大学の組織と就職指導活動 : 教員と職員の意見調査を中心に

日本教育社会学会第46回大会, 1994年10月(椙山女学園大学), Ⅱ-4部会 大学と就

Who is she? Changes in the person context affect categorization

Changes between the learning and testing contexts affect learning, memory, and generalization. We examined whether a change (between learning and testing) in the person children were interacting with affects generalization. Three-, four-, and five-year-old children were trained on eight novel noun categories by one experimenter. Children were tested for their ability to generalize the label to a new category member by either the same experimenter who trained them or by a novel experimenter. Three-year-old children's performance was not affected by who they were tested by. Four- and five-year-old children's performance was lower when tested by the novel experimenter. The results are discussed in terms of source monitoring and the effect of perceptual context change on category generalization

How Bilingual Parents Talk to Children About Number in Mandarin and English

Number-related language input has been shown to influence children’s number word acquisition and mathematical ability. Significant differences exist between how Mandarin Chinese speaking parents and monolingual English-speaking parents use numeric language in speech to children. In particular, Mandarin Chinese speaking parents use cardinal number much more frequently in speech to children than do English speaking parents. However, because previous studies have been conducted cross-nationally, research has been unable to disentangle the influences of language from parental influence. The current study examined numeric language input to preschool children with bilingual Mandarin-English American parents. Results show that when parents speak to their children in Mandarin Chinese, children hear more instances and examples of the cardinal number principle than when parents speak to their children in English. This suggests that differences between how the Mandarin Chinese and English languages are structured leads to disparities in how frequently children hear cardinal number in everyday speech

How symbolic experience shapes children's symbolic flexibility

The current experiments asked whether children with dual-symbolic experience (e.g., unimodal bilingual and bimodal) develop a preference for words like monolingual children (Namy & Waxman, 1998). In Experiment 1, ninety-five 18- and 24-month-olds, with monolingual, unimodal bilingual, or bimodal symbolic experience, were tested in their willingness to treat digitized sounds as referents. In Experiment 2, forty-seven 24-month-olds, with the same types of symbolic experience, were tested in their willingness to treat novel words as referents. Monolingual children performed in ways indicative of a growing preference for words, whereas children with dual-symbolic experience performed in ways indicative of consistency in symbolic flexibility over time. Results suggest that the developmental trajectory of children's symbolic flexibility might depend on their symbolic experience.Child Development 85(2), 738-754. (2014)1467-862

Order of Presentation Effects in Learning Color Categories

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Distinct Characteristics of Circulating Vascular Endothelial Growth Factor-A and C Levels in Human Subjects

The mechanisms that lead from obesity to atherosclerotic disease are not fully understood. Obesity involves angiogenesis in which vascular endothelial growth factor-A (VEGF-A) plays a key role. On the other hand, vascular endothelial growth factor-C (VEGF-C) plays a pivotal role in lymphangiogenesis. Circulating levels of VEGF-A and VEGF-C are elevated in sera from obese subjects. However, relationships of VEGF-C with atherosclerotic risk factors and atherosclerosis are unknown. We determined circulating levels of VEGF-A and VEGF-C in 423 consecutive subjects not receiving any drugs at the Health Evaluation Center. After adjusting for age and gender, VEGF-A levels were significantly and more strongly correlated with the body mass index (BMI) and waist circumference than VEGF-C. Conversely, VEGF-C levels were significantly and more closely correlated with metabolic (e.g., fasting plasma glucose, hemoglobin A1c, immunoreactive insulin, and the homeostasis model assessment of insulin resistance) and lipid parameters (e.g., triglycerides, total cholesterol (TC), low-density-lipoprotein cholesterol (LDL-C), and non-high-density-lipoprotein cholesterol (non-HDL-C)) than VEGF-A. Stepwise regression analyses revealed that independent determinants of VEGF-A were the BMI and age, whereas strong independent determinants of VEGF-C were age, triglycerides, and non-HDL-C. In apolipoprotein E-deficient mice fed a high-fat-diet (HFD) or normal chow (NC) for 16 weeks, levels of VEGF-A were not significantly different between the two groups. However, levels of VEGF-C were significantly higher in HFD mice with advanced atherosclerosis and marked hypercholesterolemia than NC mice. Furthermore, immunohistochemistry revealed that the expression of VEGF-C in atheromatous plaque of the aortic sinus was significantly intensified by feeding HFD compared to NC, while that of VEGF-A was not. In conclusion, these findings demonstrate that VEGF-C, rather than VEGF-A, is closely related to dyslipidemia and atherosclerosis

A mechanism for the cortical computation of hierarchical linguistic structure

Biological systems often detect species-specific signals in the environment. In humans, speech and language are species-specific signals of fundamental biological importance. To detect the linguistic signal, human brains must form hierarchical representations from a sequence of perceptual inputs distributed in time. What mechanism underlies this ability? One hypothesis is that the brain repurposed an available neurobiological mechanism when hierarchical linguistic representation became an efficient solution to a computational problem posed to the organism. Under such an account, a single mechanism must have the capacity to perform multiple, functionally related computations, e.g., detect the linguistic signal and perform other cognitive functions, while, ideally, oscillating like the human brain. We show that a computational model of analogy, built for an entirely different purpose—learning relational reasoning—processes sentences, represents their meaning, and, crucially, exhibits oscillatory activation patterns resembling cortical signals elicited by the same stimuli. Such redundancy in the cortical and machine signals is indicative of formal and mechanistic alignment between representational structure building and “cortical” oscillations. By inductive inference, this synergy suggests that the cortical signal reflects structure generation, just as the machine signal does. A single mechanism—using time to encode information across a layered network—generates the kind of (de)compositional representational hierarchy that is crucial for human language and offers a mechanistic linking hypothesis between linguistic representation and cortical computatio