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Tytuł pozycji:

Visual category learning: Navigating the intersection of rules and similarity.

Tytuł :
Visual category learning: Navigating the intersection of rules and similarity.
Autorzy :
Hughes GI; Department of Psychology, Tufts University, Medford, MA, USA. .
Thomas AK; Department of Psychology, Tufts University, Medford, MA, USA.
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Źródło :
Psychonomic bulletin & review [Psychon Bull Rev] 2021 Jan 19. Date of Electronic Publication: 2021 Jan 19.
Publication Model :
Ahead of Print
Typ publikacji :
Journal Article; Review
Język :
English
Imprint Name(s) :
Publication: <2013-> : [New York : Springer]
Original Publication: Austin, TX : Psychonomic Society, Inc., c1994-
References :
Allen, S. W., & Brooks, L. R. (1991). Specializing the operation of an explicit rule. Journal of Experimental Psychology: General, 120(1), 3–19. (PMID: 10.1037/0096-3445.120.1.3)
Archambault, K. B. (2014). How stimulus similarity impacts spacing and interleaving effects in long-term memory (Doctoral Dissertation). University of Minnesota, Twin Cities, MN.
Ashby, F. G., Alfonso-Reese, L., Turken, A. U., & Waldron, E. M. (1998). A neuropsychological theory of multiple systems in category learning. Psychological Review, 105(3), 442–481. (PMID: 969742710.1037/0033-295X.105.3.4429697427)
Ashby, F. G., & Ell, S. W. (2001). The neurobiology of human category learning. Trends in Cognitive Sciences, 5(5), 204–210. (PMID: 1132326510.1016/S1364-6613(00)01624-711323265)
Ashby, F. G., Ell, S. W., & Waldron, E. M. (2003). Procedural learning in perceptual categorization. Memory & Cognition, 31(7), 1114–1125. (PMID: 10.3758/BF03196132)
Ashby, F. G., & Gott, R. E. (1988). Decision rules in the perception and categorization of multidimensional stimuli. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14(1), 33–53. (PMID: 29638942963894)
Ashby, F. G., & Soto, F. A. (2015). Multidimensional signal detection theory. In J. R. Busemeyer, Z. Wang, J. T. Townsend & A. Eidels (Eds.), The Oxford handbook of computational and mathematical psychology (pp. 13–34, Chapter xx, 399 Pages) Oxford University Press, New York, NY.
Ashby, F. G., & Valentin, V. V. (2017). Multiple systems of perceptual category learning: Theory and cognitive tests. In H. Cohen, & C. Lefebvre (Eds.), Handbook of categorization in cognitive science (2nd ed. ed., pp. 157–188, Chapter xxviii, 1233 Pages) Elsevier Academic Press, San Diego, CA.
Ashby, F. G., & Valentin V. V. (2018). The categorization experiment: Experimental design and data analysis. In E. J. Wagenmakers & J. T. Wixted (Eds.). Stevens handbook of experimental psychology and cognitive neuroscience, Fourth Edition, Volume Five: Methodology. New York, NY: Wiley. 307–348.
Ashby, F. G., & Waldron, E. M. (1999). On the nature of implicit categorization. Psychonomic Bulletin & Review, 6(3), 363–378. (PMID: 10.3758/BF03210826)
Baghdady, M., Carnahan, H., Lam, E., & Woods, N. (2014). Dental and dental hygiene students' diagnostic accuracy in oral radiology: Effect of diagnostic strategy and instructional method. Journal of Dental Education, 78(9), 1279–85. (PMID: 2517992410.1002/j.0022-0337.2014.78.9.tb05799.x25179924)
Biederman, I., & Shiffrar, M. M. (1987). Sexing day-old chicks: A case study and expert systems analysis of a difficult perceptual-learning task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13(4), 640–645.
Birnbaum, M. S., Kornell, N., Bjork, E. L., & Bjork, R. A. (2013). Why interleaving enhances inductive learning: The roles of discrimination and retrieval. Memory & Cognition, 41(3), 392–402. (PMID: 10.3758/s13421-012-0272-7)
Brooks, L. R. (1978). Non-analytic concept formation and memory for instances. In E. Rosch & B. B. Lloyd (Eds.), Cognition and Categorization (pp. 169–211). New York, NY: Wiley.
