Six-month-old infants discriminate between large sets of objects on the basis of numerosity when other extraneous variables are controlled, provided that the sets to be discriminated differ by a large ratio (8 vs. 16 but not 8 vs. 12). The capacities to represent approximate numerosity found in adult animals and humans evidently develop in human infants prior to language and symbolic counting.

Much research on cognitive development focuses either on early-emerging domain-specific knowledge or domain-general learning mechanisms. However, little research examines how these sources of knowledge interact. Previous research suggests that young infants can make inferences from samples to populations (Xu & Garcia, 2008) and 11- to 12.5-month-old infants can integrate psychological and physical knowledge in probabilistic reasoning (Teglas, Girotto, Gonzalez, & Bonatti, 2007; Xu & Denison, 2009). Here, we ask whether infants can integrate a physical constraint of immobility into a statistical (...) inference mechanism. Results from three experiments suggest that, first, infants were able to use domain-specific knowledge to override statistical information, reasoning that sometimes a physical constraint is more informative than probabilistic information. Second, we provide the first evidence that infants are capable of applying domain-specific knowledge in probabilistic reasoning by using a physical constraint to exclude one set of objects while computing probabilities over the remaining sets. (shrink)

Individual choices are commonly taken to manifest personal preferences. The present study investigated whether social and statistical cues influence young children's inferences about the generalizability of preferences. Preschoolers were exposed to either 1 or 2 demonstrators’ selections of objects. The selected objects constituted 18%, 50%, or 100% of all available objects. We found that children took a single demonstrator's choices as indicative only of his or her personal preference. However, when 2 demonstrators made the same selection, then children inferred that (...) it generalized to other agents of the same kind as the original demonstrator's, but not to agents of a different kind. Lastly, only when both demonstrators blatantly violated random selection (i.e., in the 18% condition) did children generalize the preference even to an agent of a different kind. Thus, from a young age, social and statistical cues inform children's naïve sociology. (shrink)

In the current study, late Chinese–English bilinguals performed a facial expression identification task with emotion words in the task-irrelevant dimension, in either their first language or second language. The investigation examined the automatic access of the emotional content in words appearing in more than one language. Significant congruency effects were present for both L1 and L2 emotion word processing. Furthermore, the magnitude of emotional face-word Stroop effect in the L1 task was greater as compared to the L2 task, indicating that (...) in L1 participants could access the emotional information in words in a more reliable manner. In summary, these findings provide more support for the automatic access of emotional information in words in the bilinguals’ two languages as well as attenuated emotionality of L2 processing. (shrink)

Rational constructivism is one of the leading theories in developmental psychology. But it is not a purely psychological theory: rational constructivism also makes a number of substantial epistemological claims about both the nature of human rationality and several normative principles that fall squarely into the ambit of epistemology. The aim of this paper is to clarify and defend both theses and several other epistemological claims, as they represent the essential epistemological dimensions of rational constructivism.

I make two points in this commentary on Carey (2009). First, it may be too soon to conclude that core cognition is innate. Recent advances in computational cognitive science and developmental psychology suggest possible mechanisms for developing inductive biases. Second, there is another possible answer to Fodor's challenge – if concepts are merely mental tokens, then cognitive scientists should spend their time on developing a theory of belief fixation instead.

Explanations of how the brain makes successful predictions should refer to abstracta. But, the mind/brain system is for more than prediction alone. Creativity also plays an important role in supply the mind/brain system with abstracta that serve a number of valuable ends over and above prediction.

In this article, we focus on an extended model M ¯ of bounded rationality. Based on a rationality function with lower semicontinuity, we analyze the relationship between structural stability and robustness of Ω ¯. To further demonstrate the applicability of our theory, we introduce a model Ω ¯ 0 containing an abstract rationality function and generalize abstract fuzzy economies. We demonstrate the structural stability of the extended model Ω ¯ 0 at ξ ¯, ɛ. That is to say, Ω ¯ (...) 0 is robust to the ξ ¯, ɛ -equilibria. (shrink)

本书对马克思主义哲学和后现代主义的产生背景、总体特征、本体论特征、历史观特征和发展趋势进行了对比研究。.

We argue that creative ideas are potentially valuable improbable constructions. We arrive at this formulation of creativity after considering several problems that arise for the theories that suggest that creativity is novelty, originality, or usefulness. Our theory avoids these problems. But since we also derive our theory of creativity from the scientific commitments of a more general theory of cognitive development, a theory called rational constructivism, our theory is unique insofar as it explains creativity in both adults and children through (...) reference to a set of computational mechanisms that have been posited on the basis of independently plausible experimental research. (shrink)

We applaud Millikan's psychologically plausible version of the causal theory of reference. Her proposal offers a significant clarification of the much-debated relation between concepts and beliefs, and suggests positive directions for future empirical studies of conceptual development. However, Millikan's revision of the causal theory may leave us with no generally satisfying account of concept individuation in the mind.

Purpose: This study aimed to explore the relationship between mathematic achievement and programming self-efficacy, and adopt a mediation model to verify the mediating role of creativity on the relationship between mathematic achievement and programming self-efficacy.Methods: A total of 950 upper-secondary school students were surveyed using their math test scores, the Kirton Adaption-Innovation and the Programmed Self-Efficacy Scale. SPSS-26 was used for descriptive statistical analysis and correlation analysis of related variables. The PROCESS plugin was used to test the mediating effect of (...) creativity.Results: Mathematic achievement has a positive effect on programming self-efficacy, mathematic achievement is positively related to creativity, and creativity also has a positive influence on programming self-efficacy. Creativity has a mediating effect on the relationship between mathematic achievement and programming self-efficacy.Conclusion: The results revealed that mathematic achievement affected programming self-efficacy directly and also indirectly through creativity. This provided certain ideas for the development of programming education for teenagers. Since students’ mathematics learning and creativity are related to programming learning, it is necessary to pay attention to the integration of the disciplines of programming education and mathematics. Further, the cultivation of innovative thinking is also critical to facilitate programming learning. (shrink)

In order to account for how children can generalize words beyond a very limited set of labeled examples, Bloom's proposal of word learning requires two extensions: a better understanding of the “general learning and memory abilities” involved, and a principled framework for integrating multiple conflicting constraints on word meaning. We propose a framework based on Bayesian statistical inference that meets both of those needs.