James E. Corter
Professor of Statistics and Education
212-678-3843
Personal Website
Expertise
- Assessment and Testing
- Educational Psychology
- Measurement
- Statistics
James E. Corter
Professional Background
Educational Background
B.A. in Psychology (with highest honors), 1977, University of North Carolina - Chapel Hill
Graduate study, L. L. Thurstone Psychometric Laboratory, 1977-1979, University of North Carolina
Ph.D. in Experimental Psychology, 1983, Stanford University
Scholarly Interests
Judgment, Choice, and Decision-Making
Human Categorization and Learning
Multidimensional Scaling and Clustering Methods
Mathematics Problem Solving
Visualization in Reasoning and Problem Solving
Evaluation of New Educational Technologies
Selected Publications
Voiklis, J. & Corter, J. E. (2012). Conventional wisdom: Negotiating conventions of reference enhances category learning. In press, Cognitive Science.
Corter, J.E. (2011). Does investment risk tolerance predict emotional and behavioural reactions to market turmoil? International Journal of Behavioural Accounting and Finance, 2(3/4), 225-237.
Corter, J. E., Esche, S. K., Chassapis, C., Ma, J., & Nickerson, J. V. (2011). Process and learning outcomes from remotely-operated, simulated, and hands-on student laboratories. Computers & Education, 57(3), 2054-2067.
Zahner, D., & Corter, J. E. (2010). The process of probability problem solving: Use of external visual representations. Mathematical Thinking and Learning, 12(2), 177-204.
Corter, J.E., Rho, Y., Zahner, D., Nickerson, J.V., & Tversky, B. (2009). Bugs and biases: Diagnosing misconceptions in the understanding of diagrams. In N. A. Taatgen & H. van Rijn (Eds.),Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp. 756-761). Austin, TX: Cognitive Science Society.
Nickerson, J.V., Zahner, D., Corter, J.E., Tversky, B., Yu, L., and Rho, Y.J. (2009). Matching mechanisms to situations through the wisdom of the crowd, ICIS 2009 Proceedings, Paper 41, http://aisel.aisnet.org/icis2009/41.
Nickerson, J.V. & Corter, J.E. (2009) Clarity from confusion: Using intended interactions to design information systems. In Proceedings of the Fifteenth Americas Conference on Information Systems.
Matsuka, T., and Corter, J.E. (2008). Process tracing of attention allocation during category learning. Quarterly Journal of Experimental Psychology, 61(7), 1067-1097.
Im, S., & Corter, J. E. (2011). Statistical consequences of attribute misspecification in the Rule Space method. Educational and Psychological Measurement, 71(4), 712-731.
Lee, J., & Corter, J. E. (2011). Diagnosis of subtraction bugs using Bayesian networks. Applied Psychological Measurement, 35(1), 27-47.
Corter, J. E., Nickerson, J. V., Esche, S. K., Chassapis, C., Im, S. & Ma, J. (2007). Constructing reality: A study of remote, hands-on and simulated laboratories. ACM Transactions on Computer-Human Interaction (TOCHI), 14(2), 7:1-27.
Corter, J. E., Matuska, T., & Markman, A. B. (2007). Attention allocation in learning an XOR classification task. Proceedings of the Second European Cognitive Science Conference, 935.
Corter, J. E., & Zahner, D. C. (2007). Use of external visual representations in probability problem solving. Statistics Education Research Journal, 6(1), 22-50, http://www.stat.aukland.ac.nz/serj.
Corter, J. E., & Chen, Y.-J. (2006). Do investment risk tolerance attitudes predict portfolio risk? Journal of Business and Psychology, 20-3, 369-381.
Chen, Y.-J., & Corter, J. E. (2005). When mixed options are preferred in multiple-trial decision making. Journal of Behavioral Decision Making, 18, 1-26.
Tatsuoka, K. K., Corter, J. E., & Tatsuoka, C. (2004).Patterns of diagnosed mathematical content and process skills in TIMSS-R across a sample of twenty countries. American Educational Research Journal, 41(4), 901-926.
Matsuka, T., Corter, J. E., & Markman, A. (2002). Allocation of attention in neural network models of categorization. In Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society.
Corter, J. E. (1998). An efficient metric combinatorial algorithm for fitting additive trees. Multivariate Behavioral Research, 33, 249-272.
Corter, J. E. (1996). Tree Models of Similarity and Association. (Sage University Papers series: Quantitative Applications in the Social Sciences, series no. 07-112). Thousand Oaks CA: Sage.