Brown, R. G., & Marsden, C. D. (1988). Internal versus external cues and the control of attention in Parkinson's disease. Brain, 111(2), 323–345. (PMID: 337813910.1093/brain/111.2.3233378139)
Burda, B. U., O'Connor, E. A., Webber, E. M., Redmond, N., & Perdue, L. A. (2017). Estimating data from figures with a web-based program: Considerations for a systematic review. Research Synthesis Methods, 8(3), 258–262. (PMID: 2826824110.1002/jrsm.123228268241)
Burns, B., & Shepp, B. E. (1988). Dimensional interactions and the structure of psychological space: The representation of hue, saturation, and brightness. Perception and Psychophysics, 43, 494–507. (PMID: 338064010.3758/BF032078853380640)
Carter, C.W. (1957). Quality control of visual characteristics. American quality control society: National convention transactions, 623–634.
Carvalho, P. F., & Goldstone, R. L. (2011). Sequential similarity and comparison effects in category learning. In L. Carlson, C. Holscher, & T. Shipley (Eds.), Proceedings of the 33rd conference of the Cognitive Science Society (pp. 2977–2982). Austin, TX: Cognitive Science Society.
Carvalho, P. F., & Goldstone, R. L. (2014a). Effects of interleaved and blocked study on delayed test of category learning generalization. Frontiers in Psychology, 5, 11.
Carvalho, P. F., & Goldstone, R. L. (2014b). Putting category learning in order: Category structure and temporal arrangement affect the benefit of interleaved over blocked study. Memory & Cognition, 42(3), 481–495. (PMID: 10.3758/s13421-013-0371-0)
Carvalho, P. F., & Goldstone, R. L. (2015a). What you learn is more than what you see: What can sequencing effects tell us about inductive category learning? Frontiers in Psychology, 6, 12.
Carvalho, P. F., & Goldstone, R. L. (2015b). The benefits of interleaved and blocked study: Different tasks benefit from different schedules of study. Psychonomic Bulletin & Review, 22(1), 281–288. (PMID: 10.3758/s13423-014-0676-4)
Carvalho, P. F., & Goldstone, R. L. (2017). The sequence of study changes what information is attended to, encoded, and remembered during category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(11), 1699–1719. (PMID: 2833350728333507)
Casale, M. B., Roeder, J. L., & Ashby, F. G. (2012). Analogical transfer in perceptual categorization. Memory & Cognition, 40(3), 434–449. (PMID: 10.3758/s13421-011-0154-4)
Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354–380. (PMID: 1671956610.1037/0033-2909.132.3.35416719566)
Chin-Parker, S., & Ross, B. H. (2002). The effect of category learning on sensitivity to within-category correlations. Memory & Cognition, 30(3), 353–362. (PMID: 10.3758/BF03194936)
Chin-Parker, S., & Ross, B. H. (2004). Diagnosticity and prototypicality in category learning: A comparison of inference learning and classification learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(1), 216–226. (PMID: 1473630814736308)
DeCaro, M. S., Thomas, R. D., & Beilock, S. L. (2008). Individual differences in category learning: Sometimes less working memory capacity is better than more. Cognition, 107(1), 284–294. (PMID: 1770736310.1016/j.cognition.2007.07.00117707363)
Delaney, P. F., Verkoeijen, P. P. J. L., & Spirgel, A. (2010). Spacing and testing effects: A deeply critical, lengthy, and at times discursive review of the literature. In B. H. Ross (Ed.), The psychology of learning and motivation: Advances in research and theory (vol. 53) (pp. 63–147, Chapter x, 398 Pages) Elsevier Academic Press, San Diego, CA.
