Within an achievement motivation theoretical framework, there are factors thought to most heavily influence performance and task difficulty selection. More specifically, motivational climates, feedback, confidence, and anxiety have all been identified as important factors influencing outcomes within performance settings. Much of the literature in the area of achievement motivation has focused on on the effects of mastery- and ego-oriented feedback on performance within academic settings and has received limited attention in the sport psychology literature within an athletic setting. Given the demonstrated effects of mastery- and ego-oriented feedback on performance, the importance of performance within the athletic context, and the scant literature examining the effects of feedback on athletic performance, the influence of feedback on sport performance needed to be empirically examined. The primary aim of this study was to provide a clearer understanding of the relationship of factors influencing athletic performance, with the ultimate goal of moving research toward a greater understanding of how optimal performance is achieved. As a result, this research may prove applicable to researchers, coaches, and athletes working toward optimal performance. In this study, I examined how mastery- and ego-oriented feedback influenced youth athletes' soccer performance, task difficulty selection, confidence, and anxiety. Youth soccer athletes (n = 71) participated in a soccer kicking task consisting of two trials. Between subjects ANCOVA analyses revealed athletes receiving mastery-oriented feedback performed significantly better on the soccer kicking task than athletes receiving ego-oriented feedback. No differences were discovered on task difficulty selection, confidence, or anxiety. Providing athletes mastery-oriented feedback before or after skill execution could be helpful in the development of athletic skill development and performance. Limitations of the present study and questions to examine in future research are also discussed.

Applications of speech recognition have evolved in recent years from simple transcription tasks to metadata analysis. This thesis explores the use of speech recognition for automated fatigue detection. The fatigue detection system relies on accurate phonetic alignments from a speech recognition system. The main challenge addressed in this thesis was to make the process of phonetic alignment using speech recognition robust to out of vocabulary words. This requirement was achieved by incorporating confidence measures, which significantly reduce false positives in speech recognition output. This allowed the performance of the fatigue detection system to match the results of other cognitive tests based on the Sleep Onset Latency (SOL) and Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE). Confidence measures reduced the squared error between voice-based fatigue prediction and SAFTE by 20% when 67.1% of the words in the test set were out of vocabulary words.

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Women remain underrepresented in computer technology careers and university majors, and adolescent girls shy away from high school computer science courses. More information is needed about females who are attracted to computer technology. This study describes the online activities of young adolescent girls ages 12-14 who are high-end users of computer technology. Three developmental tasks of adolescence (search for identity, pursuit of social connections, and desire for a sense of competence and accomplishment) were used to frame explorations of the girls' online activities. Eight girls were interviewed, the personal web sites of six girls were analyzed, and postings on a message board for young girls interested in online activities were reviewed. Patterns and themes that emerged from the data indicated that Internet technology was an effective match for the informants' developmental tasks. Specific inferences included: (1)Online technologies offered the informants multiple ways of negotiating social relationships; (2) Internet use supported the informants' engagement in personalized, self-directed, and self-initiated learning; (3) Support from parents, siblings, and peers provided the environment for each girl to develop confidence and competence in Internet use; and(4) The informants' use of the internet reflected women's ways of knowing. / Ph. D.

The focus of this research is to examine the impact of emotional intelligence on consumer decision making. Several research goals are presented: 1) to develop and test a practical domain-specific scale of emotional ability, 2) to identify the influence of emotional ability on behavioral individual and group level performance in a consumer context, 3) and to identify how performance is further influenced by cognitive ability, cognitive and emotional confidence and calibration between perceived (i.e., confidence) and actual ability. Three studies were conducted to meet these goals. Study 1 involved the development and validation of a consumer emotional ability scale (CEAS), based on four underlying emotional abilities (i.e., perceiving, facilitating, understanding, managing). This instrument allowed for further examination of how emotional intelligence affected performance among consumer relationships. A proposed conceptual model was examined in an individual (study 2) and small group (study 3) context using the CEAS scale, along with additional items to assess the influence of cognitive ability, cognitive and emotional confidence, and calibration on performance in the consumer domain of healthy food choices. / Ph. D.

Yes / The trust and confidence of citizens in their governments has been declining in recent decades. Electronic government (e-government) is seen as a means to reverse this trend. Despite conflicting conclusions in the literature, there is a consensus that e-government-led transformation can improve citizen confidence and trust in government. This research investigates the influence of e-government-led transformation on citizen trust and confidence in the context of a developing country, the Kingdom of Bahrain. A conceptual model is developed, tested and validated using an online survey targeting ordinary citizens of the country. Based on 313 responses, the findings suggest that citizen trust and confidence is positively influenced by a government transformation, and this relationship is mediated by both government performance and citizen satisfaction. In addition, the results show that key factors must be met to achieve transformed government through the use of e-government systems: transparency, accountability, and meeting citizens’ expectations.

