Tracing children's vocabulary development from preschool through the school‐age years: an 8‐year longitudinal study

In this 8‐year longitudinal study, we traced the vocabulary growth of Chinese children, explored potential precursors of vocabulary knowledge, and investigated how vocabulary growth predicted future reading skills. Two hundred and sixty‐four (264) native Chinese children from Beijing were measured on a variety of reading and language tasks over 8 years. Between the ages of 4 to 10 years, they were administered tasks of vocabulary and related cognitive skills. At age 11, comprehensive reading skills, including character recognition, reading fluency, and reading comprehension were examined. Individual differences in vocabulary developmental profiles were estimated using the intercept‐slope cluster method. Vocabulary development was then examined in relation to later reading outcomes. Three subgroups of lexical growth were classified, namely high‐high (with a large initial vocabulary size and a fast growth rate), low‐high (with a small initial vocabulary size and a fast growth rate) and low‐low (with a small initial vocabulary size and a slow growth rate) groups. Low‐high and low‐low groups were distinguishable mostly through phonological skills, morphological skills and other reading‐related cognitive skills. Childhood vocabulary development (using intercept and slope) explained subsequent reading skills. Findings suggest that language‐related and reading‐related cognitive skills differ among groups with different developmental trajectories of vocabulary, and the initial size and growth rate of vocabulary may be two predictors for later reading development.     

Gender differences in STEM undergraduates' vocational interests: People–thing orientation and goal affordances

This study addressed why women have greater representation in some STEM (science, technology, engineering, and mathematics) fields compared to others by linking two theoretical approaches, people–thing orientation (PO, TO) and role congruity theory, which emphasizes occupation goal affordances associated with traditionally feminine and masculine roles. Vocational interest and goal affordance ratings (having a positive social impact, family, and occupation status) for occupations characterized as working with people or things were assessed in 1848 students (42% female; 81% white non-Hispanic) majoring in biology (gender balanced), non-biology STEM (male-dominated), and female-dominated health fields. Participant PO and TO interests were also collected. Results indicated that non-biology STEM majors showed lower PO and higher TO interests than biology and health majors. Non-biology STEM majors also endorsed PO and TO interests at similar levels, but the other two major groups indicated higher PO than TO. People Jobs were perceived to more likely afford goals related to family and positive social impact; whereas Thing Jobs were perceived to more likely afford status goals. Interest in People Jobs was similar for women in both STEM major groups. Female non-biology STEM majors were equally interested in People and Thing Jobs; whereas biology majors preferred People Jobs. PO, TO, and goal affordance ratings independently predicted interest in People and Thing Jobs, and gender accounted for very little additional variance. Taken together, the findings point to the importance of using both person–thing orientation and role congruity theory when explaining varied gender representations in different STEM fields.     

Prefrontal cortex dysfunction and income: a study in neuroeconomics

In four samples of adults, individual income was negatively associated with a measure of prefrontal cortex dysfunction even after implementing controls for age, sex, and education. The small association was stronger for men than for women. These results provide support for a neuroeconomic approach to the study of micro-economic variables.     

Digital access and national character

A digital access index was associated with measures of national character (such as extraversion and individualism) for 18 industrialized nations, but statistical controls for gross domestic product per capita eliminated these associations.     

Buying books online: a replication

In a replication study, purchasing books online by 137 state college students was predicted by computer/Internet skills.     

彝族原始宗教与道教的比较研究

彝族原始宗教和道教都是本土宗教,它们之间有诸多相融、相通之处,如诸神论、祖先崇拜、神仙思想贵阴贵柔、政教合一、返朴归真、天人感应、斋醮、法术法具、禹步等。     

Infants’ recognition of objects using canonical color

We explored infants’ ability to recognize the canonical colors of daily objects, including two color-specific objects (human face and fruit) and a non-color-specific object (flower), by using a preferential looking technique. A total of 58 infants between 5 and 8 months of age were tested with a stimulus composed of two color pictures of an object placed side by side: a correctly colored picture (e.g., red strawberry) and an inappropriately colored picture (e.g., green-blue strawberry). The results showed that, overall, the 6- to 8-month-olds showed preference for the correctly colored pictures for color-specific objects, whereas they did not show preference for the correctly colored pictures for the non-color-specific object. The 5-month-olds showed no significant preference for the correctly colored pictures for all object conditions. These findings imply that the recognition of canonical color for objects emerges at 6 months of age.     

Accumulative Equating Error after a Chain of Linear Equatings

After many equatings have been conducted in a testing program, equating errors can accumulate to a degree that is not negligible compared to the standard error of measurement. In this paper, the author investigates the asymptotic accumulative standard error of equating (ASEE) for linear equating methods, including chained linear, Tucker, and Levine, under the nonequivalent groups with anchor test (NEAT) design. A recursive formula for the ASEE is provided for a series of equatings that makes use of only historical summary statistics. This formula can serve as a new tool to measure the magnitude of equating errors that have accumulated over a series of equatings, and to help monitor and design testing programs.     

Using State-Space Model with Regime Switching to Represent the Dynamics of Facial Electromyography (EMG) Data

Facial electromyography (EMG) is a useful physiological measure for detecting subtle affective changes in real time. A time series of EMG data contains bursts of electrical activity that increase in magnitude when the pertinent facial muscles are activated. Whereas previous methods for detecting EMG activation are often based on deterministic or externally imposed thresholds, we used regime-switching models to probabilistically classify each individual’s time series into latent “regimes” characterized by similar error variance and dynamic patterns. We also allowed the association between EMG signals and self-reported affect ratings to vary between regimes and found that the relationship between these two markers did in fact vary over time. The potential utility of using regime-switching models to detect activation patterns in EMG data and to summarize the temporal characteristics of EMG activities is discussed.