Dataset of implicit sequence learning of chunking and abstract structures
Qiufang Fu,
Huiming Sun,
Zoltán Dienes,
Xiaolan Fu
Affiliations
Qiufang Fu
State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, China; Department of Psychology, University of Chinese Academy of Sciences, China; Corresponding author at: State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, China.
Huiming Sun
Institute of Politics, NDU, PLA, China
Zoltán Dienes
School of Psychology and Sackler Centre for Consciousness Science, University of Sussex, UK
Xiaolan Fu
State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, China; Department of Psychology, University of Chinese Academy of Sciences, China
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.
