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.     

Promoting environmentally sustainable attitudes and behaviour through free‐choice learning experiences: what is the state of the game?

Environmental education, both in and outside of the classroom, aims to facilitate adoption of sustainable practice by both school students and the general public. This paper explores the role of free‐choice learning experiences in this regard. An overview of theoretical approaches underpinning free‐choice learning research is provided, examples are presented of the ways in which informal educational settings can promote environmentally sustainable attitudes and behaviour, and the factors contributing to the effectiveness of these endeavours are discussed. By reviewing research evidence in relation to these issues, the paper identifies the current ‘state of the game’ and areas where new research is needed.