Drury C. G. (1975). Inspection of sheet metal materials: Model and data. Human Factors, 17, 257–265. (PMID: 120547110.1177/0018720875017003051205471)
Dunn, J. C., Newell, B. R., & Kalish, M. L. (2012). The effect of feedback delay and feedback type on perceptual category learning: The limits of multiple systems. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38(4), 840–859. (PMID: 2274695222746952)
Dwyer, D. M., Mundy, M. E., & Honey, R. C. (2011). The role of stimulus comparison in human perceptual learning: Effects of distractor placement. Journal of Experimental Psychology: Animal Behavior Processes, 37, 300–307. (PMID: 2150092821500928)
Ebbinghaus, H. (1885). Über das gedächtnis: Untersuchungen zur experimentellen psychologie. Leipzig, Germany: Duncker & Humblot.
Edmunds, C. E. R., Milton, F., & Wills, A. J. (2015). Feedback can be superior to observational training for both rule-based and information-integration category structures. The Quarterly Journal of Experimental Psychology, 68(6), 1203–1222. (PMID: 2539797510.1080/17470218.2014.97887525397975)
Eglington, L. G., & Kang, S. H. K. (2017). Interleaved presentation benefits science category learning. Journal of Applied Research in Memory and Cognition, 6(4), 475–485. (PMID: 10.1016/j.jarmac.2017.07.005)
Eichenbaum, H., & Cohen, N. J. (2001). From conditioning to conscious recollection: Memory systems of the brain. New York, NY: Oxford University Press.
Eichenbaum, H., & Cohen, N. J. (2003). Review of from conditioning to conscious recollection. Journal of the International Neuropsychological Society, 9(3), 497–498. (PMID: 10.1017/S1355617703233154)
Ell, S. W., Ashby, F. G., & Hutchinson, S. (2012). Unsupervised category learning with integral-dimension stimuli. The Quarterly Journal of Experimental Psychology, 65(8), 1537–1562. (PMID: 2250686110.1080/17470218.2012.65882122506861)
Ell, S. W., Cosley, B., & McCoy, S. K. (2011). When bad stress goes good: Increased threat reactivity predicts improved category learning performance. Psychonomic Bulletin & Review, 18(1), 96–102. (PMID: 10.3758/s13423-010-0018-0)
Ell, S. W., Marchant, N. L., & Ivry, R. B. (2006). Focal putamen lesions impair learning in rule-based, but not information-integration categorization tasks. Neuropsychologia, 44(10), 1737–1751. (PMID: 1663549810.1016/j.neuropsychologia.2006.03.01816635498)
Ell, S. W., Smith, D. B., Peralta, G., & Hélie, S. (2017). The impact of category structure and training methodology on learning and generalizing within-category representations. Attention, Perception, & Psychophysics, 79(6), 1777–1794. (PMID: 10.3758/s13414-017-1345-2)
Evered, A., Walker, D., Watt, A., & Perham, N. (2014). Untutored discrimination training on paired cell images influences visual learning in cytopathology. Cancer Cytopathology, 122(3), 200–210. (PMID: 2424944110.1002/cncy.2137024249441)
Gagné, R. M. (1950). The effect of sequence of presentation of similar items on the learning of paired associates. Journal of Experimental Psychology, 40(1), 61–73. (PMID: 10.1037/h0060804)
Garner, W. R. (1976). Interaction of stimulus dimensions in concept and choice processes. Cognitive Psychology, 8, 98–123. (PMID: 10.1016/0010-0285(76)90006-2)
Goldstone, R. L. (1994). The role of similarity in categorization: Providing a groundwork. Cognition, 52(2), 125–157. (PMID: 792420110.1016/0010-0277(94)90065-57924201)
Goldstone, R. L. (1996). Isolated and interrelated concepts. Memory & Cognition, 24(5), 608–628. (PMID: 10.3758/BF03201087)
Goldstone, R. L., Steyvers, M., & Rogosky, B. J. (2003). Conceptual interrelatedness and caricatures. Memory & Cognition, 31(2), 169–180. (PMID: 10.3758/BF03194377)
Grum, C. M., & Lynch, J. P. III (1992). Chest radiographic findings in cystic fibrosis. Seminars in Respiratory Infections, 7(3):193–209. (PMID: 14755431475543)
Guzman-Munoz, F. (2017). The advantage of mixing examples in inductive learning: A comparison of three hypotheses. Educational Psychology, 37(4), 421–437. (PMID: 10.1080/01443410.2015.1127331)
Hammer, R., Bar-Hillel, A., Hertz, T., Weinshall, D., & Hochstein, S. (2008). Comparison processes in category learning: From theory to behavior. Brain Research, 1225, 102–118. (PMID: 1861416010.1016/j.brainres.2008.04.079)
Hatala, R., Brooks, M., & Norman, L. (2003). Practice Makes Perfect: The Critical Role of Mixed Practice in the Acquisition of ECG Interpretation Skills. Advances in Health Sciences Education, 8(1), 17–26. (PMID: 1265216610.1023/A:102268740438012652166)
Hélie, S., Shamloo, F., & Ell, S. W. (2017). The effect of training methodology on knowledge representation in categorization. PLoS ONE, 12(8), 23. (PMID: 10.1371/journal.pone.0183904)
Hélie, S., Shamloo, F., & Ell, S. W. (2018). The impact of training methodology and category structure on the formation of new categories from existing knowledge. Psychological Research. 84, 990–1005 (2020).
