Fodor on global cognition and scientific inference

This paper addresses the extent to which quotidian cognition is like scientific inference by focusing on Jerry Fodor's famous analogy. I specifically consider and rebut a recent attempt made by Tim Fuller and Richard Samuels to deny the usefulness of Fodor's analogy. In so doing, I reveal some subtleties of Fodor's arguments overlooked by Fuller and Samuels and others. Recognizing these subtleties provides a richer appreciation of the analogy, allowing us to gain better traction on the issue concerning the extent to which everyday cognition is like scientific inference. In the end, I propose that quotidian cognition is indeed like scientific inference, but not precisely in the way Fodor claims it is.     

A Comparison of Two-Stage Approaches for Fitting Nonlinear Ordinary Differential Equation Models with Mixed Effects

Several approaches exist for estimating the derivatives of observed data for model exploration purposes, including functional data analysis (FDA; Ramsay &; Silverman, 2005 Ramsay, J. O., &; Silverman, B. W. (2005). Functional data analysis (2nd ed.). New York, NY: Springer-Verlag. [Google Scholar]), generalized local linear approximation (GLLA; Boker, Deboeck, Edler, &; Peel, 2010 Boker, S. M., Deboeck, P. R., Edler, C., &; Peel, P. K. (2010). Generalized local linear approximation of derivatives from time series. In S. Chow, E. Ferrer, &; F. Hsieh (Eds.), Statistical methods for modeling human dynamics: An interdisciplinary dialogue (pp. 161–178). New York, NY: Taylor &; Francis. [Google Scholar]), and generalized orthogonal local derivative approximation (GOLD; Deboeck, 2010 Deboeck, P. R. (2010). Estimating dynamical systms: Derivative estimation hints from Sir Ronald A. Fisher. Multivariate Behavioral Research, 45, 725–745. doi:10.1080/00273171.2010.498294[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]). These derivative estimation procedures can be used in a two-stage process to fit mixed effects ordinary differential equation (ODE) models. While the performance and utility of these routines for estimating linear ODEs have been established, they have not yet been evaluated in the context of nonlinear ODEs with mixed effects. We compared properties of the GLLA and GOLD to an FDA-based two-stage approach denoted herein as functional ordinary differential equation with mixed effects (FODEmixed) in a Monte Carlo (MC) study using a nonlinear coupled oscillators model with mixed effects. Simulation results showed that overall, the FODEmixed outperformed both the GLLA and GOLD across all the embedding dimensions considered, but a novel use of a fourth-order GLLA approach combined with very high embedding dimensions yielded estimation results that almost paralleled those from the FODEmixed. We discuss the strengths and limitations of each approach and demonstrate how output from each stage of FODEmixed may be used to inform empirical modeling of young children’s self-regulation.     

What behaviours do students consider academically dishonest? Findings from a survey of Canadian undergraduate students

This paper identifies those behaviours that students perceive to be academically dishonest and sheds light on several demographic, academic and situational factors that predict students’ perceptions of academic dishonesty. Data for this investigation were obtained through self-administered questionnaires from a sample of 321 undergraduate students attending university in a western Canadian city during the academic year 2007–2008. There was a high extent of leniency in students’ definitions of what behaviours constitute academic dishonesty, particularly for situations involving plagiarism and helping somebody else cheat. Sex, importance of academic ethic, strength of academic ability, deep learning strategy, and frequency of witnessing peers cheat made unique contributions to the prediction of students’ perceptions of dishonesty. Implications of these findings for institutional interventions are discussed.     

Effect of Analogy Instructions with an Internal Focus on Learning a Complex Motor Skill

This study examined the effects of an analogy in learning breaststroke swimming. Two groups of participants had 20 lessons on how to increase their stroke length. The participants in the experimental condition received an analogy with an internal focus of attention. Inter-limb coordination showed qualitative changes in this group: a greater increase in swimming efficiency (i.e., a coordination closer to anti-phase [?50° before learning and ?125° after] and a 10% decrease in the time spent in-phase). The findings showed that an internal focus of attention induced by analogy could be beneficial in improving the quality of inter-limb swimming coordination.     

Regime-Switching Bivariate Dual Change Score Model

Mixture structural equation model with regime switching (MSEM-RS) provides one possible way of representing over-time heterogeneities in dynamic processes by allowing a system to manifest qualitatively or quantitatively distinct change processes conditional on the latent “regime” the system is in at a particular time point. Unlike standard mixture structural equation models such as growth mixture models, MSEM-RS allows individuals to transition between latent classes over time. This class of models, often referred to as regime-switching models in the time series and econometric applications, can be specified as regime-switching mixture structural equation models when the number of repeated measures involved is not large. We illustrate the empirical utility of such models using one special case—a regime-switching bivariate dual change score model in which two growth processes are allowed to manifest regime-dependent coupling relations with one another. The proposed model is illustrated using a set of longitudinal reading and arithmetic performance data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998–99 study (ECLS-K; U.S. Department of Education, National Center for Education Statistics, 2010).     

