Psychological Development and Education ›› 2016, Vol. 32 ›› Issue (3): 324-329.doi: 10.16187/j.cnki.issn1001-4918.2016.03.09

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The Influences of Working Memory Capacity and Content Relevance on Category Learning

XING Qiang, XIA Jingjing, WANG Caiyan   

  1. Department of Psychology, Guangzhou University, Guangzhou 510006
  • Online:2016-05-15 Published:2016-05-15

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Abstract: Category learning is a process in which human beings classify perceptual simulations and acquire category knowledge by classification learning. 2(working memory capacity:high, low)×4(content relevance:direction, width, brightness, control) between-subject experiment were designed to explore the effects of working memory capacity and content relevance on category learning by two experiments.The results showed that:(1) Only under the condition of high capacity, focusing on the related dimensions can improve the classification performance in the rule-based category learning; (2) no matter what the working capacity is high or low, it can receive better classification performance if participants focus on the related dimensions of the information-integration category learning.

Key words: category learning, working memory capacity, dimension relevance, rule-based category learning, information integration category learning

Ashby, F. G., Alfonso-Reese, L. A., Turken, U., & Waldron, E. M. (1998). A neuropsychological theory of multiple systems in category learning. Psychological Review, 105(3),442-481.

Ashby, F. G., & Crossley, M. J. (2010). Interactions between declarative and procedural-learning categorization systems. Neurobiology of Learning and Memory, 94(1), 1-12.

Ashby, F. G., Ell, S. W., & Waldron, E. M. (2003). Procedural learning in perceptual categorization. Memory & Cognition, 31(7),1114-1125.

Ashby, F. G., & Maddox, W. T. (1990). Integrating information from separable psychological dimensions. Journal of Experimental Psychology:Human Perception and Performance, 16(3), 598-612.

Ashby, F. G., & Waldron, E. M. (2000). The neuropsychological bases of category learning. Current Directions in Psychological Science,9(1), 10-14.

Conway, A. R. A., Kane, M. J., Bunting, M. F., Hambrick, D. Z., Wilhelm, O., & Engle, R. W. (2005). Working memory span tasks:A methodological review and user's guide. Psychonomic Bulletin &Review, 12(5), 769-786.

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.

Filoteo, J. V., Lauritzen, S., & Maddox, W. T. (2010). Removing the frontal lobes:The effects of engaging executive functions on perceptual category learning. Psychological Science, 21(3), 415-423.

Grimm, L. R., & Maddox,W. T. (2013). Differential impact of relevant and irrelevant dimension primes on rule-based and information-integration category learning. Acta physiological, 144(3), 530-537.

Johansen, M. K., & Palmeri, T. J. (2002). Are there representational shifts during category learning. Cognitive Psychology,45(4), 482-553.

Kane, M. J., Bleckley, M. K., Conway, R. A., & Engle, R. W. (2001). A controlled-attention view of working-memory capacity. Journal of Experimental Psychology:General, 130(2), 169-183.

Kane, M. J., & Engle, R. W. (2000). Working-memory capacity, proactive interference, and divided attention:limits on long-term memory Retrieval. Journal of Experimental Psychology:Learning, Memory, & Cognition, 26(2), 336-358.

Lewandowsky, S., Yang, L. X., Newell, B. R., & Kalish, M. L. (2012). Working memory does not dissociate between different perceptual categorization tasks. Journal of Experimental Psychology Learning Memory & Cognition, 38(4), 881-904.

Maddox, W. T., & Ashby, F. G. (2004). Dissociating explicit and procedural-learning based systems of perceptual category learning. Behavioural Processes,66(3), 309-332.

Maddox, W. T., Ashby, F. G., Ing, A. D., & Pickering, A. D. (2004). Disrupting feedback processing interferes with rule-based but not information-integration category learning. Memory & Cognition, 32(4), 582-591.

Waldron, E. M., & Ashby, F. G. (2001).The effects of concurrent task inference in category learning. Psychonomic, Bulletin & Review, 8(1), 168-176.

Zeithamova, D., & Maddox, W. T. (2006). Dual-task interference in perceptual category learning. Memory & Cognition, 34(2), 387-398.

Zeithamova, D., & Maddox, W. T. (2007).The role of visuospatial and verbal working memory in perceptual category learning. Memory & Cognition, 35(6), 1380-1398.

陈英和, 王明怡. (2006). 工作记忆广度对儿童算术认知策略的影响. 心理发展与教育, 22(2), 29-35.

邵蕾蕾. (2012). 类别学习中学习策略的倾向性. 硕士论文. 浙江师范大学.

孙海龙, 邢强. (2014). 反馈对知觉类别学习的影响及其认知神经生理机制. 心理科学进展, 22(1), 67-74.

张娟, 莫雷, 林丹. (2008). 认知神经和神经心理角度的多重类别学习系统. 心理科学, 31(6), 1357-1360.
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