The effectiveness of workplace coaching:A meta-analysis of learning and performance outcomes; scale development; theoretical model of individual differences and longitudinal study

The extant literature on workplace coaching is characterised by a lack of theoretical and empirical understanding regarding the effectiveness of coaching as a learning and development tool; the types of outcomes one can expect from coaching; the tools that can be used to measure coaching outcomes; the underlying processes that explain why and how coaching works and the factors that may impact on coaching effectiveness. This thesis sought to address these substantial gaps in the literature with three linked studies. Firstly, a meta-analysis of workplace coaching effectiveness (k = 17), synthesizing the existing research was presented. A framework of coaching outcomes was developed and utilised to code the studies. Analysis indicated that coaching had positive effects on all outcomes. Next, the framework of outcomes was utilised as the deductive start-point to the development of the scale measuring perceived coaching effectiveness. Utilising a multi-stage approach (n = 201), the analysis indicated that perceived coaching effectiveness may be organised into a six factor structure: career clarity; team performance; work well-being; performance; planning and organizing and personal effectiveness and adaptability. The final study was a longitudinal field experiment to test a theoretical model of individual differences and coaching effectiveness developed in this thesis. An organizational sample of 84 employees each participated in a coaching intervention, completed self-report surveys, and had their job performance rated by peers, direct reports and supervisors (a total of 352 employees provided data on participant performance). The results demonstrate that compared to a control group, the coaching intervention generated a number of positive outcomes. The analysis indicated that coachees’ enthusiasm, intellect and orderliness influenced the impact of coaching on outcomes. Mediation analysis suggested that mastery goal orientation, performance goal orientation and approach motivation in the form of behavioural activation system (BAS) drive, were significant mediators between personality and outcomes. Overall, the findings of this thesis make an original contribution to the understanding of the types of outcomes that can be expected from coaching, and the magnitude of impact coaching has on outcomes. The thesis also provides a tool for reliably measuring coaching effectiveness and a theoretical model to understand the influence of coachee individual differences on coaching outcomes.

Self-determination theory and student motivation in social studies in an urban Broward County public high school

This study investigated how students perceived their motivation in high school social studies classes in school and to determine if a correlation exists between students’ grade level, race, gender, and their motivation. The sample included 337 high school students in Broward County, Florida. To assess students’ perceptions on their motivation the academic self-regulation questionnaire was utilized. Results indicate that social studies students show high levels of external regulation, with a mean score at 22.31 on a scale of 36 points. The results show a mean score of 24 on a scale of 28 points for identified regulation among social studies students. Findings revealed that student motivation could be gauged. No statistical significance was found between high school students’ grade level, race, gender, and their motivation in social studies classes. The findings of this study have shown that students at Boyd H. Anderson High School want to learn social studies.

Bayesian Inference in Large-scale Problems

Many modern applications fall into the category of "large-scale" statistical problems, in which both the number of observations n and the number of features or parameters p may be large. Many existing methods focus on point estimation, despite the continued relevance of uncertainty quantification in the sciences, where the number of parameters to estimate often exceeds the sample size, despite huge increases in the value of n typically seen in many fields. Thus, the tendency in some areas of industry to dispense with traditional statistical analysis on the basis that "n=all" is of little relevance outside of certain narrow applications. The main result of the Big Data revolution in most fields has instead been to make computation much harder without reducing the importance of uncertainty quantification. Bayesian methods excel at uncertainty quantification, but often scale poorly relative to alternatives. This conflict between the statistical advantages of Bayesian procedures and their substantial computational disadvantages is perhaps the greatest challenge facing modern Bayesian statistics, and is the primary motivation for the work presented here.

Two general strategies for scaling Bayesian inference are considered. The first is the development of methods that lend themselves to faster computation, and the second is design and characterization of computational algorithms that scale better in n or p. In the first instance, the focus is on joint inference outside of the standard problem of multivariate continuous data that has been a major focus of previous theoretical work in this area. In the second area, we pursue strategies for improving the speed of Markov chain Monte Carlo algorithms, and characterizing their performance in large-scale settings. Throughout, the focus is on rigorous theoretical evaluation combined with empirical demonstrations of performance and concordance with the theory.

One topic we consider is modeling the joint distribution of multivariate categorical data, often summarized in a contingency table. Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. In Chapter 2, we derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions.

