Conferences & Workshops
(I've helped to run)

Cogsci 2002
ICCM 2001, 2004
NSF Innovation Workshop 2006
NSF Workshop on Confidential Data Collection 2009
ISDDE 2011
 

& Book Chapters

STEM Thinking | STEM Learning | Web-based Peer Interaction | Neuroscience of Complex Learning

Engagement and Learning | HCI | Strategy Use | General Cognitive Science

 

Science Reasoning & Engineering Design

Egan, P., Chiu, F., Cagan, J., Schunn, C., LeDuc, P., Moore, J. (2016). The d3 design methodology: Bridging science and design for bio-based product development. Journal of Mechanical Design, 138, 081101-1-13. pdf

Paletz, S., Chan, J., & Schunn, C. D. (2016). Uncovering uncertainty through disagreement. Applied Cognitive Psychology, 30(3), 387-400. pdf

Egan, P., Schunn, C., Cagan, J., & LeDuc, P. (2015). Improving understanding and design proficiency of complex multi-level biosystems through animation and parametric relationships support. Design Science, 1(1), e3. doi:10.1017/dsj.2015.3 pdf

Chan, J., & Schunn, C. D. (2015). The importance of iteration in creative conceptual combination. Cognition, 145, 104–115. doi:10.1016/j.cognition.2015.08.008. pdf

Egan, P., Schunn, C. D., Cagan, J., & LeDuc, P. (2015). Emergent systems energy laws for predicting myosin ensemble processivity. PLOS Computational Biology, 11(4): e1004177. link

Egan, P., Cagan, J., Schunn, C. D., & LeDuc, P. (2015). Synergistic human-agent methods for deriving effective search strategies: The case of nanoscale design. Research In Engineering Design, 26(2), 145-169. pdf

Chan, J., Dow, S. P., & Schunn, C. D. (2015). Do the best design ideas (really) come from conceptually distant sources of inspiration? Design Studies, 36, 31-58. pdf

Chan, J., & Schunn, C. D. (2015).The impact of analogies on creative concept generation: Lessons from an in vivo study in engineering design. Cognitive Sciencee, 39(1), 126-155. pdf

Paletz, S. B. F., Kim, K., Schunn, C. D., Tollinger, I., & Vera, A. (2013). The development of adaptive expertise, routine expertise, and novelty in a large research team. Applied Cognitive Psychology, 27(4), 415–428. pdf

Egan, P. F., Cagan, J. C., Schunn, C. D., & LeDuc, P. R. (2013). Design of complex biologically-based nanoscale systems using multi-agent simulations and structure-behavior-function representations. Journal of Mechanical Design, 135(6), 061005. pdf

Fu, K., Chan, J., Cagan, J., Kotovsky, K., Schunn, C., & Wood, K. (2013). The meaning of “near” and “far”: The impact of structuring design databases and the effect of distance of analogy on design output. Journal of Mechanical Design, 135(2), 021007. pdf

Fu, K., Chan, J., Schunn, C. D., Cagan, J., & Kotovsky, K. (2013). Expert representation of design repository space: A comparison to and validation of algorithmic output. Design Studies, 34(6), 729-762. pdf

Paletz, S. B. F., Schunn, C. D., & Kim, K. (2013). The interplay of conflict and analogy in multidisciplinary teams. Cognition, 126(1), 1-19. pdf

Chan, J., Paletz, S., & Schunn, C. D. (2012). Analogy as a strategy for supporting complex problem solving under uncertainty. Memory & Cognition, 40, 1352-1365. pdf

Paletz, S. B. F., & Schunn, C. D. (2012). Digging into implicit/explicit states and processes: The case of cognitive/social process interaction in scientific groups. In R. Proctor and J. Capaldi (Eds.), Psychology of Science: Implicit and Explicit Processes. Oxford University Press. pdf

Schunn, C. D., & Trafton, J. G. (2012). The psychology of uncertainty in scientific data analysis. In G. Feist & M. Gorman (Eds.), Handbook of the Psychology of Science. Springer Publishing. pdf

Chan, J., Fu, K., Schunn, C. D., Cagan, J., Wood, K., & Kotovsky, K. (2011). On the benefits and pitfalls of analogies for innovative design: Ideation performance based on analogical distance, commonness, and modality of examples. Journal of Mechanical Design, 133, 081004-1-11. pdf

Paletz, S. B. F., Schunn, C. D., & Kim, K. (2011). Intragroup conflict under the microscope: micro-conflicts in naturalistic team discussions. Negotiation and Conflict Management Research, 4, 314-351. pdf

Paletz, S. B. F., & Schunn, C. D. (2011). Assessing group level participation in fluid teams: Testing a new metric. Behavior Research Methods, 10.3758/s13428-011-0070-3. pdf

Schunn, C. D. (2010). From uncertainly exact to certainly vague: Epistemic uncertainty and approximation in science and engineering problem solving. In B. Ross (Ed.), Psychology of Learning and Motivation (Vol. 53). pdf

