, F. J. (2003). Simple cognitive modeling in a complex cognitive architecture. In Human Factors in Computing Systems: CHI 2003 Conference Proceedings (pp. 265-272). New York: ACM Press. [HTML] [info] Schoelles, M. J., Neth, H., Myers, C. W., & Gray, W. D. (2006). Steps towards integrated models of cognitive systems: A levels-of-analysis approach to comparing human performance to model predictions in a complex task environment. In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 756-761 ) . Vancouver, British Columbia, Canada. [ Serna, A., Pigot, H., & Rialle, V. (2007). Modeling the progression of Alzheimer's disease for cognitive assistance in smart homes. User Modeling and User-Adapted Interaction, 17, 415-438. [ St. Amant, R., Freed, A. R., & Ritter, F. E. (2005). Specifying ACT-R models of user interaction with a GOMS language. Cognitive Systems Research, 6, 71-88. [ St. Amant, R., Horton, T. E., & Ritter, F. E. (2007). Model-based evaluation of expert cell phone menu interaction. ACM Transactions on Computer-Human Interaction, 14(1), Article 1 (May 2007), 24 pages.
[ St. Amant, R., McBride, S. P., Ritter, F. E. (2007). AI support for building cognitive models. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-06) (pp. 1663-1666). Menlo Park, CA: AAAI Press. [ St. Amant, R., Riedl, M. O., Ritter, F. E., & Reifers, A. (2005). Image processing in cognitive models with SegMan. In Proceedings of HCI International, 2005. (Invited.) Volume 4 - Theories Models and Processes in HCI. Paper # 1869. [ St. Amant, R. & Ritter, F. E. (2004). Automated GOMS-to-ACT-R model generation. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 26-31). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh. [ Stanley, C. T. (2010). LETF: A Lisp-Based Exploratory Testing Framework for Computational Cognitive Models. In D. D.
Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International
Conference on Cognitive Modeling (pp. 297-298). Philadelphia, PA: Drexel
University. [ Stewart, T. C. (2006). Tools and techniques for quantitaive and predictive cognitive science. In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 816-821 ) . Vancouver, British Columbia, Canada. [ Taatgen, N. A. & Anderson, J. R. (2009). The Past, Present, and Future of Cognitive Architectures. topiCS in Cognitive Science, 1-12. [ Van Maanen, L. (2007). Mediating expert knowledge and visitor
interest in art work recommendation. In proceedings of LWA 2007,
Halle (Saale), Germany. [ Van Maanen, L., Borst, J. P., Janssen, C. P., & Van Rijn, H. (2006).
Memory structures as user models, In proceedings of the 13th Annual
ACT-R Workshop. Pittsburgh, PA.
[ Van Maanen, L., & Marewski, J. N. (2009). Recommender systems for literature
selection: A competition between decision making and memory models. In N.A.
Taatgen & H. van Rijn (Eds.), Proceedings of the 31st Annual Conference of the
Cognitive Science Society (pp. 2914-2919). Austin, TX: Cognitive Science
Society. [ Van Maanen, L., Van Rijn, H., Van Grootel, M., Kemna, S., Klomp, M., &
Scholtens, E. (2010). Personal Publication Assistant: Abstract
recommendations by a cognitive model. Cognitive Systems Research, 11(1),
120-129 (Special Issue on Brain Informatics).
[ van Rijn, D. H., van Maanen, L., & van Woudenberg, M. (2009).Passing the test: Improving learning gains by balancing spacing and testing effects. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 200), Manchester, United Kingdom. [ Walsh, M.M., & Anderson, J.R. (2011). Learning from delayed feedback: Neural responses in temporal credit assignment. Cognitive, Affective, and Behavioral Neuroscience, 11, 131-143. [ West, R.L, Emond B. (2002). SOS: A simple operating system for modeling HCI with ACT-R. Seventh Annual ACT-R Workshop. Pittsburgh, PA : Department of Psychology, Carnegie Mellon University, 2 p. [ Wintermute, S., Betts, S. A., Ferris, J. L., Fincham, J. M., & Anderson, J. R. (2012). Brain Networks Supporting Execution of Mathematical Skills versus Acquisition of New Mathematical Competence. Public Library of Science (PLOS) ONE. [Document][Pyramid Data] [info] To include publications predating act-r, click here |
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