Higgins, E. J. (2017). The complexities of learning categories through comparisons. In B. H. Ross (Ed.), The psychology of learning and motivation; the psychology of learning and motivation (pp. 43–77, Chapter x, 310 Pages) Elsevier Academic Press, San Diego, CA.
Higgins, E. J., & Ross, B. H. (2011). Comparisons in category learning: How best to compare for what. In L. Carlson, C. Holscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society. Austin: Cognitive Science Society.
Hoffman, A. B., & Rehder, B. (2010). The costs of supervised classification: The effect of learning task on conceptual flexibility. Journal of Experimental Psychology: General, 139(2), 319–340. (PMID: 10.1037/a0019042)
Jacoby, L. L., & Brooks, L. R. (1984). Nonanalytic cognition: Memory, perception and concept learning. In G. H. Bower (Ed.), The psychology of learning and motivation, Vol. 18, (pp. 1–43). New York, NY: Academic Press.
Johansen, M. K., & Kruschke, J. K. (2005). Category representation for classification and feature inference. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(6), 1433–1458. (PMID: 1639305616393056)
Jones, E. L., & Ross, B. H. (2011). Classification versus inference learning contrasted with real-world categories. Memory & Cognition, 39(5), 764–777. (PMID: 10.3758/s13421-010-0058-8)
Kang, S. H. K., & Pashler, H. (2012). Learning painting styles: Spacing is advantageous when it promotes discriminative contrast. Applied Cognitive Psychology, 26(1), 97–103. (PMID: 10.1002/acp.1801)
Kéri, S. (2003). The cognitive neuroscience of category learning. Brain Research Reviews, 43(1), 85–109. (PMID: 1449946410.1016/S0165-0173(03)00204-2)
Kok, E. M., de Bruin, Anique B. H., Robben, S. G. F., & van Merriënboer, Jeroen J. G. (2013). Learning radiological appearances of diseases: Does comparison help? Learning and Instruction, 23, 90–97. (PMID: 10.1016/j.learninstruc.2012.07.004)
Kornell, N., & Bjork, R. A. (2008). Learning concepts and categories: Is spacing the "enemy of induction?". Psychological Science, 19(6), 585–592. (PMID: 1857884910.1111/j.1467-9280.2008.02127.x)
Kornell, N., Castel, A. D., Eich, T. S., & Bjork, R. A. (2010). Spacing as the friend of both memory and induction in young and older adults. Psychology and Aging, 25(2), 498–503. (PMID: 2054543510.1037/a0017807)
Kost, A. S., Carvalho, P. F., & Goldstone, R. L. (2015). Can you repeat that? The effect of item repetition on interleaved and blocked study. Proceedings of the 37th Annual Conference of the Cognitive Science Society, 1189–1194.