Linsey, J., Tseng, I., Fu, K., Cagan, J., Wood, K., & Schunn, C. D. (2010). A study of design fixation, its mitigation and perception in engineering design faculty. Journal of Mechanical Design, 132(4), 041003-1-12. pdf

Schunn, C. D. (2010). From uncertainly exact to certainly vague: Epistemic uncertainty and approximation in science and engineering problem solving. In B. Ross (Ed.), Psychology of Learning and Motivation (Vol. 53). pdf

Paletz, S. B. F., & Schunn, C. D. (2010). A social-cognitive framework of multidisciplinary team innovation. Topics in Cognitive Science, 2, 73-95. pdf

Christensen, B. T., & Schunn, C. D. (2009). Setting a limit to randomness [or: ‘Putting blinkers on a blind man’]: Providing cognitive support for creative processes with environmental cues. In K. Wood & A. Markman (Eds.), Tools for Innovation. Oxford University Press. pdf

Trickett, S. B, Trafton, J. G., & Schunn, C. D. (2009). How do scientists respond to anomalies? Different strategies used in basic and applied science. Topics in Cognitive Science, 1(4), 711-729. pdf

Christensen, B. T., & Schunn, C. D. (2009). The role and impact of mental simulation in design. Applied Cognitive Psychology, 23, 327-344. pdf

Christensen, B. T., & Schunn, C. D. (2007). The relationship of analogical distance to analogical function and pre-inventive structure: The case of engineering design. Memory & Cognition, 35(1), 29-38. pdf

Schunn, C. D., Saner, L. D., Kirschenbaum, S. K., Trafton, J. G., & Littleton, E. B. (2007). Complex visual data analysis, uncertainty, and representation. In M. C. Lovett & P. Shah (Eds.), Thinking with Data. Mahwah, NJ: Erlbaum. pdf

Trickett, S. B., Trafton, J. G., & Saner, L. D., & Schunn, C. D. (2007). "I don't know what is going on there": The use of spatial transformations to deal with and resolve uncertainty in complex visualizations. In M. C. Lovett & P. Shah (Eds.), Thinking with Data. Mahwah, NJ: Erlbaum. pdf

Mehalik, M. M., & Schunn, C. D. (2006). What constitutes good design? A review of empirical studies of the design process. International Journal of Engineering Education, 22(3), 519-532. pdf

Trafton, J. G., Trickett, S. B., Stitzlein, C. A., Saner, L. D., Schunn, C. D., & Kirschenbaum, S. S. (2006). The relationship between spatial transformations and iconic gestures. Spatial Cognition & Computation, 6(1), 1-29. pdf

Schunn, C. D., Crowley, K., & Okada, T. (2005). Cognitive Science: Interdisciplinarity now and then. In S. J. Derry, C. D. Schunn, & M. A. Gernsbacher (Eds.), Problems and promises of interdisciplinary collaboration: Perspectives from cognitive science. Mahwah, NJ: Erlbaum. pdf

Trickett, S. B., Trafton, J. G., & Schunn, C. D. (2005). Puzzles and peculiarities: How scientists attend to and process anomalies during data analysis. In M. E. Gorman, R. D. Tweney, D. Gooding, & A. Kincannon (Eds.), Scientific and technological thinking (pp. 97-118). Mahwah, NJ: LEA. pdf

Christensen, B. T., & Schunn, C. D. (2005). Spontaneous access and analogical incubation effects. Creativity Research Journal, 17(2), 207-220. pdf

Schunn, C. D., Crowley, K., & Okada, T. (2002). What makes collaborations across a distance succeed?: The case of the Cognitive Science community. In P. Hinds & S. Kiesler (Eds.), Distributed Work. Cambridge, MA: MIT Press. pdf

Schunn, C. D., Crowley, K., & Okada, T. (2000). Cognitive Science: Interdisciplinarity now and then. In K. Ueda & T. Okada (Eds.), (2000). In search of collaborative cognition: Cognitive science on creative collaboration. Tokyo: Kyoritsu Shuppan. (In Japanese)

Schunn, C. D., & Klahr, D. (2000). Discovery processes in a more complex task. In D. Klahr (Ed.), Exploring science: The cognition and development of discovery processes. Cambridge, MA: MIT Press. Download programs. pdf

Schunn, C. D., & Anderson, J. R. (1999). The generality/specificity of expertise in scientific reasoning. Cognitive Science, 23(3), 337-370. pdf

Schunn, C. D., & Anderson, J. R. (1998). Scientific Discovery. In J. R. Anderson & C. Lebiere (Eds.), Atomic Components of Thought. Mahwah, NJ: Erlbaum. pdf

Schunn, C. D., Crowley, K., & Okada, T. (1998). The growth of multidisciplinarity in the Cognitive Science Society. Cognitive Science, 22(1), 107-130.pdf

Schunn, C. D., & Dunbar, K. (1996). Priming, analogy, and awareness in complex reasoning. Memory & Cognition, 24(3), 271-284. pdf

Science, Technology, Engineering, and Mathematics Learning

Cromley, J. M., Weisberg, S. M., Dai, T., Newcombe, N. S., Schunn, C. D., Massey, C., Merlino, F. J. (in press). Improving middle school science learning using diagrammatic reasoning. Science Education.