Longitudinal Multi-Trait-State-Method Model Using Ordinal Data

Multi-trait multi-method (MTMM) models provide a way to assess convergent and discriminant validity when multiple traits are measured by multiple methods. In recent years, longitudinal extensions of MTMM models have been proposed in the structural equation modeling framework to evaluate whether and how the trait as well as method factors change over time. We propose a novel longitudinal ordinal MTMM model that can be used to effectively distinguish volatile “state” processes from “trait” processes that tend to remain stable and invariant over time. The proposed model, termed a longitudinal multi-trait-state-method (LM-TSM) model, combines 3 key modeling components: (a) a measurement model for ordinal data, (b) a vector autoregressive moving average model at the latent level to examine changes in the state as well as the method factors over time, and (c) a second-order factor-analytic model to capture time-invariant traits as shared variances among the state factors across all measurement occasions. Data from the Affective Dynamics and Individual Differences (ADID; Emotions and Dynamic Systems Laboratory, 2010 Emotions and Dynamic Systems Laboratory. (2010). The Affective Dynamics and Individual Differences (ADID) study: Developing non-stationary and network-based methods for modeling the perception and physiology of emotions. . Unpublished manual, University of North Carolina at Chapel Hill. [Google Scholar]) study was used to illustrate the proposed longitudinal LM-TSM model. Methodological issues associated with fitting the LM-TSM model are discussed.     

Influence of coaching efficacy and coaching competency on athlete‐level moral variables in Botswana youth soccer

This study examined coach‐perceived coaching efficacy and athlete‐perceived coaching competency, perceptions of coaches' endorsement of unfair play, and team norm for aggression on athlete‐level moral variables in Botswana youth soccer. Participants were youth soccer players (n = 506) and their coaches (n = 24). Players completed the coaching competency scale, the Judgments About Moral Behavior in Youth Sports Questionnaire, and the Team Norm Questionnaire. Coaches completed the Coaching Efficacy Scale. Multilevel analysis revealed that team norm for aggression, athletes' perceptions of their coaches' endorsement of aggression/cheating, and Game Strategy Coaching Competency were significant predictors of athletes' likelihood to aggress and perceptions of peer cheating. The findings contribute to previous research demonstrating the influence of the coach on athletes' antisocial behaviors.     

Nonlinear Regime-Switching State-Space (RSSS) Models

Nonlinear dynamic factor analysis models extend standard linear dynamic factor analysis models by allowing time series processes to be nonlinear at the latent level (e.g., involving interaction between two latent processes). In practice, it is often of interest to identify the phases—namely, latent “regimes” or classes—during which a system is characterized by distinctly different dynamics. We propose a new class of models, termed nonlinear regime-switching state-space (RSSS) models, which subsumes regime-switching nonlinear dynamic factor analysis models as a special case. In nonlinear RSSS models, the change processes within regimes, represented using a state-space model, are allowed to be nonlinear. An estimation procedure obtained by combining the extended Kalman filter and the Kim filter is proposed as a way to estimate nonlinear RSSS models. We illustrate the utility of nonlinear RSSS models by fitting a nonlinear dynamic factor analysis model with regime-specific cross-regression parameters to a set of experience sampling affect data. The parallels between nonlinear RSSS models and other well-known discrete change models in the literature are discussed briefly.     

Is energy expenditure in emotion regulation dependent on individual differences and the specific emotion in question?

This study tested the hypothesis that the degree of self-control exerted in suppressing emotions would depend on the combination of personality (independence and dutifulness/self-discipline) and the specific type of emotion being suppressed (anger vs. appreciation). In a between-subjects design, 245 college students were induced to experience either anger or appreciation and were then instructed to suppress their emotional expression. Self-control strength was measured using a handgrip task. Exertion of self-control strength over two time points was differentially associated with levels of independence and dutifulness/self-discipline (conscientiousness) and emotion suppression condition. Specifically, individuals higher in dutifulness/self-discipline had a harder time if they were suppressing appreciation than if they were suppressing anger at others, whereas individuals higher in independence had a harder time if they were suppressing anger at others than if they were suppressing appreciation. Implications for understanding personality, self-control, and emotion regulation are discussed.