Using a correlational design, this study examined relationships among and between differentiation, profile elevation, gender and educational level (predictors) and depression, confidence, and vocational identity (criterion). Clients presenting for counseling services (n = 90) with a career concern at a large, metropolitan university were included in the study. Six assumptions were examined using three single hierarchical regression analyses to reveal relationships among and between variables. Two research assumptions were confirmed at the .05 level of significance. Bivariate correlations were computed to examine the structure coefficients. Beta weights and structure coefficients were examined to determine the relative contribution of the predictors in the regression model. Results indicated that differentiation, profile elevation, gender and educational level did not predict significant variance in depression and vocational identity. However, differentiation, profile elevation, and educational level did significantly predict confidence (p< .0001).

Research shows that student teachers find the mentor teacher and the student teaching experience itself the two most influential factors in their practicum experience. This study examined five student teachers and the two mentor teachers of each in elementary school settings within a metropolitan school district in North Texas. Lave and Wenger’s (1991, 2002) community of practice theory informed this study. Data sources included mentor teacher interviews, student teacher interviews, student teacher observations, student teacher/mentor teacher dialogue journals, and student teacher reflections. A collective case study approach was followed to gain a detailed understanding of the experiences of the five student teachers, looking specifically at their confidence in teaching and the factors associated with it. Findings indicated that the confidence in teaching of all five student teachers changed throughout their practicum experiences. Results suggested many factors influenced these changes. Student teachers shared that the student teaching experience, the grade level/subjects taught, their relationships with their students, and their relationships with their mentor teachers contributed to their confidence. The mentor teachers perceived that student teachers’ confidence could be influenced by consistency in classroom management and their interactions with their mentor teachers. Two areas of influence on student teacher confidence not uncovered by other researchers were the quest of student teachers for perfection while teaching and the need of mentor teachers for control of the content presented by the student teachers, especially during the months prior to state-mandated testing. Implications of the study included the need for university supervisors to mediate between student teachers and mentor teachers in promoting shared ownership of student learning within that community of practice enabled by student teaching.

This research examined the performance of three parametric methods for confidence intervals: the classical, the Bonferroni, and the bootstrap-t method, as applied to estimating the mean of voucher populations in accounting. Usually auditing populations do not follow standard models. The population for accounting audits generally is a nonstandard mixture distribution in which the audit data set contains a large number of zero values and a comparatively small number of nonzero errors. This study assumed a situation in which only overstatement errors exist. The nonzero errors were assumed to be normally, exponentially, and uniformly distributed. Five indicators of performance were used. The classical method was found to be unreliable. The Bonferroni method was conservative for all population conditions. The bootstrap-t method was excellent in terms of reliability, but the lower limit of the confidence intervals produced by this method was unstable for all population conditions. The classical method provided the shortest average width of the confidence intervals among the three methods. This study provided initial evidence as to how the parametric bootstrap-t method performs when applied to the nonstandard distribution of audit populations of line items. Further research should provide a reliable confidence interval for a wider variety of accounting populations.

O objetivo deste trabalho é averiguar a existência de incremento de acurácia nos modelos de previsão das diferentes categorias de consumo das famílias nos EUA ao se considerar a incerteza macroeconômica como variável explicativa. Grande parte dos trabalhos existentes na literatura consideram o índice da pesquisa de sentimento do consumidor da Universidade de Michigan ou a confiança do consumidor do Conference Board como variáveis alternativas capazes de antecipar o comportamento do consumo das famílias. Como se tratam de entrevistas que podem carregar parcialidade nas respostas e que não estão estritamente ligadas aos movimentos da incerteza, propomos a utilização de uma medida que agregue econometricamente as variações da incerteza macroeconômica, de tal forma que nossos modelos contenham informações mais refinadas sobre o comportamento da economia. A proposta e comparar o poder preditivo de quatro grupos de modelos econométricos para três horizontes temporais distintos (um, três e doze meses à frente). Para tal, consideramos a utilização do método de avaliação conjunta de superioridade preditiva, o Model Confidence Set. Os resultados obtidos apontam para a existência de contribuição preditiva ao incluir uma variável de incerteza macroeconômica para a previsão do consumo, em especial nos modelos de previsão um passo (mês) à frente. / The aim of this work is to verify the existence of an increase in forecasting models accuracy of different categories of household consumption in USA when considering macroeconomic uncertainty as an explanatory variable. Much of the work in the literature considers the University of Michigan Consumer Sentiment Survey Index or Conference Board Consumer Confidence as alternative variables capable of anticipating household consumption behavior. Because these indexes are composed of interviews that may carry a certain amount of bias in responses and are not strictly linked to the movements of uncertainty, we propose the use of a measure that econometrically adds variations of macroeconomic uncertainty, so that our models contain more refined information on the behavior of the economy. The proposal is to compare the predictive power of four groups of econometric models for three distinct time horizons (one, three and twelve months ahead). For this, we consider the use of the joint evaluation method of predictive superiority, Model Confidence Set. The results obtained point to the existence of a predictive contribution by including a macroeconomic uncertainty variable for consumption forecast, especially in the one step (month) ahead forecast models.