Latent class models for the joint distribution of multivariate categorical, such as the PARAFAC decomposition, data play an important role in the analysis of population structure. In this context, the number of latent classes is interpreted as the number of genetically distinct subpopulations of an organism, an important factor in the analysis of evolutionary processes and conservation status. Existing methods focus on point estimates of the number of subpopulations, and lack robust uncertainty quantification. Moreover, whether the number of latent classes in these models is even an identified parameter is an open question. In Chapter 3, we show that when the model is properly specified, the correct number of subpopulations can be recovered almost surely. We then propose an alternative method for estimating the number of latent subpopulations that provides good quantification of uncertainty, and provide a simple procedure for verifying that the proposed method is consistent for the number of subpopulations. The performance of the model in estimating the number of subpopulations and other common population structure inference problems is assessed in simulations and a real data application.

In contingency table analysis, sparse data is frequently encountered for even modest numbers of variables, resulting in non-existence of maximum likelihood estimates. A common solution is to obtain regularized estimates of the parameters of a log-linear model. Bayesian methods provide a coherent approach to regularization, but are often computationally intensive. Conjugate priors ease computational demands, but the conjugate Diaconis--Ylvisaker priors for the parameters of log-linear models do not give rise to closed form credible regions, complicating posterior inference. In Chapter 4 we derive the optimal Gaussian approximation to the posterior for log-linear models with Diaconis--Ylvisaker priors, and provide convergence rate and finite-sample bounds for the Kullback-Leibler divergence between the exact posterior and the optimal Gaussian approximation. We demonstrate empirically in simulations and a real data application that the approximation is highly accurate, even in relatively small samples. The proposed approximation provides a computationally scalable and principled approach to regularized estimation and approximate Bayesian inference for log-linear models.

Another challenging and somewhat non-standard joint modeling problem is inference on tail dependence in stochastic processes. In applications where extreme dependence is of interest, data are almost always time-indexed. Existing methods for inference and modeling in this setting often cluster extreme events or choose window sizes with the goal of preserving temporal information. In Chapter 5, we propose an alternative paradigm for inference on tail dependence in stochastic processes with arbitrary temporal dependence structure in the extremes, based on the idea that the information on strength of tail dependence and the temporal structure in this dependence are both encoded in waiting times between exceedances of high thresholds. We construct a class of time-indexed stochastic processes with tail dependence obtained by endowing the support points in de Haan's spectral representation of max-stable processes with velocities and lifetimes. We extend Smith's model to these max-stable velocity processes and obtain the distribution of waiting times between extreme events at multiple locations. Motivated by this result, a new definition of tail dependence is proposed that is a function of the distribution of waiting times between threshold exceedances, and an inferential framework is constructed for estimating the strength of extremal dependence and quantifying uncertainty in this paradigm. The method is applied to climatological, financial, and electrophysiology data.

The remainder of this thesis focuses on posterior computation by Markov chain Monte Carlo. The Markov Chain Monte Carlo method is the dominant paradigm for posterior computation in Bayesian analysis. It has long been common to control computation time by making approximations to the Markov transition kernel. Comparatively little attention has been paid to convergence and estimation error in these approximating Markov Chains. In Chapter 6, we propose a framework for assessing when to use approximations in MCMC algorithms, and how much error in the transition kernel should be tolerated to obtain optimal estimation performance with respect to a specified loss function and computational budget. The results require only ergodicity of the exact kernel and control of the kernel approximation accuracy. The theoretical framework is applied to approximations based on random subsets of data, low-rank approximations of Gaussian processes, and a novel approximating Markov chain for discrete mixture models.

Data augmentation Gibbs samplers are arguably the most popular class of algorithm for approximately sampling from the posterior distribution for the parameters of generalized linear models. The truncated Normal and Polya-Gamma data augmentation samplers are standard examples for probit and logit links, respectively. Motivated by an important problem in quantitative advertising, in Chapter 7 we consider the application of these algorithms to modeling rare events. We show that when the sample size is large but the observed number of successes is small, these data augmentation samplers mix very slowly, with a spectral gap that converges to zero at a rate at least proportional to the reciprocal of the square root of the sample size up to a log factor. In simulation studies, moderate sample sizes result in high autocorrelations and small effective sample sizes. Similar empirical results are observed for related data augmentation samplers for multinomial logit and probit models. When applied to a real quantitative advertising dataset, the data augmentation samplers mix very poorly. Conversely, Hamiltonian Monte Carlo and a type of independence chain Metropolis algorithm show good mixing on the same dataset.

The goal orientations scale (GOS): Validation for portuguese students

Current research on achievement goals acknowledges that students can manifest different goal patterns. This study aimed to adapt and validate a self-report scale to assess the goal orientations of Portuguese students. A total of 2675 (age range 9–24 years) Portuguese students completed the Goal Orientations Scale (GOS). Through a cross-validation procedure, confirmatory factor analysis and descriptive statistics supports the existence of four different goal orientations: task, self-enhancing, self-defeating and avoidance orientations. The reliability and the internal validity estimates confirm that the GOS is an adequate instrument in assessing student goal orientations.