Kurtz, K. H., & Hovland, C. I. (1956). Concept learning with differing sequences of instances. Journal of Experimental Psychology, 51(4), 239–243. (PMID: 1330687110.1037/h0040295)
Lancaster, M. E., Shelhamer, R., & Homa, D. (2013). Category inference as a function of correlational structure, category discriminability, and number of available cues. Memory & Cognition, 41(3), 339–353. (PMID: 10.3758/s13421-012-0271-8)
Lavis, Y., & Mitchell, C. (2006). Effects of preexposure on stimulus discrimination: An investigation of the mechanisms responsible for human perceptual learning. Quarterly Journal of Experimental Psychology, 59, 2083–2101. (PMID: 10.1080/17470210600705198)
Maddox, T. W., Pacheco, J., Reeves, M., Zhu, B., & Schnyer, D. M. (2010). Rule-based and information-integration category learning in normal aging. Neuropsychologia, 48(10), 2998–3008. (PMID: 20547171291422010.1016/j.neuropsychologia.2010.06.008)
Maddox, W. T., Ashby, F. G., & Bohil, C. J. (2003). Delayed feedback effects on rule-based and information-integration category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29(4), 650–662. (PMID: 1292486512924865)
Maddox, W. T., & Filoteo, J. V. (2011). Stimulus range and discontinuity effects on information-integration category learning and generalization. Attention, Perception, & Psychophysics, 73(4), 1279–1295. (PMID: 10.3758/s13414-011-0101-2)
Maddox, W. T., Filoteo, J. V., Hejl, K. D., & Ing, A. D. (2004). Category number impacts rule-based but not information-integration category learning: Further evidence for dissociable category-learning systems. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(1), 227–245. (PMID: 1473630914736309)
Maddox, W. T., Filoteo, J. V., Lauritzen, J. S., Connally, E., & Hejl, K. D. (2005). Discontinuous categories affect information-integration but not rule-based category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(4).
Maddox, W. T., & Ing, A. D. (2005). Delayed feedback disrupts the procedural-learning system but not the hypothesis-testing system in perceptual category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(1), 100–107. (PMID: 1564190815641908)
Maddox, W. T., Lauritzen, J. S., & Ing, A. D. (2007). Cognitive complexity effects in perceptual classification are dissociable. Memory & Cognition, 35(5), 885–894. (PMID: 10.3758/BF03193463)
Maddox, W. T., Love, B. C., Glass, B. D., & Filoteo, J. V. (2008). When more is less: Feedback effects in perceptual category learning. Cognition, 108(2), 578–589. (PMID: 18455155246750910.1016/j.cognition.2008.03.010)
Maddox, W. T., Zeithamova, D., & Schnyer, D. M. (2009). Dissociable processes in classification: Implications from sleep deprivation. Military Psychology, 21, S55–S61. (PMID: 10.1080/08995600802554649)
Mareschal, D., Quinn, P. C., & Lea, S. E. G. (Eds.). (2010). The making of human concepts. New York, NY: Oxford University Press.
Meagher, B. J., Carvalho, P. F., Goldstone, R. L., & Nosofsky, R. M. (2017). Organized simultaneous displays facilitate learning of complex natural science categories. Psychonomic Bulletin & Review, 24(6), 1987–1994. (PMID: 10.3758/s13423-017-1251-6)
Melara, R. D., Marks, L. E., & Potts, B. C. (1993). Primacy of dimensions in color perception. Journal of Experimental Psychology: Human Perception and Performance, 19, 1082–1104. (PMID: 82288418228841)
Minda, J. P., Desroches, A. S., & Church, B. A. (2008). Learning rule-described and non-rule-described categories: A comparison of children and adults. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34(6), 1518–1533. (PMID: 1898041118980411)
Minda, J. P., & Miles, S. J. (2010). The influence of verbal and nonverbal processing on category learning. In B. H. Ross (Ed.), The psychology of learning and motivation: Advances in research and theory (vol. 52) (pp. 117–162, Chapter x, 396 Pages) Elsevier Academic Press, San Diego, CA.
