This study examined the motivations pre-service teachers possess as they progress though a teacher education program. Using Watt and Richardson’s (2007) Factors Influencing Teaching Choice (FIT-Choice) model as the theoretical underpinnings, the following research questions set the foundation for this study: 1) Do pre-service teachers’ motivation to pursue a teaching career change over the course of a teacher education program, and 2) Is there a relationship between pre-service teachers’ values and their satisfaction with their choice to pursue a teaching career? Quantitative results indicate significant drops in motivation from students’ Freshman/Sophomore year to students’ Graduate year. Qualitative results demonstrated a greater frequency of responses for social utility values, intrinsic motivation, positive prior teaching and learning experiences, career development aspirations, and epistemic values. / Educational Psychology

Minimal research has examined the interrelationship between motivation, place attachment, and the need to belong in a residential camping environment. The purpose of this study was to better understand the role of place attachment and the need to belong in facilitating 4-H Camp Graham campers and counselors interest in returning to residential 4-H summer camp year after year. All participants included in this study were at least 18 years of age, graduated from high school, former 4-H members, and attended 4-H camp for at least two consecutive years. Three camping clusters participated in focus group interviews for a total of 21 participants. A fourth camping cluster and participants unable to attend their designated focus group, were invited complete an online survey. Overall, campers and counselors were primarily motivated to return to camp each year due to the relationships, memories, and sense of belonging formed at camp. While nature and location played a role in the camp experience by providing a secluded environment free from outside influence, these attachments were secondary. Attachment to camp grew over time and participants valued the camp experience highly and tended to choose camp friendships and the camp experience over other opportunities. Longevity at camp influenced the strength of attachment. This research suggests that intentionality in these areas of staff training and program planning are critical to camper and counselor connection to camp. Additionally, this research provides tangible evidence that points to the value of sharing the residential camping experience with potential funders and parents. / Master of Science in Life Sciences

Research reviews have shown that the use of formative assessment in classroom practice can substantially improve student achievement. However, a strong research base about how to support teachers’ implementation of such formative classroom practice is lacking. In this thesis, I investigate the effects of a comprehensive professional development programme (PDP) in formative assessment on teachers’ classroom practice and students’ achievement in mathematics. In addition, I identify reasons for the changes made in the teachers’ formative classroom practice. Fourteen randomly selected year - 7 mathematics teachers participated in the PDP. The teachers’ formative classroom practice before and after attending the programme was analysed and described, and reasons for their change in practice were explored. The effect of the changes in formative classroom practice on students’ mathematics achievement was examined using pre- and post-tests administered to both the intervention group and a control group. A mixed methods approach with classroom observations, teacher interviews, questionnaires and student achievement tests in mathematics was used in the studies included in the thesis. The results show that the teachers used aspects of formative assessment in their classroom practice before the PDP, but that there was plenty of room for development towards a more effective formative assessment practice. Several possibilities for developing the practice were identified. After the PDP the teachers believed in the idea of formative assessment and were motivated to make changes towards a more formative classroom practice. The teachers included new formative assessment activities in their classroom practice, but in different ways and to different degrees. The characteristics of these changes were identified, and also the characteristics of the PDP that the teachers found to be influential for their development of the formative classroom practice. Results also show that the teachers’ motivational beliefs held after the PDP was an explanatory factor for their changes in practice. However, the formative assessment practice the teachers implemented did not have a significant effect on their students’ achievement compared to the control group. In addition, there was no correlation between the number of formative assessment activities implemented by the teachers and their students’ achievement gains. Reasons for these non-effects on student achievement, and for the teachers’ degree and type of implementation of formative assessment in the classroom practice, are discussed in the thesis.