Dietary Supplement Usage And Motivation In Brazilian Road Runners.

The consumption of dietary supplements is highest among athletes and it can represent potential a health risk for consumers. The aim of this study was to determine the prevalence of consumption of dietary supplements by road runners. We interviewed 817 volunteers from four road races in the Brazilian running calendar. The sample consisted of 671 male and 146 female runners with a mean age of 37.9 ± 12.4 years. Of the sample, 28.33% reported having used some type of dietary supplement. The main motivation for this consumption is to increase in stamina and improve performance. The probability of consuming dietary supplements increased 4.67 times when the runners were guided by coaches. The consumption of supplements was strongly correlated (r = 0.97) with weekly running distance, and also highly correlated (r = 0.86) with the number of years the sport had been practiced. The longer the runner had practiced the sport, the higher the training volume and the greater the intake of supplements. The five most frequently cited reasons for consumption were: energy enhancement (29.5%), performance improvement (17.1%), increased level of endurance (10.3%), nutrient replacement (11.1%), and avoidance of fatigue (10.3%). About 30% of the consumers declared more than one reason for taking dietary supplements. The most consumed supplements were: carbohydrates (52.17%), vitamins (28.70%), and proteins (13.48%). Supplement consumption by road runners in Brazil appeared to be guided by the energy boosting properties of the supplement, the influence of coaches, and the experience of the user. The amount of supplement intake seemed to be lower among road runners than for athletes of other sports. We recommend that coaches and nutritionists emphasise that a balanced diet can meet the needs of physically active people.

Estilos motivacionais de professores: propriedades psicométricas de um instrumento de avaliação

The purpose of this study was to conduct an exploratory factorial analysis of Problems in School, a teachers' motivational styles evaluation instrument, constructed by Deci et al. The original instrument is in a Likert-scale format with the underlying assumption of the existence of a continuum of four different styles contributing to promote students' autonomy. Translated into portuguese, the instrument was applied to 582 elementary and junior high school teachers from several regions of Brazil. Factorial analyses revealed a solution with four orthogonal distinct factors, the authors' initial supposition (existence of a continuum) was not confirmed. In fact, only two opposite styles (both high promotion of autonomy and of control) corresponded to the Deci et al. original ideas. Problems regarding the validity of the other remaining styles emerged. Data was discussed and a revised version of the scale was developed. Directions for further research were also suggested.

Validação da Body Appreciation Scale (BAS), Life Satisfaction Index for the Third Age (LSITA) e do Aging Perception Questionnaire (APQ) para a língua portuguesa no Brasil : um estudo em idosos brasileiros

Universidade Estadual de Campinas . Faculdade de Educação Física

Tradução, adaptação cultural e estrutura fatorial do Body Shape Questionnaire, Body Esteem Scale e Body Appreciation Scale para mulheres brasileiras na meia-idade

Universidade Estadual de Campinas . Faculdade de Educação Física

Tradução, adaptação cultural e validação da escala Moorong Self-Efficacy Scale (MSES) para o português no Brasil = : Translation, cultural adaptation and validation of Moorong Self-Efficacy Scale (MSES) into Brazilian Portuguese

Universidade Estadual de Campinas . Faculdade de Educação Física

Adaptação e validação da escla ASKAS - Aging Sexual Knowledge and Attitudes Scale em idosos brasileiros

Universidade Estadual de Campinas . Faculdade de Educação Física

O uso de videogames, jogos de computador e internet por uma amostra de universitários da Universidade de São Paulo

OBJETIVO: Avaliar uso de jogos eletrônicos (videogames, jogos de computador e internet) em uma amostra de universitários. MÉTODO: Um questionário a respeito de comportamentos relacionados ao uso de jogos eletrônicos, contendo a escala Problem Videogame Playing (PVP), foi aplicado em 100 alunos da Universidade de São Paulo (USP). RESULTADOS: A maioria (83%) relatou ter jogado no último ano, dentre a qual 81,9% eram homens, 51,8% jogavam de 1 a 2 horas por sessão; 74,4% afirmaram que jogar não interfere em seus relacionamentos sociais e 60,5%, que o uso de jogos violentos não influencia sua agressividade. Os estudantes dividiram-se entre jogadores ocasionais e frequentes, diferenciando-se por duração de cada sessão, jogo preferido, motivação para jogar, e influência do jogo na vida social. Cerca de 5% relataram só parar de jogar quando interrompidos, normalmente jogar mais de 4 horas por sessão e se relacionar mais com amigos virtuais, sugerindo maior envolvimento com a atividade. Na escala PVP, 15,8% da amostra preencheu mais da metade dos itens, indicando consequências adversas associadas ao uso dos jogos eletrônicos. CONCLUSÃO: Observou-se que o uso de jogos eletrônicos é comum entre os estudantes da USP e que uma parcela apresenta problemas relacionados ao excesso de jogo.