Mitchell, C., Nash, S., & Hall, G. (2008). The intermixed-blocked effect in human perceptual learning is not the consequence of trial spacing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34, 237–242. (PMID: 1819406618194066)
Monteiro, S., Melvin, L., Manolakos, J., Patel, A., & Norman, G. (2017). Evaluating the effect of instruction and practice schedule on the acquisition of ECG interpretation skills. Perspectives on medical education, 6(4), 237–245. (PMID: 28744821554289610.1007/s40037-017-0365-x)
Mundy, M. E., Honey, R. C., & Dwyer, D. M. (2007). Simultaneous presentation of similar stimuli produces perceptual learning in human picture processing. Journal of Experimental Psychology: Animal Behavior Processes, 33(2), 124–138. (PMID: 1746996117469961)
Mundy, M. E., Honey, R. C., & Dwyer, D. M. (2009). Superior discrimination between similar stimuli after simultaneous exposure. The Quarterly Journal of Experimental Psychology, 62(1), 18–25. (PMID: 1872027510.1080/1747021080224061418720275)
Nelson, D. G. K. (1984). The effect of intention on what concepts are acquired. Journal of Verbal Learning & Verbal Behavior, 100, 734–759. (PMID: 10.1016/S0022-5371(84)90442-0)
Noh, S. M., Yan, V. X., Bjork, R. A., & Maddox, W. T. (2016). Optimal sequencing during category learning: Testing a dual-learning systems perspective. Cognition, 155, 23–29. (PMID: 2734348010.1016/j.cognition.2016.06.00727343480)
Nosofsky, R. M. (2011). The generalized context model: An exemplar model of classification. In E. M. Pothos, & A. J. Wills (Eds.), Formal approaches in categorization; formal approaches in categorization (pp. 18–39, Chapter xii, 336 Pages) Cambridge University Press, New York, NY.
Nosofsky, R. M., & Palmeri, T. J. (1998). A rule-plus-exception model for classifying objects in continuous-dimension spaces. Psychonomic Bulletin & Review, 5(3), 345–369. (PMID: 10.3758/BF03208813)
Nosofsky, R. M., Palmeri, T. J., & McKinley, S. C. (1994). Rule-plus-exception model of classification learning. Psychological Review, 101(1), 53–79. (PMID: 812196010.1037/0033-295X.101.1.538121960)
Nosofsky, R. M., Sanders, C. A., Gerdom, A., Douglas, B. J., & McDaniel, M. A. (2017). On learning natural-science categories that violate the family-resemblance principle. Psychological Science, 28(1), 104–114. (PMID: 2787218010.1177/095679761667563627872180)
Palmeri, T., Gauthier, I. Visual object understanding. Nat Rev Neurosci 5, 291–303 (2004). (PMID: 1503455410.1038/nrn136415034554)
Patalano, A. L., Smith, E. E., Jonides, J., & Koeppe, R. A. (2001). PET evidence for multiple strategies of categorization. Cognitive, Affective & Behavioral Neuroscience, 1(4), 360–370. (PMID: 10.3758/CABN.1.4.360)
Poldrack, R. A., Clark, J., Pare-Blagoev, E., Shohamy, D., Moyano, J. C., Myers, C., & Gluck, M. (2001). Interactive memory systems in the human brain. Nature, 414(6863), 546–550. (PMID: 1173485510.1038/3510708011734855)
Poldrack, R. A., & Packard, M. G. (2003). Competition among multiple memory systems: Converging evidence from animal and human brain studies. Neuropsychologia, 41(3), 245–251. (PMID: 1245775010.1016/S0028-3932(02)00157-412457750)
Raven, P., & Johnson, G. B. (2002). Biology. New York, NY: McGraw-Hill.
Roads, B., Xu, B., Robinson, J., & Tanaka, J. (2018). The easy-to-hard training advantage with real-world medical images. Cognitive Research: Principles and Implications, 3(1), 1–13.