Iriti, J., Bickel, W., Schunn, C., & Stein, M. K. (2016). Maximizing research and development resources: Identifying and testing “load-bearing conditions” for educational technology innovations. Educational Technology Research & Development, 64, 245-262. 10.1007/s11423-015-9409-2 pdf

Cox, C., Reynolds, B., Schuchardt, A., & Schunn, C. D., (2016). How do secondary level biology teachers make sense of using mathematics in design-based lessons about a biological process? In L. Annetta & J. Minogue (Eds.), Connecting Science and Engineering Practices in Meaningful Ways (pp. 339-372). Heidelberg: Springer. pdf

Cox, C., Schuchardt, A., Reynolds, B., & Schunn, C. D. (2016). Using mathematics and engineering to solve problems in secondary level biology. Journal of STEM Education: Innovations and Research, 17(1), 6-14. pdf

Schuchardt, A., & Schunn, C. D. (2016). Modeling scientific processes with mathematics equations enhances student qualitative conceptual understanding and quantitative problem solving. Science Education, 100(2), 290–320. pdf

Crowell, A. J., & Schunn, C. D. (2016). Unpacking the relationship between science education and applied scientific literacy. Research in Science Education, 46(1), 129-140. 10.1007/s11165-015-9462-1. pdf

Bathgate, M.E., Crowell, A.J., Cannady, M., Dorph, R. & Schunn, C.D. (2015). The learning benefits of being willing and able to engage in scientific argumentation. International Journal of Science Education, 37(10), 1590-1612. 10.1080/09500693.2015.1045958 pdf

Kessler, A., Stein, M. K., & Schunn, C. (2015). Cognitive demand of model tracing tutor tasks: Conceptualizing and predicting how deeply students engage. Technology, Knowledge and Learning, 20(3), 317-337. pdf

Alfieri, L., Higashi, R., Shoop, R., & Schunn, C. D. (2015). Case studies of a robot-based game to shape interests and hone proportional reasoning skills. International Journal of STEM Education, 2:4. pdf

Peffer, M. E., Beckler, M. L., Schunn, C. D., Renken, M., & Revak, A. (2015). Science classroom inquiry (SCI) simulations: A novel method to scaffold science learning. PLoS ONE, 10(3): e0120638. link

Tekkumru-Kisa, M., Stein, M. K., & Schunn, C. D. (2015). A framework for analyzing cognitive demand and content-practices integration: Task analysis guide in science. Journal of Research in Science Teaching, 52(5), 659-685. pdf

Crowell, A. J., & Schunn, C. D. (2014). The context-specificity of scientifically literate action: key barriers and facilitators across contexts and contents. Public Understanding of Science, 23(6), 718-733. pdf

Cox, C., Reynolds, B., Schuchardt, A., & Schunn, C. D., (2014). How do secondary level biology teachers make sense of using mathematics in engineering design-based lessons about describing and predicting a biological process? In L. Annetta & J. Minogue (Eds.), Achieving science and technological literacy through engineering design practices. Springer.

Liu, A., Schunn, C. D., Flot, J., & Shoop, R. (2013). The role of physicality in rich programming environments. Computer Science Education, 23(4), 315-331. pdf

Apedoe, X. & Schunn, C. D. (2013). Strategies for Success: Uncovering what makes students successful in design and learning. Instructional science, 41, 773-791. pdf

Apedoe, X. & Ellefson, M. E., Schunn, C. D. (2012). Learning together while designing: Does group size make a difference? Journal of Science Education and Technology, 21(1), 83-94. pdf

Schunn, C. D., Silk, E. M., & Apedoe, X. S. (2012). Engineering in/&/or/for science education. In S. M. Carver and J. Shrager (Eds.), From Child to Scientist. Washington, DC: APA Press. pdf

Schunn, C.D., & Silk, E. M. (2011). Learning theories for engineering technology and engineering education. In M. Barak and M. Hacker (Eds.), Fostering Human Development through Engineering and Technology Education (p. 3–18). Sense Publishers. pdf

Singh, C., Moin, L., & Schunn, C. D. (2010). Introduction to physics teaching for science and engineering undergraduates. Journal of Physics Teacher Education Online, 5(3), 3-10. pdf

Silk, E. M., Higashi, R., Shoop, R., Schunn, C. D. (2010). Designing technology activities that teach mathematics. The Technology Teacher, 69(4), 21-27. pdf

Doppelt, Y. , Schunn, C. D., Silk, E., Mehalik, M., Reynolds, B., & Ward, E. (2009). Evaluating the impact of a facilitated learning community approach to professional development on teacher practice and student achievement. Research in Science & Technological Education, 27(3), 339-354. pdf

