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| Autor/inn/en | Nosofsky, Robert M.; Donkin, Chris |
|---|---|
| Titel | Qualitative Contrast between Knowledge-Limited Mixed-State and Variable-Resources Models of Visual Change Detection |
| Quelle | In: Journal of Experimental Psychology: Learning, Memory, and Cognition, 42 (2016) 10, S.1507-1525 (19 Seiten)
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| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 0278-7393 |
| DOI | 10.1037/xlm0000268 |
| Schlagwörter | Short Term Memory; Probability; Models; Prediction; Bayesian Statistics; Statistical Analysis; Qualitative Research; Comparative Analysis; Visual Perception; College Students; Change; Stimuli; Cognitive Processes; Indiana |
| Abstract | We report an experiment designed to provide a qualitative contrast between knowledge-limited versions of mixed-state and variable-resources (VR) models of visual change detection. The key data pattern is that observers often respond "same" on big-change trials, while simultaneously being able to discriminate between same and small-change trials. The mixed-state model provides a natural account of this data pattern: With some probability, the observer is in a zero-memory state and is forced to guess. Thus, even on big-change trials, there is a significant probability that the observer will respond "same." On other trials, the observer retains memory for the probed study item, and these memory-based responses allow the observer to show above-chance discrimination between same and small-change trials. By contrast, we show that important versions of the VR models that we refer to as "knowledge-limited" models are stymied by this simple pattern of results. In agreement with Keshvari, van den Berg, and Ma (2012, 2013), alternative "knowledge-rich" VR models that employ ideal-observer decision rules provide a significant improvement over the knowledge-limited VR models; however, extant versions of the knowledge-rich VR models still fall short quantitatively compared to the descriptive mixed-state model. We discuss implications of the knowledge-rich assumptions that are posited in current versions of the VR models that have been used to fit change-detection data. (As Provided). |
| Anmerkungen | American Psychological Association. Journals Department, 750 First Street NE, Washington, DC 20002. Tel: 800-374-2721; Tel: 202-336-5510; Fax: 202-336-5502; e-mail: order@apa.org; Web site: http://www.apa.org |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2020/1/01 |
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