有话，好好说

明明很爱孩子,可是孩子却总是不领情,这让做母亲的心里很不是滋味。和朋友聊天之后才恍然大悟,原来是在说话方式上出了小问题,还好,及时的改正换来了孩子的感恩。     

Is Canada really an education superpower? The impact of non-participation on results from PISA 2015

Educational Assessment, Evaluation and Accountability - The purpose of large-scale international assessments is to compare educational achievement across countries. For such cross-national...     

The Sensitivity of Value-Added Teacher Effect Estimates to Different Mathematics Achievement Measures

Using longitudinal data from a cohort of middle school students from a large school district, we estimate separate "value-added" teacher effects for two subscales of a mathematics assessment under a variety of statistical models varying in form and degree of control for student background characteristics. We find that the variation in estimated effects resulting from the different mathematics achievement measures is large relative to variation resulting from choices about model specification, and that the variation within teachers across achievement measures is larger than the variation across teachers. These results suggest that conclusions about individual teachers' performance based on value-added models can be sensitive to the ways in which student achievement is measured.     

Does adviser mentoring add value? A longitudinal study of mentoring and doctoral student outcomes

This study of the impact of doctoral adviser mentoring on student outcomes was undertaken in response to earlier research that found (a) students with greater incoming potential received more adviser mentoring, and (b) adviser mentoring did not significantly contribute to important student outcomes, including research productivity [Green, S. G., and Bauer, T. N. (1995). Personnel Psychology 48(3): 537–561]. In this longitudinal study spanning 5 1/2 years, the effect of mentorship on the research productivity, career commitment, and self-efficacy of Ph.D. students in the ‘hard’ sciences was assessed, while controlling for indicators of ability and attitudes at program entry. Positive benefits of mentoring were found for subsequent productivity and self-efficacy. Mentoring was not significantly associated with commitment to a research career.     

‘I’ll take care of the flowers!’ Researching agency through initiatives across different learning environments

ABSTRACT

This case study examined how the agency of a fifth-grade pupil appeared across different learning environments in the primary school context. In this study, agency is defined as the initiatives taken by an individual in interactive situations. The research question is: how does a pupil’s agency manifest and vary through taking initiatives across different learning environments within curriculum-based education? The empirical data consist of 50 video episodes including learning activities in a classroom, in a vegetable garden and on a nearby farm. The findings show that the pupil’s agency varied across learning environments, manifesting itself through complementing, supportive, constructive and challenging initiatives. When developing pedagogy that supports learning across formal and informal learning environments, it is essential to enable pupils to take different kinds of initiatives and to exercise their agency in versatile contexts.     

不走寻常路，理科生PK文科类重点大学

镜头闪回 想去北京上大学,而且一定要上一所重点大学,一直就是我的心愿。为什么呢？原因其实很简单：北京是首都嘛,从小就在课本和电视里了解了很多。后来在一个假期里,爸爸还带我去玩了一趟。什么颐和园、故宫博物馆,北京就是北京,那才叫一个恢宏大气。而且现在考到北京去念书,正好能赶上2008年奥运会。这个机会可是千载难逢啊!     

陌生的父亲

这位海军陆战队员赶到医院时,期盼儿子归来的垂危老人已神智不清。为了给予老人最温暖的临终关怀,海军陆战队员寸步不离地陪伴着老人度过了漫长而安详的一夜。可是,送走老人后他却问护士:"那个男人是谁?"     

Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods

A number of psychometricians have suggested that parallel analysis (PA) tends to yield more accurate results in determining the number of factors in comparison with other statistical methods. Nevertheless, all too often PA can suggest an incorrect number of factors, particularly in statistically unfavorable conditions (e.g., small sample sizes and low factor loadings). Because of this, researchers have recommended using multiple methods to make judgments about the number of factors to extract. Implicit in this recommendation is that, when the number of factors is chosen based on PA, uncertainty nevertheless exists. We propose a Bayesian parallel analysis (B-PA) method to incorporate the uncertainty with decisions about the number of factors. B-PA yields a probability distribution for the various possible numbers of factors. We implement and compare B-PA with a frequentist approach, revised parallel analysis (R-PA), in the contexts of real and simulated data. Results show that B-PA provides relevant information regarding the uncertainty in determining the number of factors, particularly under conditions with small sample sizes, low factor loadings, and less distinguishable factors. Even if the indicated number of factors with the highest probability is incorrect, B-PA can show a sizable probability of retaining the correct number of factors. Interestingly, when the mode of the distribution of the probabilities associated with different numbers of factors was treated as the number of factors to retain, B-PA was somewhat more accurate than R-PA in a majority of the conditions.