Singh, C., & Schunn, C. D. (2009). Connecting three pivotal concepts in K-12 science state standards and maps of conceptual growth to research in physics education. Journal of Physics Teacher Education Online, 5(2), 16-28. pdf

Steinberg, D., Patchan, M., Schunn, C. D., Landis, A. (2009). Determining adequate information for green building occupant training materials. Journal of Green Building, 4(3), 143-150. pdf

Steinberg, D., Patchan, M., Schunn, C. D., Landis, A. (2009). Developing a focus for green building occupant training materials. Journal of Green Building, 4(2), 175–184. pdf

Silk, E. M., Schunn, C. D., & Shoop, R. (2009). Synchronized robot dancing: Motivating efficiency and meaning in problem solving with robotics. Robot Magazine, 17, 42-45. pdf

Schunn, C. D. (2009). How Kids Learn Engineering: The Cognitive Science Perspective. The Bridge, 39(3), 32-37. pdf (in Hebrew)

Silk, E., Schunn, C. D., & Strand-Cary, M. (2009). The impact of an engineering design curriculum on science reasoning in an urban setting. Journal of Science Education and Technology, 18(3), 209-223. pdf

Reynolds, B., Mehalik, M. M., Lovell, M. R., & Schunn, C. D. (2009).Increasing student awareness of and interest in engineering as a career option through design-based learning. International Journal of Engineering Education, 25(1), 788-798. pdf

Schunn, C. D. (2008). Engineering educational design. Educational Designer, 1. html (in Hebrew)

Apedoe, X., Reynolds, B., Ellefson, M. R., & Schunn, C. D. (2008). Bringing engineering design into high school science classrooms: The heating/cooling unit. Journal of Science Education and Technology, 17(5), 454–465. pdf

Doppelt, Y. & Schunn, C. D. (2008). Identifying students' perceptions of the important classroom features affecting learning aspects of a design based learning environment? Learning Environments Research, 11(3), 195-209. pdf

Ellefson, M., Brinker, R., Vernacchio, V., & Schunn, C. D. (2008). Design-based learning for biology: Genetic engineering experience improves understanding of gene expression. Biochemistry and Molecular Biology Education, 36(4), 292–298. pdf

Doppelt, Y., Mehalik, M. M., Schunn, C. D., & Krysinski, D. (2008). Engagement and achievements in design-based learning. Journal of Technology Education, 19(2), 21-38. pdf

Mehalik, M. M., & Doppelt, Y., & Schunn, C. D. (2008). Middle-school science through design-based learning versus scripted inquiry: Better overall science concept learning and equity gap reduction. Journal of Engineering Education, 97(1), 71-85. pdf

Moin, L., Dorfield, J., & Schunn, C. D. (2005). Where Can We Find Future K-12 Science & Math Teachers? A Search by Academic Year, Discipline, and Achievement Level. Science Education, 89, 980-1006. pdf

Schunn, C. D., & Anderson, J. R. (2001). Science education in universities: Explorations of what, when, and how. In K. Crowley, C.D. Schunn, & T. Okada (Eds.), Designing for Science: Implications from Professional, Instructional, and Everyday Science. Mawah, NJ: Erlbaum. pdf

Web-based Peer Interaction

Patchan, M. M., Schunn, C. D., & Correnti, R. (In press). The nature of feedback: how feedback features affect students' implementation rate and quality of revisions. Journal of Educational Psychology. pdf

Schunn, C. D., Godley, A. J., & DiMartino, S. (2016). The reliability and validity of peer review of writing in high school AP English classes. Journal of Adolescent & Adult Literacy, 60(1), 13–23. pdf

Patchan, M. M., & Schunn, C. D. (2016). Understanding the benefits of receiving peer feedback: A case of matching ability in peer-review. Journal of Writing Research, 8(1). pdf

Patchan, M. M., & Schunn, C. D. (2015). Understanding the benefits of providing peer feedback: How students respond to peers' texts of varying quality. Instructional Science, 43(5), 591-614. 10.1007/s11251-015-9353-x. pdf

Abramovich, S., Schunn, C., D., Correnti, R. J. (2013). The role of evaluative metadata in an online teacher resource exchange. Educational Technology Research & Development, 61, 863-883. pdf

Abramovich, S., & Schunn, C. D. (2012). Studying teacher selection of resources in an ultra-large scale interactive system: Does metadata guide the way? Computers & Education, 58(1), 551-559. pdf

Patchan, M. M., Hawk, B. H., Stevens, C. A., & Schunn, C. D. (2013). The effects of skill diversity on commenting and revisions. Instructional Science, 41(2), 381-405. pdf

Xiong, W., Litman, D., & Schunn, C. D. (2012). Redesigning peer review interactions using computer tools. Journal of Writing Research, 4(2), 155-176. pdf

Lee, C. J., & Schunn, C.D. (2011). Social biases and solutions for procedural objectivity. Hypatia, 26(2), 352-373. pdf

