Student Evaluations and Gendered Expectations: What We Can't Count Can Hurt Us

Does teacher's gender impact students' evaluations? We critically evaluated the research literature and concluded that the form gender bias takes may not be easily detectible by quantitative scales. To explore this possibility, we did a qualitative analysis of the words that 288 college students at two campuses used to describe their best- and worst-ever teachers. Although we found considerable overlap in the ways that students talked about their male and female teachers, we also saw indications that students hold teachers accountable to certain gendered expectations. These expectations place burdens on all teachers, but the burdens on women are more labor-intensive. We also saw signs of much greater hostility toward women than toward men who do not meet students' gendered expectations.     

Accuracy in parameter estimation for targeted effects in structural equation modeling: sample size planning for narrow confidence intervals

In addition to evaluating a structural equation model (SEM) as a whole, often the model parameters are of interest and confidence intervals for those parameters are formed. Given a model with a good overall fit, it is entirely possible for the targeted effects of interest to have very wide confidence intervals, thus giving little information about the magnitude of the population targeted effects. With the goal of obtaining sufficiently narrow confidence intervals for the model parameters of interest, sample size planning methods for SEM are developed from the accuracy in parameter estimation approach. One method plans for the sample size so that the expected confidence interval width is sufficiently narrow. An extended procedure ensures that the obtained confidence interval will be no wider than desired, with some specified degree of assurance. A Monte Carlo simulation study was conducted that verified the effectiveness of the procedures in realistic situations. The methods developed have been implemented in the MBESS package in R so that they can be easily applied by researchers.     

Do Provocateurs’ Emotion Displays Influence Children’s Social Goals and Problem Solving?

The social goals and social problem-solving of children who varied in social adjustment were examined in the context of hypothetical ambiguous provocation situations in which provocateurs’ emotion displays were systematically manipulated. Children rated the importance of six different social goals and explained how they would solve the problems. Social adjustment was measured with rating and nomination sociometric procedures. Rejected-aggressive, rejected-nonaggressive, average-nonaggressive, and popular-nonaggressive children showed both commonalities and differences in rating the six social goals, the relative importance of the six social goals, and social problem-solving depending on the provocateur’s emotion display. When provocateurs were happy, there were few group differences, but when provocateurs were angry or sad, rejected-aggressive children: a) rated hostile/instrumental goals more positively; b) rated prosocial goals less positively; and c) made problem-solving responses that were less friendly than those of other children. Results are discussed in relation to Lemerise and Arsenio’s (2000) model of emotion and social information processing.     

Self-evaluation as a moderating factor of strategy change in directed forgetting benefits

In list method directed forgetting, instructing people to forget a studied word list usually results in better recall for a newly studied list. Sahakyan and Delaney (2003) have suggested that these benefits are due to a change in encoding strategy that occurs between the study of the first list and the study of the second list. To investigate what might mediate such strategy change decisions, in two experiments we induced bothforget and remember participants to evaluate their memory performance on the two lists. In Experiment 1, they were asked to explicitly recall the items from the first list before studying the second list. In Experiment 2, after the study of the first list, the participants provided a rapid aggregate judgment of learning. Evaluation eliminated the differences between the forget and remember groups for the second list in both experiments, because the remember group achieved recall levels comparable to those for the forget group. The role of performance evaluation in mediating directed forgetting benefits is discussed.     

Reinforcement magnitude and responding during treatment with differential reinforcement

Basic findings indicate that the amount or magnitude of reinforcement can influence free-operant responding prior to and during extinction. In this study, the relation between reinforcement magnitude and adaptive behavior was evaluated with 3 children as part of treatment with differential reinforcement. In the first experiment, a communicative response was shaped and maintained by the same reinforcer that was found to maintain problem behavior. Two reinforcement magnitudes (20-s or 60-s access to toys or escape from demands) were compared and found to be associated with similar levels of resistance to extinction. The relation between reinforcement magnitude and response maintenance was further evaluated in the second experiment by exposing the communicative response to 20-s or 300-s access to toys or escape. Results for 2 participants suggested that this factor may alter the duration of postreinforcement pauses.     

Further evaluation of the role of protective equipment in the functional analysis of self-injurious behavior

Using a procedure similar to the one described by Le and Smith (in press), we evaluated the effects of protective equipment during a functional analysis for 2 individuals who engaged in severe self-injurious behavior (SIB). Results of our analyses revealed that the use of protective equipment during functional analyses of SIB suppressed levels of responding such that a behavioral function could not be identified.     

Further analysis of idiosyncratic antecedent influences during the assessment and treatment of problem behavior

Recent research findings suggest that idiosyncratic variables can influence the outcomes of functional analyses (E. G. Carr, Yarbrough, & Langdon, 1997). In the present study, we examined idiosyncratic environment-behavior relations more precisely after identifying stimuli (i.e., a particular toy and social interaction) associated with increased levels of problem behavior. Two children, an 8-year-old boy with moderate mental retardation and a 5-year-old boy with no developmental delays, participated. Results of functional analyses for both children indicated that idiosyncratic antecedent stimuli set the occasion for occurrences of problem behavior (hand biting or hand flapping) and that problem behavior persisted in the absence of social contingencies. Further analyses were conducted to identify specific components of the stimuli that occasioned problem behavior. Treatments based on results of the analyses successfully reduced self-injury and hand flapping.     

An empirical investigation of the factor structure of the AUDIT

This study investigated the Alcohol Use Disorders Identification Test's (AUDIT) factor structure and psychometric properties. The factor structure was derived from a sample of 7,035 men and women primary care patients. A principal components analysis identified 2 factors in the AUDIT data and was supported in a confirmatory factor analysis (CFA). The 2 factors were Dependence/Consequences and Alcohol Consumption. The CFA also provided support for a 3-factor model whose factors (Alcohol Consumption, Alcohol Dependence, and Related Consequences) matched those proposed by the AUDIT's developers. Psychometric indexes were determined by use of the baseline and 12-month follow-up data of 301 men and women who entered a clinical trial. The results showed that the 2 factors had good reliability. Validity tests supported the interpretation of what the 2 factors measure, its implications for relationships to other variables, and the comparability of the 2- and 3-factor models.