In search of average growth: Describing within-year oral reading fluency growth across Grades 1–8

Measures of oral reading fluency (ORF) are perhaps the most often used assessment to monitor student progress as part of a response to intervention (RTI) model. Rates of growth in research and aim lines in practice are used to characterize student growth; in either case, growth is generally defined as linear, increasing at a constant rate. Recent research suggests ORF growth follows a nonlinear trajectory, but limitations related to the datasets used in such studies, composed of only three testing occasions, curtails their ability to examine the true functional form of ORF growth. The purpose of this study was to model within-year ORF growth using up to eight testing occasions for 1448 students in Grades 1 to 8 to assess (a) the average growth trajectory for within-year ORF growth, (b) whether students vary significantly in within-year ORF growth, and (c) the extent to which findings are consistent across grades. Results demonstrated that for Grades 1 to 7, a quadratic growth model fit better than either linear or cubic growth models, and for Grade 8, there was no substantial, stable growth. Findings suggest that the expectation for linear growth currently used in practice may be unrealistic.     

Examining classroom influences on student perceptions of school climate: The role of classroom management and exclusionary discipline strategies

There is growing emphasis on the use of positive behavior supports rather than exclusionary discipline strategies to promote a positive classroom environment. Yet, there has been limited research examining the association between these two different approaches to classroom management and students' perceptions of school climate. Data from 1902 students within 93 classrooms that were nested within 37 elementary schools were examined using multilevel structural equation modeling procedures to investigate the association between two different classroom management strategies (i.e., exclusionary discipline strategies and the use of positive behavior supports) and student ratings of school climate (i.e., fairness, order and discipline, student–teacher relationship, and academic motivation). The analyses indicated that greater use of exclusionary discipline strategies was associated with lower order and discipline scores, whereas greater use of classroom-based positive behavior supports was associated with higher scores on order and discipline, fairness, and student–teacher relationship. These findings suggest that pre-service training and professional development activities should promote teachers' use of positive behavior support strategies and encourage reduced reliance on exclusionary discipline strategies in order to enhance the school climate and conditions for learning.     

Factorial validity of the Mental Toughness Questionnaire-48

The purpose of this study was to assess the factorial validity of the Mental Toughness Questionnaire-48 (Clough, Earle, & Sewell, 2002). In total, 8207 participants (male n = 4019, female n = 3922, unspecified = 266) aged between 16 and 68 years (M = 37.00, SD = 12.09) completed the MTQ48. Model fit was assessed using confirmatory factor analysis (CFA) and exploratory structural equation modeling, in addition to the robust maximum likelihood estimator. Overall, our results support the factorial validity of the MTQ48 and indicate that the MTQ48 is a robust psychometric measure of mental toughness. Along with previous data, which supports the internal validity of the MTQ48 in addition to results of this study, it would appear that the MTQ48 is an acceptable method of assessing mental toughness.     

Evolution of communication in perfect and imperfect worlds

We extend previous work on cooperation to some related questions regarding the evolution of simple forms of communication. The evolution of cooperation within the iterated Prisoner's Dilemma has been shown to follow different patterns, with significantly different outcomes, depending on whether the features of the model are classically perfect or stochastically imperfect (Axelrod, 1980a,b, 1984, 1985; Axelrod and Hamilton, 1981; Nowak and Sigmund, 1990, 1992; Sigmund, 1993). Our results here show that the same holds for communication. Within a simple model, the evolution of communication seems to require a stochastically imperfect world.     

INTEGRAL GEOGRAPHY: SPACE,PLACE, AND PERSPECTIVE

Considering the role of space and place in Integral Ecology is presented as the concept of Integral Geography. First, an ecological AQAL model is proposed to situate the diverse scientific disciplines used in geography, giving equal consideration for their respective contributions in knowledge and understanding of the world. Second, a model for incorporating perspectives provided in the arts and humanities is proposed in situating scientific understanding in relation to aesthetic and cultural aspects of “being and becoming.” Third, a Geographical Information System (GIS) based map model illustrates how biophysical and social realities can be viewed and analyzed from a geographical perspective as “Integral places.”     