Patchan, M. M., Schunn, C.D., & Clark, R. (2011). Writing in natural sciences: Understanding the effects of different types of reviewers on the writing process. Journal of Writing Research, 2(3), 365-393. pdf

Kaufman, J. H., & Schunn, C. D. (2011). Students' perceptions about peer assessment for writing: Their origin and impact on revision work. Instructional Science, 39(3), 387-406. pdf

Cho, K., & Schunn, C. D. (2010). Developing writing skills through students giving instructional explanations. In M. K. Stein & L. Kucan (Eds.), Instructional Explanations in the Disciplines: Talk, Texts and Technology. New York: Springer. pdf

Patchan, M. M., Charney, D., & Schunn, C. D. (2009). A validation study of students’ end comments: Comparing comments by students, a writing instructor, and a content instructor. Journal of Writing Research, 1(2), 124-152. pdf

Nelson, M. M., & Schunn, C. D. (2009). The nature of feedback: How different types of peer feedback affect writing performance. Instructional Science, 27(4), 375-401. pdf

Cho, K., Chung, T. R., King, W. R., & Schunn, C. D. (2008). Peer-based computer-supported knowledge refinement: An empirical investigation. Communications of the ACM, 51(3), 83-88. pdf

Cho, K., & Schunn, C. D. (2007). Scaffolded writing and rewriting in the discipline: A web-based reciprocal peer review system. Computers and Education, 48(3), 409-426. pdf

Cho, K., Schunn, C. D., & Charney, D. (2006). Commenting on writing: Typology and perceived helpfulness of comments from novice peer reviewers and subject matter experts. Written Communication, 23(3), 260-294. pdf

Cho, K., Schunn, C. D., & Wilson, R. (2006). Validity and reliability of scaffolded peer assessment of writing from instructor and student perspectives. Journal of Educational Psychology, 98(4), 891-901. pdf

Neuroscience of Complex Learning

Moss, J., & Schunn, C. D. (2015). Comprehension through explanation as the interaction of the brain’s coherence and cognitive control networks. Frontiers in Human Neuroscience, 9(562). doi: 10.3389/fnhum.2015.00562 link

Liu, A. S., Kallai, A. Y., Schunn, C. D., & Fiez, J. (2015). Using mental computation training to improve complex mathematical performance. Instructional Science, 43(4), 463-485. 10.1007/s11251-015-9350-0 pdf

Richey, J. E., Phillips, J. S., Schunn, C. D., & Schneider, W. (2014). Is the link from working memory to analogy causal? No analogy improvements following working memory training gains. PLOS One, 9(9), e106616. pdf

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. pdf

Kallai, A. Y., Schunn, C. D., & Fiez, J. A. (2012). Mental arithmetic activates analogic representations of internally generated sums. Neuropsychologia, 50, 2397–2407. pdf

Verstynen, T., Phillps, J., Braun, E., Schneider, W., & Schunn, C. D. (2012). Dynamic sensorimotor planning during long-term sequence learning: the role of variability, response chunking and planning errors. PLoS ONE, 7(10), e47336. pdf

Moss, J., Schunn C.D., Schneider, W., McNamara, D. S., & VanLehn, K. (2011). The neural correlates of strategic reading comprehension: cognitive control and discourse comprehension. NeuroImage, 58(2), 675-686. pdf

Engagement and Learning

Bathgate, M. E., & Schunn, C. D. (In press). Disentangling intensity from breadth of science interest: What predicts learning behaviors? Instructional Science.

Akiva, T., Kehoe, S., & Schunn, C. D. (In press). Are we ready for citywide learning? Examining the nature of within- and between-program pathways in a community-wide learning initiative. Journal of Community Psychology.

Sha, L., Schunn, C. D., Bathgate, M., & Ben-Eliyahu, A. (2016). Families support their children’s success in science learning by influencing interest and self-efficacy. Journal of Research in Science Teaching, 53(3), 450–472. 10.1002/tea.21251. pdf

Sha, L., Schunn, C. D. & Bathgate, M. (2015). Measuring choice to participate in optional science learning experiences during early adolescence. Journal of Research in Science Teaching, 52(5), 686-709. 10.1002/tea.21210 pdf

Bathgate, M., Schunn, C. D., Correnti, R. J. (2014). Children’s motivation towards science across contexts, manner-of-interaction, and topic. Science Education, 98(2), 189-215. pdf

Abramovich, S., Schunn, C. D., & Higashi, R. M (2013). Are badges useful in education?: It depends upon the type of badge and type of learner. Educational Technology Research & Development, 61(2), 217-232. pdf

Bathgate, M., Schunn, C. D. (2013). Exploring and encouraging metacognitive awareness in novice music students. In M. Stakelum (Ed.), Developing the Musician, SEMPRE Studies in the Psychology of Music series. Ashgate.