Thesis (MBA)--Stellenbosch University, 2001. / ENGLISH ABSTRACT: Commercial banks, investment banks, insurance companies, non-financial firms, and pension funds hold portfolios of assets that may include stocks, bonds, currencies, and derivatives. Each institution needs to quantify the amount of risk its portfolio is exposed to in the course of a day, week, month, or year. Extreme events in financial markets, such as the stock market crash of October 1987, are central issues in finance and particularly in risk management and financial regulation. A method called value at risk (VaR) can be used to estimate market risk. Value at risk is a powerful measure of risk that is gaining wide acceptance amongst institutions for the management of market risk. Value at Risk is an estimate of the largest lost that a portfolio is likely to suffer during all but truly exceptional periods. More precisely, the VaR is the maximum loss that an institution can be confident it would lose a certain fraction of the time over a particular period. The power of the concept is its generality. VaR measures are applicable to entire portfolios - encompassing many asset categories and multiple sources of risk. As with its power, the challenge of calculating VaR also stems from its generality. In order to measure risk in a portfolio using VaR, some means must be found for determining a return distribution for the portfolio. There exists a wide range of literature on different methods of implementing VaR. But, when one attempts to apply the results, several questions remain open. For example, given a VaR measure, how can the risk manager test that the particular measure at hand is appropriately specified? And secondly, given two different VaR measures, how can the risk manager pick the best measure? Despite the popularity of VaR for measuring market risk, no consensus has yet been reach as to the best method to implement this risk measure. The absence of consensus is in part derived from the realization that each method currently in use has some significant drawbacks. The aim of this project is threefold: to introduce the reader to the concept of VaR; present the theoretical basis for the general approaches to VaR computations; and to introduce and apply Extreme Value Theory to VaR calculations. The general approaches to VaR computation falls into three categories, namely, Analytic (Parametric) Approach, Historical Simulation Approach, and Monte Carlo Simulation Approach. Each of these approaches has its strengths and weaknesses, which will study more closely. The extreme value approach to VaR calculation is a relatively new approach. Since most observed returns are central ones, traditional VaR methods tend to ignore extreme events and focus on risk measures that accommodate the whole empirical distribution of central returns. The danger of this approach is that these models are prone to fail just when they are needed most - in large market moves, when institutions can suffer very large losses. The extreme value approach is a tool that attempts to provide the user with the best possible estimate of the tail area of the distribution. Even in the absence of useful historical data, extreme value theory provides guidance on the kind of distribution that should be selected so that extreme risks are handled conservatively. As an illustration, the extreme value method will be applied to a foreign exchange futures contract. The validity of EVT to VaR calculations will be tested by examining the data of the Rand/Dollar One Year Futures Contracts. An extended worked example will be provided wherein which attempts to highlight the considerable strengths of the methods as well as the pitfalls and limitations. These results will be compared to VaR measures calculated using a GARCH(l,l) model. / AFRIKAANSE OPSOMMING: Handelsbanke, aksepbanke, assuransiemaatskappye, nie-finansiële instellings en pensioenfondse beskik oor portefeuljes van finansiële bates soos aandele, effekte, geldeenhede en afgeleides. Elke instelling moet die omvang kan bepaal van die risiko waaraan die portefeulje blootgestel is in die loop van 'n dag, week, maand of jaar. Uitsonderlike gebeure op finansiële markte, soos die ineenstorting van die aandelemark in Oktober 1987, is van besondere belang vir finansies en veral vir risikobestuur en finansiële regulering. 