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Journal articles on the topic 'Category learning'

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1

Markman, Arthur B., and Brian H. Ross. "Category use and category learning." Psychological Bulletin 129, no. 4 (2003): 592–613. http://dx.doi.org/10.1037/0033-2909.129.4.592.

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2

Kersten, Alan W., and Dorrit Billman. "Event category learning." Journal of Experimental Psychology: Learning, Memory, and Cognition 23, no. 3 (1997): 638–58. http://dx.doi.org/10.1037/0278-7393.23.3.638.

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3

Ashby, F. Gregory, and W. Todd Maddox. "Human Category Learning." Annual Review of Psychology 56, no. 1 (2005): 149–78. http://dx.doi.org/10.1146/annurev.psych.56.091103.070217.

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4

Paradis, Rosemary D., Jinhong K. Guo, John Olden-Stahl, and Jack Moulton. "Cognitive Category Learning." Procedia Computer Science 12 (2012): 188–93. http://dx.doi.org/10.1016/j.procs.2012.09.052.

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5

Pollmann, Stefan. "Sensory category learning." Nature Human Behaviour 2, no. 7 (2018): 448–49. http://dx.doi.org/10.1038/s41562-018-0377-5.

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6

Richler, Jennifer J., and Thomas J. Palmeri. "Visual category learning." Wiley Interdisciplinary Reviews: Cognitive Science 5, no. 1 (2013): 75–94. http://dx.doi.org/10.1002/wcs.1268.

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7

Heffner, Christopher C. "Age and category structure in phonetic category learning." Journal of the Acoustical Society of America 155, no. 3_Supplement (2024): A269. http://dx.doi.org/10.1121/10.0027460.

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When learning new speech sound categories in a second language, listeners must decide which sounds belong to the same category and which belong to different categories. This learning process is contingent on perceptual systems that change across the lifespan, which may, in turn, make certain categories easier to learn depending on which systems are employed by learners. In the present study, learners across a variety of ages categorize speech sounds taken from German that vary in their category structure (i.e., the complexity of the categories being learned within the stimulus space). Particip
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8

Ward, Thomas B. "Whenis category learning holistic?" Memory & Cognition 16, no. 1 (1988): 85–89. http://dx.doi.org/10.3758/bf03197749.

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9

Holt, Lori L., Yafit Gabay, Frederic Dick, and Jason Zevin. "Incidental auditory category learning." Journal of the Acoustical Society of America 137, no. 4 (2015): 2386. http://dx.doi.org/10.1121/1.4920684.

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10

Goldstone, Robert L. "Unitization during category learning." Journal of Experimental Psychology: Human Perception and Performance 26, no. 1 (2000): 86–112. http://dx.doi.org/10.1037/0096-1523.26.1.86.

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11

Gabay, Yafit, Frederic K. Dick, Jason D. Zevin, and Lori L. Holt. "Incidental auditory category learning." Journal of Experimental Psychology: Human Perception and Performance 41, no. 4 (2015): 1124–38. http://dx.doi.org/10.1037/xhp0000073.

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12

Lassaline, Mary E., and Gregory L. Murphy. "Alignment and category learning." Journal of Experimental Psychology: Learning, Memory, and Cognition 24, no. 1 (1998): 144–60. http://dx.doi.org/10.1037/0278-7393.24.1.144.

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13

Djonlagic, I., A. Rosenfeld, D. Shohamy, C. Myers, M. Gluck, and R. Stickgold. "Sleep enhances category learning." Learning & Memory 16, no. 12 (2009): 751–55. http://dx.doi.org/10.1101/lm.1634509.

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14

Smith, J. David, Joseph I. Tracy, and Morgan J. Murray. "Depression and category learning." Journal of Experimental Psychology: General 122, no. 3 (1993): 331–46. http://dx.doi.org/10.1037/0096-3445.122.3.331.

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15

Bott, Lewis, Aaron B. Hoffman, and Gregory L. Murphy. "Blocking in category learning." Journal of Experimental Psychology: General 136, no. 4 (2007): 685–99. http://dx.doi.org/10.1037/0096-3445.136.4.685.

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16

Ashby, F. Gregory, and W. Todd Maddox. "Human category learning 2.0." Annals of the New York Academy of Sciences 1224, no. 1 (2010): 147–61. http://dx.doi.org/10.1111/j.1749-6632.2010.05874.x.

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17

Rosedahl, Luke A., Miguel P. Eckstein, and F. Gregory Ashby. "Retinal-specific category learning." Nature Human Behaviour 2, no. 7 (2018): 500–506. http://dx.doi.org/10.1038/s41562-018-0370-z.

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18

Ross, Brian H., Susan J. Perkins, and Patricia L. Tenpenny. "Reminding-based category learning." Cognitive Psychology 22, no. 4 (1990): 460–92. http://dx.doi.org/10.1016/0010-0285(90)90010-2.

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19

Chandrasekaran, Bharath, Han-Gyol Yi, and W. Todd Maddox. "Dual-learning systems during speech category learning." Psychonomic Bulletin & Review 21, no. 2 (2013): 488–95. http://dx.doi.org/10.3758/s13423-013-0501-5.