Bathgate, M. & Sims-Knight, J., & Schunn, C. D. (2012). Thoughts on thinking: Engaging novice music students in metacognition. Applied Cognitive Psychology, 26(3), 403-409. pdf

Human Computer Interaction & Learning

Patchan, M. M., Schunn, C. D., Sieg, W., & McLaughlin, D. (2016). The effect of blended instruction on accelerated learning. Technology, Pedagogy and Education, 25(3), 269-286.. 10.1080/1475939X.2015.1013977 pdf

Jang, J., & Schunn, C. D. (2014). A Framework for Unpacking Cognitive Benefits of Distributed Complex Visual Displays. Journal of Experimental Psychology: Applied, 20(3), 260-269. pdf

Kirschenbaum, S. S., Schunn, C. D., & Trafton, J. G. (2014). Visualizing uncertainty: The impact on performance. Human Factors, 56(3), 509-520. pdf

Jang, J., Trickett, S. B., Schunn, C. D., & Trafton, J. G. (2012). Unpacking the temporal advantage of distributing complex visual displays. International Journal of Human-Computer Studies, 70, 812-827. pdf

Jang, J., & Schunn, C. D. (2012). Performance benefits of spatially distributed vs. stacked information on integration tasks. Applied Cognitive Psychology, 26, 207-214. pdf

Jang, J., & Schunn, C. D. (2012). Physical design tools support and hinder innovative engineering design. Journal of Mechanical Design, 134(4), 041001-1-9. pdf

Jang, J., Schunn, C.D., & Nokes, T. J. (2011). Spatially distributed instructions improve learning outcomes and efficiency. Journal of Educational Psychology, 103(1), 60-72. pdf

MacWhinney, B., St. James, J., Schunn, C., Li, P., Schneider, W. (2001). STEP --- A system for teaching experimental psychology using E-Prime. Behavioral Research Methods, Instruments, & Computers, 33(2), 287-296. pdf

Strategy Use & Learning

Winsler, A., Abar, B., Feder, M., Rubio, D.A., & Schunn, C. D. (2007). Private speech and executive functioning among high functioning children with autistic spectrum disorders. Journal of Autism and Developmental Disabilities, 37(9), 1617-1635. pdf

Hansberger, J. T., Schunn, C. D., & Holt, R. W. (2006). Strategy variability: How too much of a good thing can hurt performance. Memory & Cognition, 34(8), 1652-1666. pdf

Schunn, C. D., McGregor, M., Saner, L. D. (2005). Expertise in ill-defined problem solving domains as effective strategy use. Memory & Cognition, 33(8), 1377-1387. pdf

Morris, B. J., & Schunn, C. D. (2004). Rethinking logical reasoning skills from a strategy perspective. In M. J. Roberts & E. Newton (Eds.), Methods of thought: Individual differences in reasoning strategies. Psychology Press. pdf

Schunn, C. D. (2002). Why motivation only sometimes affects base-rate sensitivity: The mediating role of representations on adaptive performance. In S. P. Shohov (Ed.), Advances in Psychology Research. New York: NovaScience. pdf

 Schunn, C. D., Lovett, M., & Reder, L. M. (2001). Awareness and working memory in strategy adaptivity. Memory & Cognition, 29(2), 256-266. pdf

Schunn, C. D., & Reder, L. M. (2001). Another source of individual differences: Strategy adaptivity to changing rates of success. Journal of Experimental Psychology: General, 130(1), 59-76. pdf

Lovett, M. C., & Schunn, C. D. (2000). The importance of frameworks for directing empirical questions: Reply to Goodie and Fantino. Journal of Experimental Psychology: General, 129(4), 453-456. pdf

Lovett, M. C., & Schunn, C. D. (1999). Task representations, strategy variability and base-rate neglect. Journal of Experimental Psychology: General, 128(2), 107-130. pdf

Reder, L. M., & Schunn, C. D. (1999). Bringing Together the psychometric and strategy worlds: Predicting adaptivity in a dynamic task. In D. Gopher & A. Koriat (Eds), Cognitive regulation of performance: Interaction of theory and application. Attention and Performance XVII.pdf

Schunn, C. D., & Reder, L. M. (1998). Individual differences in strategy adaptivity. In D. L. Medin (Ed.), The psychology of learning and motivation. pdf

Schunn, C. D., Reder, L. M., Nhouyvanisvong, A., Richards, D. R., & Stroffolino, P.J. (1997). To calculate or not calculate: A source activation confusion (SAC) model of problem-familiarity's role in strategy selection. Journal of Experimental Psychology: Learning, Memory, & Cognition, 23(1), 3-29. pdf

Reder, L., & Schunn, C. D. (1996). Metacognition does not imply awareness: Strategy choice is goverened by implicit learning and memory. In L. M. Reder (Ed.), Implicit memory and metacognition (pp. 45-78). Mahwah, NJ: Erlbaum. pdf

General Cognitive Science & Learning Science

Liu, A. S., & Schunn, C. D. (2016). The central questions of spatial cognition. To appear in S. Chipman (Ed.), The Oxford Handbook of Cognitive Science. Oxford University Press. pdf

