23 found
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  1. Social Biases and Solution for Procedural Objectivity.Carole J. Lee & Christian D. Schunn - 2011 - Hypatia 26 (2):352-73.
    An empirically sensitive formulation of the norms of transformative criticism must recognize that even public and shared standards of evaluation can be implemented in ways that unintentionally perpetuate and reproduce forms of social bias that are epistemically detrimental. Helen Longino’s theory can explain and redress such social bias by treating peer evaluations as hypotheses based on data and by requiring a kind of perspectival diversity that bears, not on the content of the community’s knowledge claims, but on the beliefs and (...)
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  2.  37
    The Growth of Multidisciplinarity in the Cognitive Science Society.Christian D. Schunn, Kevin Crowley & Takeshi Okada - 1998 - Cognitive Science 22 (1):107-130.
    In a case study of the growth of cognitive science, we analyzed the activities of the Cognitive Science Society with a particular emphasis on the multidisciplinary nature of the field. Analyses of departmental affiliations, training back‐grounds, research methodology, and paper citations suggest that the journal Cognitive Science and the Annual Meeting of the Cognitive Science Society are dominated by cognitive psychology and computer science, rather than being an equal division among the constituent disciplines of cognitive science. However, at many levels, (...)
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  3.  55
    Philosophy journal practices and opportunities for bias.Carole J. Lee & Christian D. Schunn - 2010 - American Philosophical Association Newsletter on Feminism and Philosophy.
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  4.  36
    Task representations, strategy variability, and base-rate neglect.Marsha C. Lovett & Christian D. Schunn - 1999 - Journal of Experimental Psychology: General 128 (2):107.
  5.  44
    The Generality/Specificity of Expertise in Scientific Reasoning.Christian D. Schunn & John R. Anderson - 1999 - Cognitive Science 23 (3):337-370.
    Previous research on scientific reasoning has shown that it involves a diverse set of skills. Yet, little is known about generality or domain specificity of those skills, an important issue in theories of expertise and in attempts to automate scientific reasoning skills. We present a study designed to test what kinds of skills psychologists actually use in designing and interpreting experiments and contrast expertise within a particular research area with general expertise at designing and interpreting experiments. The results suggest that (...)
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  6.  21
    What Should Cognitive Science Look Like? Neither a Tree Nor Physics.Christian D. Schunn - 2019 - Topics in Cognitive Science 11 (4):845-852.
    While pointing out important features of cognitive science, Núñez et al. (2019) also argue prematurely for the end of cognitive science. I discuss problematic analytic features in the application of hierarchical cluster analysis to journal citation data. On the conceptual side, I argue that the research programs framework of Lakatos may not be so wisely applied to cognitive science. Further, the diversity of structure in cognitive science departments may represent a rational, strategic adaptation by an interdisciplinary department to cognitive and (...)
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  7.  22
    The importance of iteration in creative conceptual combination.Joel Chan & Christian D. Schunn - 2015 - Cognition 145:104-115.
  8.  71
    A Social‐Cognitive Framework of Multidisciplinary Team Innovation.Susannah B. F. Paletz & Christian D. Schunn - 2010 - Topics in Cognitive Science 2 (1):73-95.
    The psychology of science typically lacks integration between cognitive and social variables. We present a new framework of team innovation in multidisciplinary science and engineering groups that ties factors from both literatures together. We focus on the effects of a particularly challenging social factor, knowledge diversity, which has a history of mixed effects on creativity, most likely because those effects are mediated and moderated by cognitive and additional social variables. In addition, we highlight the distinction between team innovative processes that (...)
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  9.  17
    Comprehension through explanation as the interaction of the brain’s coherence and cognitive control networks.Jarrod Moss & Christian D. Schunn - 2015 - Frontiers in Human Neuroscience 9.
  10.  45
    Another source of individual differences: strategy adaptivity to changing rates of success.Christian D. Schunn & Lynne M. Reder - 2001 - Journal of Experimental Psychology: General 130 (1):59.
  11.  93
    (1 other version)Effects of Trained Peer vs. Teacher Feedback on EFL Students’ Writing Performance, Self-Efficacy, and Internalization of Motivation.Ying Cui, Christian D. Schunn, Xiaosong Gai, Ying Jiang & Zhe Wang - 2021 - Frontiers in Psychology 12.
    This study investigated the longer-term impacts of trained peer feedback in comparison with teacher feedback on students’ writing development and writing motivation. Sections of an EFL writing course were randomly assigned to either teacher feedback or trained peer feedback conditions across two semesters. In the first semester, during their writing class, students either received training in how to implement peer feedback or simply studied models of writing. In the second semester, students either received teacher or peer feedback across multiple assignments. (...)