Roediger, H. L., & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249–255. (PMID: 1650706610.1111/j.1467-9280.2006.01693.x16507066)
Rosch, E., Mervis, C.B., Gray, W., Johnson, D., & Boyes-Braem, P. (1976). Basic objects in natural categories. Cognitive Psychology, 7, 573–605. (PMID: 10.1016/0010-0285(75)90024-9)
Rozenshtein, A., Pearson, G. D., Yan, S. X., Liu, A. Z., & Toy, D. (2016). Effect of massed versus interleaved teaching method on performance of students in radiology. Journal of the American College of Radiology, 13(8), 979–984. . (PMID: 2723628610.1016/j.jacr.2016.03.03127236286)
Sajjad, R., & Marsden, J. (2008). ABC of Skin Cancer. Malden, MA. Blackwell Publishing.
Sana, F., Yan, V. X., Kim, J. A., Bjork, E. L., & Bjork, R. A. (2018). Does working memory capacity moderate the interleaving benefit? Journal of Applied Research in Memory and Cognition, 7(3), 361–369. (PMID: 10.1016/j.jarmac.2018.05.005)
Searston, R. A., & Tangen, J. M. (2017). The emergence of perceptual expertise with fingerprints over time. Journal of Applied Research in Memory and Cognition, 6(4), 442–451. (PMID: 10.1016/j.jarmac.2017.08.006)
Shah, R., Sibbald, M., Jaffer, N., Probyn, L., & Cavalcanti, R. B. (2016). Online self-study of chest X-rays shows no difference between blocked and mixed practice. Medical Education, 50, 540–549. (PMID: 2707244310.1111/medu.1299127072443)
Sorensen, L. J., & Woltz, D. J. (2016). Blocking as a friend of induction in verbal category learning. Memory & Cognition, 44(7), 1000–1013. (PMID: 10.3758/s13421-016-0615-x)
Smith, J. D., Tracy, J. I., & Murray, M. J. (1993). Depression and category learning. Journal of Experimental Psychology: General, 122, 331–346. (PMID: 10.1037/0096-3445.122.3.331)
Smith, J. D., Boomer, J., Zakrzewski, A. C., Roeder, J. L., Church, B. A., & Ashby, F. G. (2014). Deferred feedback sharply dissociates implicit and explicit category learning. Psychological Science, 25(2), 447–457. (PMID: 2433560510.1177/095679761350911224335605)
Smith, J. D., & Shapiro, J. H. (1989). The occurrence of holistic categorization. Journal of Memory and Language, 28(4), 386–399. (PMID: 10.1016/0749-596X(89)90018-1)
Spiering, B. J., & Ashby, F. G. (2008a). Initial training with difficult items facilitates information integration, but not rule-based category learning. Psychological Science, 19(11), 1169–1177. (PMID: 19076490260528210.1111/j.1467-9280.2008.02219.x)
Spiering, B. J., & Ashby, F. G. (2008b). Response processes in information-integration category learning. Neurobiology of Learning and Memory, 90(2), 330–338. (PMID: 18550397256267910.1016/j.nlm.2008.04.015)
Squire, L. R. (2004). Memory systems of the brain: A brief history and current perspective. Neurobiology of Learning and Memory, 82(3), 171–177. (PMID: 1546440210.1016/j.nlm.2004.06.00515464402)
Sweller, N., & Hayes, B. K. (2010). More than one kind of inference: Re-examining what's learned in feature inference and classification. The Quarterly Journal of Experimental Psychology, 63(8), 1568–1589. (PMID: 2037322810.1080/1747021090343854720373228)
Tangen, J. M., Thompson, M. B., & McCarthy, D. J. (2011). Identifying fingerprint expertise. Psychological Science, 22(8), 995–997. (PMID: 2172494810.1177/095679761141472921724948)
Taylor, E. G., & Ross, B. H. (2009). Classifying partial exemplars: Seeing less and learning more. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35(5), 1374–1380. (PMID: 1968603119686031)
Verkoeijen, P. P. J. L., & Bouwmeester, S. (2014). Is spacing really the "friend of induction?" Frontiers in Psychology, 5, 259. (PMID: 24744742397833410.3389/fpsyg.2014.00259)
Wahlheim, C. N., Dunlosky, J., & Jacoby, L. L. (2011). Spacing enhances the learning of natural concepts: An investigation of mechanisms, metacognition, and aging. Memory & Cognition, 39(5), 750–763. (PMID: 10.3758/s13421-010-0063-y)
Waldron, E. M., & Ashby, F. G. (2001). The effects of concurrent task interference on category learning: Evidence for multiple category learning systems. Psychonomic Bulletin & Review, 8(1), 168–176. (PMID: 10.3758/BF03196154)
Ward, T. B. (1988). When is category learning holistic? A reply to Kemler Nelson. Memory & Cognition, 16, 85–89. (PMID: 10.3758/BF03197749)
Weitnauer, E., Carvalho, P. F., Goldstone, R. L., & Ritter, H. (2013). Grouping by similarity helps concept learning. Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 3747– 3752). Austin, TX: Cognitive Science Society.