Cross-cultural adaptation, validation and reliability of the Body Area Scale for Brazilian adolescents

The aim of this study was to translate, validate and verify the reliability of the Body Area Scale (BAS). Participants were 386 teenagers, enrolled in a private school. Translation into Portuguese was conducted. The instrument was evaluated for internal consistency and construct validation analysis. Reproducibility was evaluated using the Wilcoxon test and the coefficient of interclass correlation. The BAS demonstrated good values for internal consistency (0.90 and 0.88) and was able to discriminate boys and girls according to nutritional state (p = 0.020 and p = 0.026, respectively). BAS scores correlated with adolescents' BMI (r = 0.14, p = 0.055; r = 0.23, p = 0.001) and WC (r =0.13, p = 0.083; r = 0.22, 0.002). Reliability was confirmed by the coefficient of inter-class correlation (0.35, p < 0.001; 0.60, p < 0.001) for boys and girls, respectively. The instrument performed well in terms of understanding and time of completion. BAS was successfully translated into Portuguese and presented good validity when applied to adolescents.

Psychometric evaluation of the Disordered Eating Attitude Scale (DEAS)

Eating attitudes are defined as beliefs, thoughts, feelings, behaviors and relationship with food. They could influence people’s food choices and their health status. Objective: This study aimed to adapt from Portuguese to English the Disordered Eating Attitude Scale (DEAS) and evaluate its validity and reliability. The original scale in Portuguese was translated and adapted into English and was applied to female university students of University of Minnesota—USA (n = 224). Internal consistency was determined (Cronbach’s Alpha). Convergent validity was assessed by correlations between Eating Attitude Test-26 (EAT-26) and Restrain Scale (RS). Reliability was evaluated applying twice the scale to a sub-sample (n = 30). The scale was back translated into Portuguese and compared with the original version and discrepancies were not found. The internal consistency was .76. The DEAS total score was significantly associated with EAT-26 (r = 0.65) and RS (r = 0.69) scores. The correlation between test–retest was r = 0.9. The English version of DEAS showed appropriate internal consistency, convergent validity and test–retest reliability and will be useful to assess eating attitudes in different population groups in English spoken countries

Direct measurement of intrinsic atomic scale magnetostriction

Using differential x-ray absorption spectroscopy (DiffXAS) we have measured and quantified the intrinsic, atomic-scale magnetostriction of Fe(81)Ga(19). By exploiting the chemical selectivity of DiffXAS, the Fe and Ga local environments have been assessed individually. The enhanced magnetostriction induced by the addition of Ga to Fe was found to originate from the Ga environment, where lambda(gamma,2)(approximate to (3/2)lambda(100)) is 390 +/- 40 ppm. In this environment, < 001 > Ga-Ga pair defects were found to exist, which mediate the magnetostriction by inducing large strains in the surrounding Ga-Fe bonds. For the first time, intrinsic, chemically selective magnetostrictive strain has been measured and quantified at the atomic level, allowing true comparison with theory.

EVALUATING VIBRATIONS ON A SMALL-SCALE MODEL OF A TIMBER FOOTBRIDGE

In Brazil, the study of pedestrian-induced vibration on footbridges has been undertaken since the early 1990s, for concrete and steel footbridges. However, there are no recorded studies of this kind for timber footbridges. Brazilian code ABNT NBR 7190 (1997) gives design requirements only for static loads in the case of timber footbridges, without considering the serviceability limit state from pedestrian-induced vibrations. The aim of this work is to perform a theoretical dynamic, numerical and experimental analysis on simply-supported timber footbridges, by using a small-scale model developed from a 24 m span and 2 m width timber footbridge, with two main timber beams. Span and width were scaled down (1:4) to 6 m e 0.5 in, respectively. Among the conclusions reached herein, it is emphasized that the Euler-Bernoulli beam theory is suitable for calculating the vertical and lateral first natural frequencies in simply-supported timber footbridges; however, special attention should be given to the evaluation of lateral bending stiffness, as it leads to conservative values.