Carroll, J. D., & Corter, J. E. (1995). A graph-theoretic method for organizing overlapping clusters into trees, multiple trees, or extended trees. Journal of Classification, 12, 283-314.
Corter, J. E. (1995). Using clustering methods to explore the structure of diagnostic tests. In P. Nichols, S. Chipman & R. Brennan (Eds.), Cognitively Diagnostic Assessment. Hillsdale NJ: Lawrence Erlbaum Associates, 305-326.
Corter, J.E., & Gluck, M.A. (1992). Explaining basic categories: feature predictability and information. Psychological Bulletin, 111, 291-303.
Corter, J. E., Gluck, M.A ., & Bower, G.H. (1988). Basic levels in hierarchically structured categories. In Proceedings of the Tenth Annual Conference of the Cognitive Science Society. Hillsdale, NJ: Lawrence Erlbaum Associates.
Corter, J. E. (1987). Similarity, confusability, and the density hypothesis. Journal of Experimental Psychology: General, 116, 238-249.
Butler, K. A. & Corter, J. E. (1986). Use of psychometric methods in knowledge acquisition: A case study. In W.A. Gale (Ed.), Artificial Intelligence and Statistics. Reading MA: Addison-Wesley.
Corter, J. E., & Tversky, A. (1986).Extended similarity trees. Psychometrika, 51, 429-451.
publications
Chen, Y.-J., & Corter, J. E. (2010). Changes in risk preference over repeated decisions. Under revision.
Matsuka, T., Corter, J. E., & Markman, A. (2010). Attention learning in adaptive network models of categorization. Under revision.
Corter, J. E., & Monos, C. L. (2010). Effects of category structure and task goals on reference behavior during category learning. Under revision.
Voiklis, J. & Corter, J. E. (2012). Conventional wisdom: Negotiating conventions of reference enhances category learning. In press, Cognitive Science.
Corter, J. E. (2011). Does investment risk tolerance predict emotional and behavioural reactions to market turmoil? International Journal of Behavioural Accounting and Finance, 2(3/4), 225-237.
Corter, J. E., Esche, S. K., Chassapis, C., Ma, J., & Nickerson, J. V. (2011).Process and learning outcomes from remotely-operated, simulated, and hands-on student laboratories. Computers & Education, 57(3), 2054-2067.
Corter, J. E., Mason, D. L., Tversky, B., & Nickerson, J. V. (2011). Identifying causal pathways with and without diagrams. In C. Hoelscher, T. F. Shipley, and L. Carlson (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 2715-2720). Austin, TX: Cognitive Science Society.
Tversky, B., Corter, J. E., Yu, L., Mason, D. L., & Nickerson, J. V. (2011). Visualizing thought: Mapping category and continuum. In C. Hoelscher, T. F. Shipley, and L. Carlson (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 1577-1582). Austin, TX: Cognitive Science Society.
Im, S., & Corter, J. E. (2011). Statistical consequences of attribute misspecification in the Rule Space method. Educational and Psychological Measurement, 71(4), 712-731.
Lee, J., & Corter, J. E. (2011). Diagnosis of subtraction bugs using Bayesian networks. Applied Psychological Measurement, 35(1), 27-47.
Zahner, D., Nickerson, J. V., Tversky, B., Corter, J. E., and Ma. J. (2010). A Fix for Fixation? Re-representing and abstracting as creative processes in the design of information systems. In Maher, M., Kim, Y. S., and Bonnardel, N. (Eds.), Artificial Intelligence in Engineering Design, Analysis and Manufacturing, 24(2), 231-244.
Bobek, E. J., & Corter, J. E. (2010). Effects of problem difficulty and student expertise on the utility of provided diagrams in probability problem solving. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 2650-2655). Austin, TX: Cognitive Science Society.
Nickerson, J. V., Tversky, B., Corter, J. E., Yu, L., Rho, Y. J., & Mason, D. L. (2010). Thinking with networks. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 2662-2667). Austin, TX: Cognitive Science Society.
Zahner, D., & Corter, J. E. (2010). The process of probability problem solving: Use of external visual representations. Mathematical Thinking and Learning, 12(2), 177-204.
Corter, J.E., Rho, Y., Zahner, D., Nickerson, J.V., & Tversky, B. (2009).Bugs and biases: Diagnosing misconceptions in the understanding of diagrams. In N. A. Taatgen & H. van Rijn (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp. 756-761). Austin, TX: Cognitive Science Society.
