Teaching social perspective taking: how educators might learn from the Army

Frequently and accurately discerning others’ thoughts and feelings is associated with multiple valued educational outcomes across an array of settings. Despite its foundational role in social interactions, it is unclear whether individuals can be taught to improve their social perspective taking capacities. This experiment assesses whether a curriculum taught to US Army personnel (N?=?116) improved their social perspective taking prior to deployment. Results showed that participants improved their social perspective taking in three ways: through more accurately detecting biases in others, by generating more initial hypotheses to explain others’ behaviours, and by adapting their hypotheses in the face of new evidence. The curriculum did not affect participants’ perspective taking accuracy on a video measure. We discuss these findings with respect to their implications for other learning environments.     

Decisions that make a difference in detecting differential item functioning

There are numerous statistical procedures for detecting items that function differently across subgroups of examinees that take a test or survey. However, in endeavouring to detect items that may function differentially, selection of the statistical method is only one of many important decisions. In this article, we discuss the important decisions that affect investigations of differential item functioning (DIF) such as choice of method, sample size, effect size criteria, conditioning variable, purification, DIF amplification, DIF cancellation, and research designs for evaluating DIF. Our review highlights the necessity of matching the DIF procedure to the nature of the data analysed, the need to include effect size criteria, the need to consider the direction and balance of items flagged for DIF, and the need to use replication to reduce Type I errors whenever possible. Directions for future research and practice in using DIF to enhance the validity of test scores are provided.     

A Comparative Framing Analysis of Embedded and Behind-the-Lines Reporting on the 2003 Iraq War

This study sought to develop a typology of communication challenges perceived by frontline employees during the implementation of organizational change. A sample of midlevel managers (N = 166) self-reported 486 challenges they perceived encountering while implementing a new customer service program at a national textbook retailer. These perceived impediments were inductively analyzed into a five-tiered typology including (a) resistance from external stakeholders, (b) a lack of resources and decision-making authority, (c) personal management issues, (d) competing changes, and (e) staff resistance.     

The Role of Perceived Control in Alcohol Prevention Campaigns

Optimistic bias provides a framework in this study to consider college students' knowledge about and perceptions of control over the effect of alcohol consumption on genes and health. Participants were 339 college students who completed a survey on genetics in the spring of 2001. This study confirmed that there is a significant relationship between knowledge and perceived control. In addition, the prediction that there are no differences between heavy and light drinkers with respect to their perceived knowledge and perceived control was supported. These results suggest the need to reconsider how prevention programs promote control over alcohol's use and effects because of the perceptions of invulnerability that may accompany feelings of control.     

Theory‐led confirmation bias and experimental persona

Questionnaire and interview findings from a survey of three Year 8 (ages 12–13 years) science practical lessons (n = 52) demonstrate how pupils' data collection and inference making were sometimes biased by desires to confirm a personal theory. A variety of behaviours are described where learners knowingly rejected anomalies, manipulated apparatus, invented results or carried out other improper operations to either collect data which they believed were scientifically correct, or achieve social conformity. It is proposed that confirmation bias was a consequence of the degree to which individuals were laden by theory, and driven by this, experimenters assumed one of three different personas: becoming right answer confirmers; good scientists; or indifferent spectators. These personas have parallels with historical instances of scientific behaviour. Implications of a continued teacher‐tolerance of pupil confirmation bias include the promotion of unscientific experimenting, and the persistence of unchallenged science misconceptions. Solutions are offered in the way of practical strategies that might reduce experimenters' theory‐ladeness.     

Estimating R 2 Shrinkage in Multiple Regression: A Comparison of Different Analytical Methods

The effectiveness of various analytical formulas for estimating R ² shrinkage in multiple regression analysis was investigated. Two categories of formulas were identified: estimators of the squared population multiple correlation coefficient (ρ²) and those of the squared population cross-validity coefficient (ρ_c ²). The authors conducted a Monte Carlo experiment to investigate the effectiveness of the analytical formulas for estimating R ² shrinkage, with 4 fully crossed factors (squared population multiple correlation coefficient, number of predictors, sample size, and degree of multicollinearity) and 500 replications in each cell. The results indicated that the most widely used Wherry formula (in both SAS and SPSS) is probably not the most effective analytical formula for estimating ρ². Instead, the Pratt formula and the Browne formula outperformed other analytical formulas in estimating ρ² and ρ_c ², respectively.     

Troubled Diversities,Multiple Identities and the Relevance of Royce: What makes a community worth caring about?

Based on a rather simple thesis that we can learn from our mistakes, Karl Popper developed a falsificationist epistemology in which knowledge grows through falsifying, or criticizing, our theories. According to him, knowledge, especially scientific knowledge, progresses through conjectures (i.e. tentative solutions to problems) that are controlled by criticism, or attempted refutations (including severely critical tests). As he puts it, ‘Criticism of our conjectures is of decisive importance: by bringing out our mistakes it makes us understand the difficulties of the problem which we are trying to solve. This is how we become better acquainted with our problem, and able to propose more mature solutions: the very refutation of a theory ... is always a step forward that takes us nearer to the truth. And this is how we can learn from our mistakes’ (1989, p. vii). Since criticism plays such a crucial role in Popper's falsificationist methodology, it seems natural to envisage his heuristic as a helpful resource for developing critical thinking. However, there is much controversy in the psychological literature over the feasibility and utility of his falsificationism as a heuristic. In this paper, I first consider Popper's falsificationism within the framework of his critical rationalism, elucidating three core and interrelated concepts, viz. fallibilism, criticism, and verisimilitude. Then I argue that the implementation of Popper's falsificationism means exposing to criticism various philosophical presuppositions that work against criticism, such as essentialism, instrumentalism, and conventionalism; it also means combating what seems a common tendency of humans to be biased towards confirmation. I examine the confirmation bias, to which Popper did not give much attention: its pervasiveness and various guises, some theoretical explanations for it, and the role of teachers in undermining its strength and spread. Finally, I consider the question whether students can and should be taught to use disconfirmatory strategies for solving problems.     

A Test for Cluster Bias: Detecting Violations of Measurement Invariance Across Clusters in Multilevel Data

We present a test for cluster bias, which can be used to detect violations of measurement invariance across clusters in 2-level data. We show how measurement invariance assumptions across clusters imply measurement invariance across levels in a 2-level factor model. Cluster bias is investigated by testing whether the within-level factor loadings are equal to the between-level factor loadings, and whether the between-level residual variances are zero. The test is illustrated with an example from school research. In a simulation study, we show that the cluster bias test has sufficient power, and the proportions of false positives are close to the chosen levels of significance.     

Measurement Bias in Multilevel Data

Measurement bias can be detected using structural equation modeling (SEM), by testing measurement invariance with multigroup factor analysis (Jöreskog, 1971;Meredith, 1993;Sörbom, 1974) MIMIC modeling (Muthén, 1989) or restricted factor analysis (Oort, 1992,1998). In educational research, data often have a nested, multilevel structure, for example when data are collected from children in classrooms. Multilevel structures might complicate measurement bias research. In 2-level data, the potentially “biasing trait” or “violator” can be a Level 1 variable (e.g., pupil sex), or a Level 2 variable (e.g., teacher sex). One can also test measurement invariance with respect to the clustering variable (e.g., classroom). This article provides a stepwise approach for the detection of measurement bias with respect to these 3 types of violators. This approach works from Level 1 upward, so the final model accounts for all bias and substantive findings at both levels. The 5 proposed steps are illustrated with data of teacher–child relationships.