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20

Maddox, W. Todd, Brian D. Glass, Jeffrey B. O’Brien, J. Vincent Filoteo, and F. Gregory Ashby. "Category label and response location shifts in category learning." Psychological Research Psychologische Forschung 74, no. 2 (2009): 219–36. http://dx.doi.org/10.1007/s00426-009-0245-z.

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21

Maddox, W. Todd, J. Vincent Filoteo, Kelli D. Hejl, and A. David Ing. "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, no. 1 (2004): 227–45. http://dx.doi.org/10.1037/0278-7393.30.1.227.

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22

Richey, J. Elizabeth, Timothy J. Nokes-Malach, and Kara Cohen. "Collaboration facilitates abstract category learning." Memory & Cognition 46, no. 5 (2018): 685–98. http://dx.doi.org/10.3758/s13421-018-0795-7.

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23

Ell, Shawn W., and F. Gregory Ashby. "Dynamical trajectories in category learning." Perception & Psychophysics 66, no. 8 (2004): 1318–40. http://dx.doi.org/10.3758/bf03195001.

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24

Seger, Carol A., and Earl K. Miller. "Category Learning in the Brain." Annual Review of Neuroscience 33, no. 1 (2010): 203–19. http://dx.doi.org/10.1146/annurev.neuro.051508.135546.

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25

Goldwater, Micah B., Hilary J. Don, Moritz J. F. Krusche, and Evan J. Livesey. "Relational discovery in category learning." Journal of Experimental Psychology: General 147, no. 1 (2018): 1–35. http://dx.doi.org/10.1037/xge0000387.

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26

Pothos, Emmanuel M., and Nick Chater. "Unsupervised Categorization and Category Learning." Quarterly Journal of Experimental Psychology Section A 58, no. 4 (2005): 733–52. http://dx.doi.org/10.1080/02724980443000322.

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When people categorize a set of items in a certain way they often change their perceptions for these items so that they become more compatible with the learned categorization. In two experiments we examined whether such changes are extensive enough to change the unsupervised categorization for the items—that is, the categorization of the items that is considered more intuitive or natural without any learning. In Experiment 1 we directly employed an unsupervised categorization task; in Experiment 2 we collected similarity ratings for the items and inferred unsupervised categorizations using Pot
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27

patel, pooja, audrey zlatkin, andrew wismer, and corey bohil. "Awareness of category rule learning." Journal of Vision 18, no. 10 (2018): 402. http://dx.doi.org/10.1167/18.10.402.

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28

Ashby, F. Gregory, and Brian J. Spiering. "The Neurobiology of Category Learning." Behavioral and Cognitive Neuroscience Reviews 3, no. 2 (2004): 101–13. http://dx.doi.org/10.1177/1534582304270782.

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29

Ryherd, Kayleigh, and Nicole Landi. "Category Learning in Poor Comprehenders." Scientific Studies of Reading 23, no. 4 (2019): 305–16. http://dx.doi.org/10.1080/10888438.2019.1566908.

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30

Clapper, John P., and Gordon H. Bower. "Category invention in unsupervised learning." Journal of Experimental Psychology: Learning, Memory, and Cognition 20, no. 2 (1994): 443–60. http://dx.doi.org/10.1037/0278-7393.20.2.443.

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31

Kruschke, John K. "Base rates in category learning." Journal of Experimental Psychology: Learning, Memory, and Cognition 22, no. 1 (1996): 3–26. http://dx.doi.org/10.1037/0278-7393.22.1.3.

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32

Haskell, Todd R., Cade D. Mansfield, and Katherine M. Brewer. "Linguistic markedness and category learning." Language and Cognitive Processes 26, no. 8 (2011): 1022–54. http://dx.doi.org/10.1080/01690965.2010.503438.

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33

Lake, B. M., G. K. Vallabha, and J. L. McClelland. "Modeling Unsupervised Perceptual Category Learning." IEEE Transactions on Autonomous Mental Development 1, no. 1 (2009): 35–43. http://dx.doi.org/10.1109/tamd.2009.2021703.

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34

Haslam, C. "Preserved category learning in amnesia." Neurocase 3, no. 5 (1997): 337a—347. http://dx.doi.org/10.1093/neucas/3.5.337-a.

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35

de Sa, Virginia R., and Dana H. Ballard. "Category Learning Through Multimodality Sensing." Neural Computation 10, no. 5 (1998): 1097–117. http://dx.doi.org/10.1162/089976698300017368.

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Humans and other animals learn to form complex categories without receiving a target output, or teaching signal, with each input pattern. In contrast, most computer algorithms that emulate such performance assume the brain is provided with the correct output at the neuronal level or require grossly unphysiological methods of information propagation. Natural environments do not contain explicit labeling signals, but they do contain important information in the form of temporal correlations between sensations to different sensory modalities, and humans are affected by this correlational structur
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36

Smith, Edward E., and Murray Grossman. "Multiple systems of category learning." Neuroscience & Biobehavioral Reviews 32, no. 2 (2008): 249–64. http://dx.doi.org/10.1016/j.neubiorev.2007.07.009.