Nickerson, J.V., Zahner, D., Corter, J.E., Tversky, B., Yu, L., and Rho, Y.J. (2009). Matching mechanisms to situations through the wisdom of the crowd, ICIS 2009 Proceedings, Paper 41,
http://aisel.aisnet.org/icis2009/41.
Nickerson, J.V. & Corter, J.E. (2009) Clarity from confusion: Using intended interactions to design information systems. In Proceedings of the Fifteenth Americas Conference on Information Systems.
Corter, J. E., Nickerson, J.V., Tversky, B., Zahner, D., & Rho, Y. (2008). Using diagrams to design information systems. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society, (pp. 2259.2264). Austin, TX: Cognitive Science Society.
Nickerson, J.V., Corter, J.E., Tversky, B., Zahner, D., & Rho, Y. (2008a). Diagrams as tools in the design of information systems. In J.S. Gero & A. Goel (Eds.), Design Computing and Cognition 08. Dordrecht, Netherlands: Springer-Verlag.
Nickerson, J. V., Corter, J. E., Tversky, B., Zahner, D., and Rho, Y. (2008b). The spatial nature of thought: Understanding information systems design through diagrams, in Boland, R., Limayem, M., and Pentland B., (Eds), Proceedings of the 29th International Conference on Information Systems, Paper 216. http://aisel.aisnet.org/icis2008/216
Tversky, B., Corter, J. E., Nickerson, J.V., Zahner, D., & Rho, Y. (2008). Transforming descriptions and diagrams to sketches in information system design. In G. Stapelton, J. Howse, & J. Lee (Eds.), Proceedings of the 5th International Conference on the Theory and Application of Diagrams 2008. Berlin: Springer-Verlag.
Corter, J. E., Matuska, T., & Markman, A. B. (2007). Attention allocation in learning an XOR classification task. Proceedings of the Second European Cognitive Science Conference, 935.
Nickerson, J. V., Corter, J. E., Esche, S. K., & Chassapis, C. (2007). A model for evaluating the effectiveness of remote engineering laboratories and simulations in education. Computers and Education, 49(3), 7-8-725.
Corter, J. E., & Zahner, D. C. (2007). Use of external visual representations in probability problem solving. Statistics Education Research Journal, 6(1), 22-50, http://www.stat.aukland.ac.nz/serj.
Chen, Y.-J., & Corter, J. E. (2006). When mixed options are preferred in multiple-trial decision making. Journal of Behavioral Decision Making, 19, 1-26.
Tatsuoka, K., Guerrero, A., Corter, J.E., Tatsuoka, C., Yamada, T., Xin, T., Dogan, E., Dean, M., and Im, S. (2006). International comparisons of mathematical thinking skills in the TIMSS-R. Japanese Journal for Research on Testing, 2(1), 3-39.
Corter, J. E. (2005). Additive trees. In B. Everitt & D. Howell (Eds.), Encyclopedia of Statistics in the Behavioral Sciences. London: Wiley.
Matsuka, T. & Corter, J.E. (2004). Stochastic learning algorithm for modeling human category learning. International Journal of Computational Intelligence, 1(1), 40-48.
Corter, J. E., Nickerson, J. V., Esche, S. K., & Chassapis, C. (2004). Remote vs. hands-on labs: A comparative study. In Proceedings of the 34th ASEE/IEEE Frontiers in Education Conference. Piscataway NJ: IEEE.
Matsuka, T., & Corter, J.E. (2004). Modeling human category learning with stochastic optimization methods. Proceedings of the Sixth International Conference on Cognitive Modeling (pp. 196-201). Mahwah NJ: Lawrence Erlbaum Associates.
Matsuka, T., Corter, J. E., & Hanson, S. J. (2004). Irresistibly attractive fruitless feature dimensions. Proceedings of the Sixth International Conference on Cognitive Modeling (pp. 370-371). Mahwah NJ: Lawrence Erlbaum Associates.
Matsuka, T., & Corter, J. E. (2003). Stochastic learning in neural network models of categorization. In Proceedings of the Twenty-Fifth Annual Conference of the Cognitive Science Society. Hillsdale NJ: Lawrence Erlbaum Associates.
Corter, J.E. (2003). Centroid method. In M. Lewis-Beck, A. E. Bryman, & T. F. Liao (Eds.), Encyclopedia of Social Science Research Methods. Thousand Oaks CA: Sage.