From Good to Great: Examining Exemplary Counselor Development

Some counselors excel in the profession. Few do so while maintaining a balance in life. This article examines the life of one such individual, Samuel T. Gladding. He models for counselors an aspirational process of making significant contributions to the profession while staying personally grounded. Qualities that propel professionals like Gladding from being good as a young professional into prominence as a mature counselor are examined.     

A New Model for Acquiescence at the Interface of Psychometrics and Cognitive Psychology

ABSTRACT

When measuring psychological traits, one has to consider that respondents often show content-unrelated response behavior in answering questionnaires. To disentangle the target trait and two such response styles, extreme responding and midpoint responding, Böckenholt (2012a Böckenholt, U. (2012a). Modeling multiple response processes in judgment and choice. Psychological Methods, 17, 665–678. doi:10.1037/a0028111[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) developed an item response model based on a latent processing tree structure. We propose a theoretically motivated extension of this model to also measure acquiescence, the tendency to agree with both regular and reversed items. Substantively, our approach builds on multinomial processing tree (MPT) models that are used in cognitive psychology to disentangle qualitatively distinct processes. Accordingly, the new model for response styles assumes a mixture distribution of affirmative responses, which are either determined by the underlying target trait or by acquiescence. In order to estimate the model parameters, we rely on Bayesian hierarchical estimation of MPT models. In simulations, we show that the model provides unbiased estimates of response styles and the target trait, and we compare the new model and Böckenholt’s model in a recovery study. An empirical example from personality psychology is used for illustrative purposes.     

Improved Insight into and Prediction of Network Dynamics by Combining VAR and Dimension Reduction

To understand within-person psychological processes, one may fit VAR(1) models (or continuous-time variants thereof) to multivariate time series and display the VAR(1) coefficients as a network. This approach has two major problems. First, the contemporaneous correlations between the variables will frequently be substantial, yielding multicollinearity issues. In addition, the shared effects of the variables are not included in the network. Consequently, VAR(1) networks can be hard to interpret. Second, crossvalidation results show that the highly parametrized VAR(1) model is prone to overfitting. In this article, we compare the pros and cons of two potential solutions to both problems. The first is to impose a lasso penalty on the VAR(1) coefficients, setting some of them to zero. The second, which has not yet been pursued in psychological network analysis, uses principal component VAR(1) (termed PC-VAR(1)). In this approach, the variables are first reduced to a few principal components, which are rotated toward simple structure; then VAR(1) analysis (or a continuous-time analog) is applied to the rotated components. Reanalyzing the data of a single participant of the COGITO study, we show that PC-VAR(1) has the better predictive performance and that networks based on PC-VAR(1) clearly represent both the lagged and the contemporaneous variable relations.     

Modeling Interactions Between Latent Variables in Research on Type D Personality: A Monte Carlo Simulation and Clinical Study of Depression and Anxiety

Several approaches exist to model interactions between latent variables. However, it is unclear how these perform when item scores are skewed and ordinal. Research on Type D personality serves as a good case study for that matter. In Study 1, we fitted a multivariate interaction model to predict depression and anxiety with Type D personality, operationalized as an interaction between its two subcomponents negative affectivity (NA) and social inhibition (SI). We constructed this interaction according to four approaches: (1) sum score product; (2) single product indicator; (3) matched product indicators; and (4) latent moderated structural equations (LMS). In Study 2, we compared these interaction models in a simulation study by assessing for each method the bias and precision of the estimated interaction effect under varying conditions. In Study 1, all methods showed a significant Type D effect on both depression and anxiety, although this effect diminished after including the NA and SI quadratic effects. Study 2 showed that the LMS approach performed best with respect to minimizing bias and maximizing power, even when item scores were ordinal and skewed. However, when latent traits were skewed LMS resulted in more false-positive conclusions, while the Matched PI approach adequately controlled the false-positive rate.