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  12. The effects of feedback elaboration on the giver of feedback.R. Wooley, C. Was, Christian D. Schunn & D. Dalton - unknown
     
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  13.  47
    Causality and the categorisation of objects and events.Christian D. Schunn & Alonso H. Vera - 1995 - Thinking and Reasoning 1 (3):237 – 284.
  14.  57
    Modeling adaptivity in a dynamic task.Bradley J. Best, Christian D. Schunn & Lynne M. Reder - 1998 - In Morton Ann Gernsbacher & Sharon J. Derry (eds.), Proceedings of the 20th Annual Conference of the Cognitive Science Society. Lawerence Erlbaum. pp. 144--159.
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  15.  55
    High Regularities in Eye‐Movement Patterns Reveal the Dynamics of the Visual Working Memory Allocation Mechanism.Xiaohui Kong, Christian D. Schunn & Garrick L. Wallstrom - 2010 - Cognitive Science 34 (2):322-337.
    With only two to five slots of visual working memory (VWM), humans are able to quickly solve complex visual problems to near optimal solutions. To explain the paradox between tightly constrained VWM and impressively complex human visual problem‐solving ability, we propose several principles for dynamic VWM allocation. In particular, we propose that complex visual information is represented in a temporal manner using only a few slots of VWM that include global and local visual chunks. We built a model of human (...)
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  16.  37
    Where can we find future K‐12 science and math teachers? a search by academic year, discipline, and academic performance level.Laura J. Moin, Jennifer K. Dorfield & Christian D. Schunn - 2005 - Science Education 89 (6):980-1006.
  17.  39
    The interplay of conflict and analogy in multidisciplinary teams.Susannah Bf Paletz, Christian D. Schunn & Kevin H. Kim - 2013 - Cognition 126 (1):1-19.
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  18.  61
    Cross-cultural similarities in category structure.Christian D. Schunn & Alonso H. Vera - 2004 - Thinking and Reasoning 10 (3):273 – 287.
    Categories, as mental structures, are more than simply sums of property frequencies. A number of recent studies have supported the view that the properties of categories may be organised along functional lines and possibly dependency structures more generally. The study presented here investigates whether earlier findings reflect something unique in the English language/North American culture or whether the functional structuring of categories is a more universal phenomenon. A population of English-speaking Americans was compared to a population of Cantonese-speaking Hong Kong (...)
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  19.  11
    Production Systems.Christian D. Schunn & David Klahr - 1998 - In George Graham & William Bechtel (eds.), A Companion to Cognitive Science. Blackwell. pp. 542–551.
    “Fiiirre!” If someone were to shout that while you were in the midst of reading this essay, you would, like most people, stop reading and look around the room for the source of the shout, or the fire itself. You would also consider whether the likelihood of a fire was sufficiently high to cause you to take appropriate action – for example, locate a fire extinguisher, call the fire department, or leave the room. Of course, you have not been sitting (...)
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  20. The psychology of uncertainty in scientific data analysis.Christian D. Schunn & J. Gregory Trafton - 2013 - In Gregory J. Feist & Michael E. Gorman (eds.), Handbook of the psychology of science. New York: Springer Pub. Company, LLC.
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  21.  21
    Why motivation only sometimes affects base-rate sensitivity: The mediating role of representations on adaptive performance.Christian D. Schunn - 2002 - In Serge P. Shohov (ed.), Advances in Psychology Research. Nova Science Publishers. pp. 14.
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  22.  43
    How Do Scientists Respond to Anomalies? Different Strategies Used in Basic and Applied Science.Susan Bell Trickett, J. Gregory Trafton & Christian D. Schunn - 2009 - Topics in Cognitive Science 1 (4):711-729.
    We conducted two in vivo studies to explore how scientists respond to anomalies. Based on prior research, we identify three candidate strategies: mental simulation, mental manipulation of an image, and comparison between images. In Study 1, we compared experts in basic and applied domains (physics and meteorology). We found that the basic scientists used mental simulation to resolve an anomaly, whereas applied science practitioners mentally manipulated the image. In Study 2, we compared novice and expert meteorologists. We found that unlike (...)
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  23.  36
    Puzzles and peculiarities: How scientists attend to and process anomalies during data analysis.Susan B. Trickett, Christian D. Schunn & J. Gregory Trafton - 2005 - In M. Gorman, R. Tweney, D. Gooding & A. Kincannon (eds.), Scientific and Technological Thinking. Erlbaum. pp. 97--118.