Corter, J.E. (2003). Tree diagram. In M. Lewis-Beck, A. E. Bryman, & T. F. Liao (Eds.), Encyclopedia of Social Science Research Methods. Thousand Oaks CA: Sage.
Matsuka, T., Corter, J. E., & Markman, A. B. (2002). Allocation of attention in neural network models of categorization. In Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society. Hillsdale NJ: Lawrence Erlbaum Associates.
Corter, J. E. (1997). [Review of Classification and Cognition]. Journal of Classification, 14(1), 171-173.
Corter, J. E. (1997). GTREE: A PASCAL program to fit additive trees to proximity data. Public domain software, published on Lucent Technologies Bell Labs NETLIB node (http://www.netlib.com/~mds).
Corter, J. E. (1997). User's manual for the GTREE program to fit additive trees. Documentation for software, published on Lucent Technologies Bell Labs NETLIB node (http://www.netlib.com/~mds).
Corter, J. E. (1996). Tree Models of Similarity and Association. (Sage University Papers series: Quantitative Applications in the Social Sciences, series no. 07-112). Thousand Oaks CA: Sage.
Stein, H., Corter, J. E., & Hull, J. (1996). Impact of therapist vacations on inpatients with borderline personality disorder. Psychoanalytic Psychology, 13, 513-530.
Corter, J. E. (1995). Using clustering methods to explore the structure of diagnostic tests. In P. Nichols, S. Chipman & R. Brennan (Eds.), Cognitively Diagnostic Assessment. Hillsdale NJ: Lawrence Erlbaum Associates, 305-326.
Corter, J. E. (1994). The statistical analysis of sequences [Review of Sequential Analysis: A Guide for Behavioral Researchers. New Ideas in Psychology, 12, 95-97.
Corter, J. E., & Gluck, M. A. (1992). Explaining basic categories: Feature predictability and information. Psychological Bulletin, 111(2), 291-303.
Corter, J. E. (1991). Normative theories of categorization. [Commentary on J.R. Anderson, Is human cognition adaptive?] The Behavioral and Brain Sciences, 14, 491-492.
Corter, J. E. (1991). [Review of Data Theory and Dimensional Analysis]. Applied Psychological Measurement, 15, 423-424.
Corter, J. E. (1989). Extended tree representation of relationships among languages. In N.X. Luong (Ed.), Analyse Arbore des Donnes Textuelles [special issue]. Cahiers des Utilisateurs de Machines lectronique des Fins d'Information et de Documentation (CUMFID), 16[Juin], 139-155.
Corter, J. E. (1988). Testing the density hypothesis: Reply to Krumhansl. Journal of Experimental Psychology: General, 117, 105 106.
Corter, J., Gluck, M. A., & Bower, G. H. (1988). Basic levels in hierarchically structured categories. In Proceedings of the Tenth Annual Conference of the Cognitive Science Society. Hillsdale NJ: Lawrence Erlbaum Associates.
Butler, K. A., & Corter, J. E. (1986). Use of psychometric methods in knowledge acquisition: A case study. In W.A. Gale (Ed.), Artificial Intelligence and Statistics. Reading MA: Addison-Wesley.
Corter, J. E. (1986). Relevant features and statistical theories of generalization. [Commentary on R.C. Schank, G.C. Collins & L.E. Hunter, Transcending inductive category formation in learning.] The Behavioral and Brain Sciences, 9, 653-654.
Corter, J. E., & Tversky, A. (1986). Extended similarity trees. Psychometrika, 51, 429 451.
Gluck, M. A., & Corter, J. E. (1985). Information, uncertainty and the utility of categories. In Proceedings of the Seventh Annual Conference of the Cognitive Science Society. Hillsdale NJ: Lawrence Erlbaum.
Corter, J. E., & Gluck, M. A. (1985). Machine generalization and human categorization: An information-theoretic view. In Proceedings of the Workshop on Uncertainty and Probability in Artificial Intelligence, Los Angeles: AAAI/RCA.
Corter, J. E. (1983). Psychological similarity and the density hypothesis. Unpublished Ph.D. dissertation, Stanford University.
