Abstract

Cognitive flexibility reflects the ability to switch quickly between tasks or stimulus sets, which is an important feature of human intelligence. Researchers have confirmed that this ability is related to the learners’ academic achievement, cognitive ability, and creativity development. The number-letter switching task is an effective tool for measuring cognitive flexibility. Previous studies have found that high flexibility individuals perform better in rule-based tasks such as the Iowa Gambling Task. It is not clear whether highly flexible learners have learning advantages when the rule tasks involve probabilistic cues. Using an inter-individual differences approach, we examined whether cognitive flexibility, as assessed by the number-letter task, is associated with the learning process of a probabilistic rule task. The results showed that the high flexibility group reached a higher level of rule acquisition, and the accuracy during the post-learning stage was significantly higher than the low flexibility group. These findings demonstrate that cognitive flexibility is associated with the performance after the rule acquisition during the probabilistic rule task. Future research should explore the internal process of learning differences between high and low flexibility learners by using other technologies across multiple modes.

Highlights

  • As a core component of executive functioning (EF), cognitive flexibility has attracted much attention in psychological research

  • Participants with a score less than 525.3 ms were assigned to the high flexibility group, and participants with a score greater than 1041.1 ms were assigned to the low flexibility group (Table 2). 39 (15 males, age39 = 20.2 ± 2.0) high flexibility and 37 (5 males, age37 = 19.3 ± 1.6) low flexibility participants were willing to participate further

  • Behavioral data analysis showed that the differences between the two groups are mainly manifested in the following three points: (1) The high CF group showed a higher rate of rule acquisition, which partially verified our hypothesis that high cognitive flexibility learners would show more accurate rule acquisition during rule learning

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Summary

Introduction

As a core component of executive functioning (EF), cognitive flexibility has attracted much attention in psychological research. Research from various fields has investigated the internal mechanism underlying cognitive flexibility. Animal-based research has explored the underlying mechanisms of this function from an anatomical neurology perspective (Darby et al, 2018). Studies of patients with neurological impairment provide a window for exploring internal mechanisms (Lange et al, 2017). Despite extensive attention and research, there is still no clear common definition of cognitive flexibility, which can influence how this construct is operationalized in research (Müller et al, 2014).

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