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37

Haslam, Catherine, Max Coltheart, and Michael Cook. "Preserved category learning in Amnesia." Neurocase 3, no. 5 (1997): 337–47. http://dx.doi.org/10.1080/13554799708411973.

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38

Estes, W. K. "Array models for category learning." Cognitive Psychology 18, no. 4 (1986): 500–549. http://dx.doi.org/10.1016/0010-0285(86)90008-3.

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39

Hammer, Rubi, Tomer Hertz, Shaul Hochstein, and Daphna Weinshall. "Category learning from equivalence constraints." Cognitive Processing 10, no. 3 (2008): 211–32. http://dx.doi.org/10.1007/s10339-008-0243-x.

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40

Rowlandson, Paul, and Adrian Simpson. "Interleaving in Mathematical Category Learning." Journal for Research in Mathematics Education 56, no. 3 (2025): 125–47. https://doi.org/10.5951/jresematheduc-2024-0055.

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On the basis of a substantial, robust, and well-replicated cognitive science research literature, interleaving has been recommended across a range of professional pedagogical works as an evidence-based strategy for mathematics teachers. This report first notes the conflation of interleaving and spacing effects underpinning those recommendations and the limitations of some laboratory-based research as grounding for practice, particularly given that no direct interleaving research involves mathematical concepts with school students. It then reports on two large classroom experiments aimed at rep
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41

Caplan, Spencer. "Word learning as category formation." PLOS One 20, no. 7 (2025): e0327615. https://doi.org/10.1371/journal.pone.0327615.

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A fundamental question in word learning is how, given only evidence about what objects a word has previously referred to, children are able to generalize to the correct class. How does a learner end up knowing that “poodle” only picks out a specific subset of dogs rather than the broader class and vice versa? Numerous phenomena have been identified in guiding learner behavior such as the “suspicious coincidence effect” (SCE)—that an increase in the sample size of training objects facilitates more narrow (subordinate) word meanings. While SCE seems to support a class of models based in statisti
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42

LIU, Zhi-Ya, Xiao-Hong SONG, and A. Seger Carol. "Six-year-old Children's Ability on Category Learning: Category Representation, Attention and Learning Strategy." Acta Psychologica Sinica 44, no. 5 (2013): 634–46. http://dx.doi.org/10.3724/sp.j.1041.2012.00634.

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43

MacGregor, James N. "Incremental category learning without external information: An algorithm for category-opening internal learning (COIL)." British Journal of Psychology 87, no. 1 (1996): 81–103. http://dx.doi.org/10.1111/j.2044-8295.1996.tb02578.x.

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44

Stanton, Roger D., and Robert M. Nosofsky. "Category number impacts rule-based and information-integration category learning: A reassessment of evidence for dissociable category-learning systems." Journal of Experimental Psychology: Learning, Memory, and Cognition 39, no. 4 (2013): 1174–91. http://dx.doi.org/10.1037/a0031670.

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45

Maddox, W. Todd, A. David Ing, and J. Scott Lauritzen. "Stimulus modality interacts with category structure in perceptual category learning." Perception & Psychophysics 68, no. 7 (2006): 1176–90. http://dx.doi.org/10.3758/bf03193719.

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46

Minda, John Paul, and J. David Smith. "Prototypes in category learning: The effects of category size, category structure, and stimulus complexity." Journal of Experimental Psychology: Learning, Memory, and Cognition 27, no. 3 (2001): 775–99. http://dx.doi.org/10.1037/0278-7393.27.3.775.

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47

Waldron, Elliott M., and F. Gregory Ashby. "The effects of concurrent task interference on category learning: Evidence for multiple category learning systems." Psychonomic Bulletin & Review 8, no. 1 (2001): 168–76. http://dx.doi.org/10.3758/bf03196154.

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48

Chin-Parker, Seth, and Brian H. Ross. "The effect of category learning on sensitivity to within-category correlations." Memory & Cognition 30, no. 3 (2002): 353–62. http://dx.doi.org/10.3758/bf03194936.

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49

Nopiyanto, Yahya Eko, Ari Sutisyana, Septian Raibowo, and Yarmani Yarmani. "Blended Learning with Jigsaw in Increasing Interest, Motivation, and Learning Outcomes in Sports Sociology Learning." Kinestetik : Jurnal Ilmiah Pendidikan Jasmani 5, no. 1 (2021): 26–34. http://dx.doi.org/10.33369/jk.v5i1.13905.

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The purpose of this study was to increase the interest, motivation, and learning outcomes of students in learning sports sociology by applying blended learning with the jigsaw method. The research method used was an action classroom with two cycles. The research subjects were students of the fifth semester with a total of 39 students. The results showed that in the pre-cycle students' interest in learning was in the low category, learning motivation was in the sufficient category. The results of cycle 1 showed that interest in learning student increases in the high category with a percentage o
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50

Kazan, Serap, and Hakan Karakoca. "Product Category Classification with Machine Learning." Sakarya University Journal of Computer and Information Sciences 2, no. 1 (2019): 18–27. http://dx.doi.org/10.35377/saucis.02.01.523139.

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