Corter, J. E. (1982). ADDTREE/P: A PASCAL program for fitting additive trees based on Sattath & Tversky's ADDTREE algorithm. Behavior Research Methods and Instrumentation, 14, 353 354.
professional experiences
Program Coordinator, Applied Statistics, May 2009-January 2010
Chair, Department of Human Development, Teachers College, Columbia University, July 2000-August 2007
Acting Chair, Department of Human Development, Summer 1999
Program Coordinator, Cognitive Studies in Education, May 1998-August 2000
Associate Professor of Statistics and Education, Teachers College, Columbia University, 1989-August 2007.
Assistant Professor of Statistics and Education, Teachers College, Columbia University, 1983-1989.
Resident Visitor, AT&T Bell Laboratories, 1983-1988.
Consultant, Xerox Palo Alto Research Center (PARC), 1981-1983.
Teaching Experience:
Applied Regression Analysis Individual Decision Making
Experimental Design Cognition and Computers
Multivariate Statistics Factor Analysis
Multidimensional Scaling and Clustering Statistical Treatment of Mass Data
Professional Affiliations and Activities:
Ad-hoc reviewing for: The Behavioral and Brain Sciences, Behavioral Research Methods, Instruments, and Computers, British Journal of Mathematical and Statistical Psychology, Cognitive Science, Journal of Experimental Psychology: General, Journal of Experimental Psychology: Learning, Memory, and Cognition, Journal of Mathematical Psychology, Memory and Cognition, Multivariate Behavioral Research, Perception and Psychophysics, Psychological Bulletin, Psychological Review, Psychometrika, Review of Educational Research, and the National Science Foundation.
National Science Foundation (NSF) grant review panelist, Spring 2003. Directorate: Behavioral and Cognitive Sciences, Program in Perception, Action, and Cognition.
National Science Foundation (NSF) site review team, Pittsburgh Science of Learning Center. Spring 2007, Spring 2008, Spring 2009.
National Science Foundation (NSF) grant review panelist, September 2008. Machine Learning program, CAREER Awards.
current projects
Several recent / current projects have combined several of these interests. With Kikumi Tatsuoka, I conducted an NSF-funded project involving statistical and empirical studies of mathematics problem solving, aimed at better understanding student performance on the Third International Math and Science Study - Revised (TIMSS-R). This work explored applications of "cognitively diagnostic" psychometric methods to the study of mathematics problem solving. A recent NSF grant, in collaboration with a group of researchers from Stevens Institute of Technology, examined the effectiveness of remotely-operated student labs and computer simulations, relative to traditional hands-on labs, in engineering courses. Two more recent NSF-funded projects, in collaboration with Barbara Tversky and Jeffrey Nickerson, examine the role of diagrams in reasoning, design, and problem solving. Finally, another current NSF-supported project explores the use of game-based simulations in science and medical education. In collaboration with several current and former doctoral students, I have been studying how students acquire skill in probability problem solving and what role external visual inscriptions play in these skills; other collaborative work has focused on developing and applying new measurement models to better understand problem-solving.
In the area of category learning, a former student, Toshihiko Matsuka, and I are writing up research that collected empirical data investigating how attention is allocated across stimulus dimensions in the learning of complex categories, and examines how well prominent neural network models account for the data. Some of this work, with a modeling focus, has been conducted in collaboration with Art Markman of the University of Texas. With another former student, Yuh-Jia Chen, I have been investigating how people make repeated decisions, and the role of learning in shaping decision behavior in such contexts. In other decision-making research I have examined the relationship of attitudes towards risk and uncertainty with decision behavior. With a former student, Yi-Chun Chen, I have recently been studying how students make and use budgets to manage their expenditures while achieving goals. With Yun-Jin Rho and Huiyun Tseng (former students) and Prof. Matthew Johnson, I have been working on new cognitively diagnostic measurement models.
In the area of statistical methodology, I have been working on a long-term project on representing asymmetric proximity relationships using directed trees.
honors and awards
professional organization membership
Service to Field, Profession, and Society:
Statistics/psychometric consultant to Ivy League Athletic Association
Chair, Human Development (Summer 2000-August 2007)
Coordinator, Cognitive Studies in Education program (1998-2000)
Medical Benefits Committee (2005-2006)
Intellectual Property Committee
Research Literacy Task Force
Area A Ph.D committee
Interviews for Human Resources Director
Middle States Reaccreditation Committee – Evaluation Standards Subcommittee
Faculty Executive Committee
Faculty Advisory Committee
Presidential Search Committee (AY 1994-1995)
HUDM 4122: Probability and statistical inference
Prerequisite: HUDM 4120 or undergraduate statistics course. Elementary probability theory; random variables and probability distributions; sampling distributions; estimation theory and hypothesis testing using binomial, normal, T, chi square, and F distributions.Lab fee $50.00
HUDM 5058: Choice and decision making
Prerequisite: HUDM 4122 or equivalent. Surveys quantitative models of individual decision making, from the introduction of the notion of "utility" by Daniel Bernoulli through current models such as Tversky and Kahnemans "Prospect Theory." The focus is on psychological or descriptive models of how people make decisions, although methods of rational decision analysis are briefly discussed.