Alfieri, L., Nokes, T. N., & Schunn, C. D. (2013). Learning through case comparisons: a meta-analytic review. Educational Psychologist, 48(2), 87-113. pdf

Altmann, E. M. & Schunn, C. D. (2012). Decay versus Interference: A new look at an old interaction. Psychological Science, 23(11), 1435-1437. pdf

Kong, X., Schunn, C. D., Wallstrom, G. L. (2010). High regularities in eye-movement patterns reveal the dynamics of visual working memory allocation mechanism. Cognitive Science, 34(2), 322-337. pdf

Nokes, T. J., Schunn, C. D., & Chi, M. T. H. (2010). Problem solving and human expertise.In E. Baker, B. McGraw, & P. Peterson (Eds.), International Encyclopedia of Education, Third Edition. Oxford, UK: Elsevier. pdf

Schunn, C. D. & Nelson, M. M. (2009). Expert-novice studies: An educational perspective. In Eric Anderman (Ed.), Psychology of Classroom Learning: An Encyclopedia. Detroit, MI: Macmillan Reference. pdf

Schunn, C. D., (2009). John Robert Anderson biography. In Eric Anderman (Ed.), Psychology of Classroom Learning: An Encyclopedia. Detroit, MI: Macmillan Reference.

Kong, X., & Schunn, C. D. (2007). Global vs. local information processing in visual/spatial problem solving: The case of traveling salesman problem. Cognitive Systems Research, 8(3), 192-207. pdf

Schunn, C. D., & Wallach, D. (2005). Evaluating goodness-of-fit in comparison of models to data. In W. Tack (Ed.), Psychologie der Kognition: Reden and Vorträge anlässlich der Emeritierung von Werner Tack (pp. 115-154). Saarbrueken, Germany: University of Saarland Press. pdf

Reder, L. M., Nhouyvansivong, A., Schunn, C. D., Ayers, M. S., Angstadt, P., Hiraki, K. (2000). A mechanistic account of the mirror effect for word frequency: A computational model of remember/know judgments in a continuous recognition paradigm. Journal of Experimental Psychology: Learning, Memory, & Cognition, 26(2), 294-320. pdf

Schunn, C. D., & Vera, A. H. (2004). Cross-cultural similarities in category structure. Thinking & Reasoning, 10(3), 273-287. pdf

Schunn, C. D., & Gray, W. D. (2002). Introduction to the special issue on computational cognitive modeling. Cognitive Systems Research, 3, 1-3. pdf

Duric, Z., Gray, W., Heishman, R., Li, F., Rosenfeld, A., Schoelles, M. J., Schunn, C., & Wechsler, H. (2002). Integrating perceptual and cognitive modeling for adaptive and intelligent human-computer interaction. Proceedings of the IEEE. 90(7), 1272-1289. pdf

Anderson, J. R., & Schunn, C. D. (2000). Implications of the ACT-R learning theory: No magic bullets. In R. Glaser (Ed.), Advances in instructional psychology: Educational design and cognitive science, Vol. 5 (pp. 1-33). Mahwah, NJ: Erlbaum. pdf

Schunn, C. D., & Klahr, D. (1998). Stances: Production systems. In W. Bechtel and G. Graham (Eds.), A Companion to Cognitive Science. Blackwell. pdf

Schunn, C. D., & Vera, A. H. (1995). Causality and the categorization of objects and events. Thinking & Reasoning, 1(3), 237-284. Full paper

 

 
Derry, S. J., Schunn, C. D., & Gernsbacher, M. A. (Eds.), (2005). Interdisciplinary Collaboration: An Emerging Cognitive Science. Mahwah, NJ: Erlbaum.

Schunn, C. D., Lovett, M. C., Munro, P., & Lebiere, C. (Eds.) (2004). Proceedings of the 2004 Sixth International Conference on Cognitive Modeling. Mahwah, NJ: Erlbaum.

Gray, W. D., & Schunn, C. D. (Eds.) (2002). Proceedings of the 24th Annual Meeting of the Cognitive Science Society. Mahwah, NJ: Erlbaum. pdf

Altmann, E. M., Cleeremans, A., Schunn, C. D., & Gray, W. D. (Eds.) (2001). Proceedings of the 2001 Fourth International Conference on Cognitive Modeling. Mahwah, NJ: Erlbaum.

Crowley, K., Schunn, C. D., & Okada, T. (Eds.). (2001). Designing for Science: Implications from Professional, Instructional, and Everyday Science. Mawah, NJ: Erlbaum. Table of contents

 

 

Conferences

Older published proceedings (not kept uptodate):

Titus, N., Schunn, C. D., Walhall, C., Chiu, G., & Ramani, K. (2008). What design processes predict better design outcomes? The case of robotics design teams. Proceedings of the Tools and Methods of Competitive Engineering Conference, Izmir, Turkey, (April, 2009). pdf

Schunn, C. D., Wong, T., Manzoul, W., Kamer, J., Harris, J., Trafton, J. G., & Trickett, S. B. (2007). Detecting and Resolving Informational Uncertainty in Complex Domains. In the Proceedings of the 29th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum.