Wright, E. G. (2017). Combining blocked and interleaved presentation during passive study and its effect on inductive learning (Master Thesis). University of Dayton, Dayton, OH.
Yan, V. X., Bjork, E. L., & Bjork, R. A. (2016). On the difficulty of mending metacognitive illusions: A priori theories, fluency effects, and misattributions of the interleaving benefit. Journal of Experimental Psychology: General, 145, 918 –933. (PMID: 10.1037/xge0000177)
Yan, V. X., Soderstrom, N. C., Seneviratna, G. S., Bjork, E. L., & Bjork, R. A. (2017). How should exemplars be sequenced in inductive learning? Empirical evidence versus learners’ opinions. Journal of Experimental Psychology: Applied, 23(4), 403–416. (PMID: 2881647228816472)
Yamauchi, T., Love, B. C., & Markman, A. B. (2002). Learning nonlinearly separable categories by inference and classification. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28(3), 585–593. (PMID: 1201851012018510)
Yamauchi, T., & Markman, A. B. (1998). Category learning by inference and classification. Journal of Memory and Language, 39(1), 124–148. (PMID: 10.1006/jmla.1998.2566)
Yamauchi, T., & Markman, A. B. (2000a). Inference using categories. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26(3), 776–795. (PMID: 1085543110855431)
Yamauchi, T., & Markman, A. B. (2000b). Learning categories composed of varying instances: The effect of classification, inference, and structural alignment. Memory & Cognition, 28(1), 64–78. (PMID: 10.3758/BF03211577)
Zeithamova, D., & Maddox, W. T. (2006). Dual-task interference in perceptual category learning. Memory & Cognition, 34(2), 387–398. (PMID: 10.3758/BF03193416)
Zulkiply, N. (2015). The role of bottom-up vs. top-down learning on the interleaving effect in category induction. Pertanika Journal of Social Science & Humanities, 23, 933–944.
Zulkiply, N., & Burt, J. S. (2013a). The exemplar interleaving effect in inductive learning: Moderation by the difficulty of category discriminations. Memory & Cognition, 41(1), 16–27. (PMID: 10.3758/s13421-012-0238-9)
Zulkiply, N., & Burt, J. S. (2013b). Inductive learning: Does interleaving exemplars affect long-term retention? Malaysian Journal of Learning and Instruction, 10, 133–155.
Contributed Indexing :
Keywords: Interleaving; Visual categorization
Entry Date(s) :
Date Created: 20210119 Latest Revision: 20210119
Update Code :
20210210
DOI :
10.3758/s13423-020-01838-0
PMID :
33464550
Czasopismo naukowe
Visual categorization is fundamental to expertise in a wide variety of disparate domains, such as radiology, art history, and quality control. The pervasive need to master visual categories has served as the impetus for a vast body of research dedicated to exploring how to enhance the learning process. The literature is clear on one point: no category learning technique is always superior to another. In the present review, we discuss how two factors moderate the efficacy of learning techniques. The first, category similarity, refers to the degree of featural overlap of exemplars. The second moderator, category type, concerns whether the features that define category membership can be mastered through learning processes that are implicit/non-verbal (information-integration categories) or explicit/verbal (rule-based categories). The literature on each moderator has been conducted almost entirely in isolation, such that their potential interaction remains underexplored. We address this gap in the literature by reviewing empirical and theoretical evidence that these two moderators jointly influence the efficacy of learning techniques.

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