Children's environmental moral judgments: Variations according to type of victim and exposure to nature

Introduction Human actions are largely responsible for environmental problems such as global warming (Cook et al., 2013, Evans, 2018). It is therefore increasingly important to understand how individuals develop a sense of environmental morality. Behaving in a pro-environmental way has long been considered a moral issue (Harland et al., 1999, Kaiser et al., 2006, Matthies et al., 2012, Thøgersen, 1996, Thøgersen, 2006). Indeed, some empirical evidence shows that school-aged children reason about environmental issues in moral terms (e.g., Kahn, 1997, Kahn and Friedman, 1995), and children as young as three years of age show moral attitudes towards environmentally harmful actions (Hahn & Garrett, 2017). However, the factors and processes leading to children's moral judgments of actions that harm the environment are still quite unknown. Building upon research based on social domain theory, we expand on previous studies on children's environmental morality by examining two factors that may regulate children's moral judgments of environmentally harmful actions: 1. The target of the action and 2. Children's experiences in nature. Social domain theory proposes that children's judgments about harmful actions depend on the identity of the victim (Smetana, 2006). The targets of environmentally harmful actions are diverse. Hence we decided it would be valuable to examine whether children's environmental moral judgments would vary depending on the victim of the actions..

Inferential Item-Fit Evaluation in Cognitive Diagnosis Modeling

Research related to the fit evaluation at the item level involving cognitive diagnosis models (CDMs) has been scarce. According to the parsimony principle, balancing goodness of fit against model complexity is necessary. General CDMs require a larger sample size to be estimated reliably, and can lead to worse attribute classification accuracy than the appropriate reduced models when the sample size is small and the item quality is poor, which is typically the case in many empirical applications. The main purpose of this study was to systematically examine the statistical properties of four inferential item-fit statistics: S-X2, the likelihood ratio (LR) test, the Wald (W) test, and the Lagrange multiplier (LM) test. To evaluate the performance of the statistics, a comprehensive set of factors, namely, sample size, correlational structure, test length, item quality, and generating model, is systematically manipulated using Monte Carlo methods. Results show that the S-X2 statistic has unacceptable power. Type I error and power comparisons favor LR and W tests over the LM test. However, all the statistics are highly affected by the item quality. With a few exceptions, their performance is only acceptable when the item quality is high. In some cases, this effect can be ameliorated by an increase in sample size and test length. This implies that using the above statistics to assess item fit in practical settings when the item quality is low remains a challenge

Helping out on the land: Effects of children's role in agriculture on reported psychological restoration

Social decision makin

A relational model of perceived restorativeness: Intertwined effects of obligations, familiarity, security and parental supervision

Social decision makin