Kong, X., & Schunn, C. D. (2007). Information seeking in complex problem solving. In the Proceedings of the 8th International Conference on Cognitive Modeling. Ann Arbor, MI.

Tollinger, I., Schunn, C. D., & Vera, A. H. (2006). What changes when a large team becomes more expert? In the Proceedings of the 28th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum.

Kong, X., & Schunn, C. D. (2006). Global vs. local information processing in problem solving: A study of the traveling salesman problem. In the Proceedings of the 7th International Conference on Cognitive Modeling. Trieste, Italy.

Harrison, A., & Schunn, C. D. (2004). The transfer of logically general scientific reasoning skills. In the Proceedings of the 26th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum.

Harrison, A., & Schunn, C. D. (2003). ACT-R/S: Look MA, No "Cognitive map"! In the Proceedings of the 5th International Conference on Cognitive Modeling. Bamberg, Germany: Universitäts-Verlag Bamberg.
Altmann, E. M., & Schunn, C. D. (2002). Integrating Decay and Interference: A New Look at an Old Interaction. In the Proceedings of the 24th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum.
Cho, K., Schunn, C. D., & Lesgold, A. (2002). Comprehension monitoring and regulation in collaboration. In the Proceedings of the 24th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum.
Morris, B. J., & Schunn, C. D. (2002). Logical Strategery. In the Proceedings of the 24th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum.
Trickett, S. B., Trafton, J. G., Schunn, C. D., & Harrison, A. (2001). "That's odd!" How scientists respond to anomalous data. In the Proceedings of the 23rd Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum.
Schunn, C. D., & Ngo, T. L. (2000). Motivating base-rate sensitivity (sometimes): Testing predictions of the RCCL framework. In the Proceedings of the 22nd Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum. Full paper
Schunn, C. D., & O'Malley, C. J. (2000). Now they see the point: Improving science reasoning through making predictions. In the Proceedings of the 22nd Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum. Full paper
Trickett, S. B., Fu, W.-T., Schunn, C. D., & Trafton, J. G. (2000). From dipsy-doodles to streaming motions: Changes in representation in the analysis of visual scientific data. In the Proceedings of the 22nd Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum. Full paper
Trickett, S. B., Trafton, J. G., & Schunn, C. D. (2000). Blobs, dipsy-doodles and other funky things: Framework anomalies in exploratory data analysis. In the Proceedings of the 22nd Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum. Full paper
 Schunn, C. D. (1999). The presence and absence of category knowledge in LSA. In the Proceedings of the 21st Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum. Abstract Full paper
Saner, L., & Schunn, C. D. (1999). Analogies out of the blue: When history seems to retell itself. In the Proceedings of the 21st Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum. Abstract Full paper
Best, B. J., Schunn, C. D., & Reder, L. M. (1998). Modeling adaptivity in a dynamic task. In M. A. Gernsbacher & S. J. Derry (Eds.), Proceedings of the 20th Annual Conference of the Cognitive Science Society. (p. 144-149) Mahwah, NJ: Erlbaum.
 Schunn, C. D., & Anderson, J. R. (1997). General and specific expertise in scientific reasoning. In the Proceedings of the 19th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum. Abstract
Reder, L. M., Nhouyvansivong, A., Schunn, C. D., Ayers, M. S., Angstadt, P., & Hiraki, K. (1997). Modeling the Mirror effect in a Continuous Remember/Know Paradigm. In the Proceedings of the 19th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum.
Schunn, C. D., & Klahr, D. (1996). The problem of problem spaces: When and how to go beyond a 2-space model of scientific discovery. Part of symposium on Building a theory of problem solving and scientific discovery: How big is N in N-space search? In the Proceedings of the 18th Annual Conference of the Cognitive Science Society. Abstract pdf
Schunn, C. D., & Klahr, D. (1995). A 4-space model of scientific discovery. In the Proceedings of the 17th Annual Conference of the Cognitive Science Society. Abstract pdf
Schunn, C. D., Okada, T., & Crowley, K. (1995). Is cognitive science truly interdisciplinary?: The case of interdisciplinary collaborations. In the Proceedings of the 17th Annual Conference of the Cognitive Science Society. Abstract
Schunn, C. D., & Klahr, D. (1993). Self- vs. other-generated hypothesis in scientific discovery. In the Proceedings of the 15th Annual Conference of the Cognitive Science Society (pp. 900-905). Hillsdale, NJ: Erlbaum. Abstract pdf
Schunn, C. D., & Klahr, D. (1992). Complexity management in a discovery task. In the Proceedings of the 14th Annual Conference of the Cognitive Science Society (pp.177-182). Hillsdale, NJ: Erlbaum.Abstract
Dunbar, K., & Schunn, C. D. (1990). The temporal nature of scientific discovery: The roles of priming and analogy. In Proceedings of the 12th Annual Conference of the Cognitive Science Society (pp. 93-100). Hillsdale, NJ: Erlbaum.