HUDM 5122: Applied regression analysis
Prerequisite: HUDM 4122 or permission of instructor. Least squares estimation theory. Traditional simple and multiple regression models and polynomial regression models, with grouping variables including one-way ANOVA, two-way ANOVA, and analysis of covariance. Lab devoted to applications of SPSS regression program. Lab fee: $50.
HUDM 5123: Linear models and experimental design
Prerequisite: HUDM 5122. Analysis of variance models including within subject designs, mixed models, blocking, Latin Square, path analysis, and models with categorical dependent variables. Lab devoted to computer applications. Lab fee: $50.
HUDM 5124: Multidimensional scaling and clustering
Permission required. Prerequisites: HUDM 4122 and HUDM 5122 or equivalent. Methods of analyzing proximity data (similarities, correlations, etc.), including multidimensional scaling, which represents similarities among items by plotting the items into a geometric space, and cluster analysis for grouping items.
Documents & Papers
Download: 1986_Corter_Tversky_Extended similarity trees [PDF]
Download: 2007_Coter et al_Constructing reality [PDF]
Download: 2010_Zahner_Nickerson_Tversky_Corter_Ma [PDF]
Download: 2011_Im_Corter_Statistical consequences of attribute misspecification in the Rule Space method. [PDF]
Download: 1992_Corter_Gluck_Explaining basic categories_ feature predictability and information [PDF]
Download: 2010_Nickerson_Tversky_Corter_Yu_ Thinking with networks [PDF]
Download: 1995_Carroll_Corter_A graph-theoretic method for organizing overlapping clusters into trees [PDF]
Download: 2009_Nickerson_Zahner_Corter_Tversky_Yu_Rho_Matching mechanisms to situations through the wisdom of the crowd, [PDF]
Download: 2008_Nickerson_Corter_Tversky_Zahner_Rho_Diagrams as tools in the design of information systems. [PDF]
Download: 2007_Nickerson_Corter_Esche_Chassapis_A model for evaluating the effectiveness of remote engineering laboratories and simulations in education. [PDF]
Download: 2003_Matsuka_Corter_ Stochastic learning in neural network models of categorization. [PDF]
Download: 2010_Zahner_Corter_The process of probability problem solving_Use of external visual representations. [PDF]
Download: 1985_Gluck_Corter_Machine generalization and human categorization_ An information-theoretic view [PDF]
Download: 2008_Matsuka_Corter_Process tracing of attention allocation during category learning. [PDF]
Download: 2004_Matsuka_Corter_Stochastic learning algorithm for modeling human category learning. [PDF]
Download: 2009_Nickerson_Corter_Clarity from confusion_ Using intended interactions to design information systems. [PDF]
Download: 2010_Bobek_Corter_Effects of problem difficulty and student expertise on the utility of provided diagrams in probability problem solving. [PDF]
Download: 2011_Corter_Esche_Chassapis_Ma_Nickson_Process and learning outcomes from romotely operated simulated and hands on student laboratories [PDF]
Download: 2008_Corter et al_Using diagrams to design information systems. [PDF]
Download: Corter et al_tech report TIMSS [PDF]
Download: 2004_Matsuka_Corter_Stochastic learning algorithm for modeling human category learning [PDF]
Download: 2004_Corter_Nickerson_Esche_Chassapis_Remote vs. hands-on labs_ A comparative study. [PDF]
Download: 2009_Corter_Pho_Zahner_Nickson_Tversky_Bugs and biases_Diagnosing misconceptions in the understanding of diagrams [PDF]
Download: 2004_Tatsuoka_Corter_Tatsuoka_Patterns of diagnosed mathematical content and process skills in TIMSS-R across a sample of twenty countries. [PDF]
Download: 1996_Stein_Corter_James_Impact of therapist vacations on inpatients with borderline personality disorder [PDF]
Download: 2007_Corter et al_Constructing reality_A study of remote, hands-on and simulated laboratories. [PDF]
