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Dataset of implicit sequence learning of chunking and abstract structures.
Fu, Qiufang; Sun, Huiming; Dienes, Zoltán; Fu, Xiaolan.
Afiliación
  • Fu Q; State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, China.
  • Sun H; Department of Psychology, University of Chinese Academy of Sciences, China.
  • Dienes Z; Institute of Politics, NDU, PLA, China.
  • Fu X; School of Psychology and Sackler Centre for Consciousness Science, University of Sussex, UK.
Data Brief ; 22: 72-75, 2019 Feb.
Article en En | MEDLINE | ID: mdl-30581907
This article describes the data analyzed in the paper "Implicit sequence learning of chunking and abstract structures" (Fu et al., 2018) [1]. It includes reaction times in the serial reaction time task and generation proformance for each confidence rating or attribution under the inclusion and exclusion tests from three experiments. For the serial reaction time task, the independent varialbles were type of stimuli and blocks or type of deviants; for the generation tests, the independent varialbles were type of stimuli, instructions, and confidence ratings or attribution tests. The data can be used to examine wether a computor model can account for what type of knowledge is acquried in implicit sequence learning.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Data Brief Año: 2019 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Data Brief Año: 2019 Tipo del documento: Article País de afiliación: China
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