'n Metode wat genoem word Waarde op Risiko (WoR), kan gebruik word om markverliese te meet. WoR is 'n kragtige maatstaf vir risiko en word deur vele instellings gebruik vir die bestuur van mark-risiko. Waarde op Risiko is 'n raming van die grootste verlies wat 'n portefeulje moontlik kan ly gedurende enige tydperk, met uitsluiting van werklik uitsonderlike tydperke. Van nader beskou, is WoR die maksimum verlies wat 'n instelling kan verwag om gedurende 'n sekere tydperk binne 'n bepaalde periode te ly. Die waarde van die konsep lê in die algemene aard daarvan. WoR metings is van toepassing op portefeuljes in dié geheel en dit omvat baie kategorieë bates en veelvuldige bronne van risiko. Soos met die waarde van die konsep, hou die uitdaging om WoR te bereken ook verband met die algemene aard van die konsep. Ten einde die risiko te bepaal in 'n portefeulje waar WoR gebruik word, moet metodes gevind word waarvolgens 'n opbrengsverdeling vir die portefeulje vasgestel kan word. Daar bestaan 'n groot verskeidenheid literatuur oor die verskillende metodes om WoR te implementeer. Wanneer dit egter kom by die toepassing van die resultate, bly verskeie vrae onbeantwoord. Byvoorbeeld, hoe kan die risikobestuurder aan die hand van 'n gegewe WoR-maatstaf toets of die spesifieke maatstaf reg gespesifiseer is? Tweedens, hoe kan die risikobestuurder die beste maatstaf kies in die geval van twee verskillende WoR-maatstawwe? Ondanks die feit dat WoR algemeen gebruik word vir die meting van markrisiko, is daar nog nie konsensus bereik oor die beste metode om hierdie benadering tot risikometing te implementeer nie. Die feit dat daar nie konsensus bestaan nie, kan deels daaraan toegeskryf word dat elkeen van die metodes wat tans gebruik word, ernstige leemtes het. Die doel van hierdie projek is om die konsep WoR bekend te stel, om die teoretiese grondslag te lê vir die algemene benadering tot die berekening van WoR en om die Ekstreme Waarde-teorie bekend te stel en toe te pas op WoR-berekenings. Die algemene benadering tot die berekening van WoR word in drie kategorieë verdeel naamlik die Analitiese (Parametriese) benadering, die Historiese simulasiebenadering en die Monte Carlo-simulasiebenadering. Elkeen van die benaderings het sterk- en swakpunte wat van nader ondersoek sal word. Die Ekstreme Waarde-benadering tot WoR is 'n relatief nuwe benadering. Aangesien die meeste opbrengste middelwaarde-gesentreer is, is tradisionele WoR-metodes geneig om uitsonderlike gebeure buite rekening te laat en te fokus op risiko-maatstawwe wat die hele empiriese verdeling van middelwaarde-gesentreerde opbrengste akkommodeer. Die gevaar bestaan dan dat hierdie modelle geneig is om te faal juis wanneer dit die meeste benodig word, byvoorbeeld in die geval van groot markverskuiwings waartydens organisasies baie groot verliese kan ly. Daar word beoog om met behulp van die Ekstreme Waarde-benadering aan die gebruiker die beste moontlike skatting van die stert-area van die verdeling te gee. Selfs in die afwesigheid van bruikbare historiese data verskaf die Ekstreme Waarde-teorie riglyne ten opsigte van die aard van die verdeling wat gekies moet word, sodat uiterste risiko's versigtig hanteer kan word. Ten einde hierdie metode te illustreer, word dit in hierdie studie toegepas op 'n termynkontrak ten opsigte van buitelandse wisselkoerse. Die geldigheid van die Ekstreme Waarde-teorie ten opsigte van WoR berekenings word getoets deur die data van die Rand/Dollar Eenjaartermynkontrak te bestudeer. 'n Volledig uitgewerkte voorbeeld word verskaf waarin die slaggate en beperkings asook die talle sterkpunte van die model uitgewys word. Hierdie resultate sal vergelyk word met 'n WoR-meting wat bereken is met die GARCH (1,1) model.

Business intelligence (BI) systems have been widely recognized as a leading technology for many years. However, despite the high priority and importance placed on BI, there has been a significant lack of BI system implementation (BISI) success. BI systems are not considered to be conventional information systems (IS) and often rely on the integration of a complex information infrastructure. Consequently, the degree of information quality (IQ) and system quality (SQ) have not met expectations for BISI success. This study was designed to determine how an organization may gain benefits in the context of BISI by uncovering the antecedents and critical value factors (CVFs) of SQ and IQ necessary to derive greater BISI success. In phase one, a list of BISI SQ and IQ characteristics were collected through literature discovery and an open-ended questionnaire delivered to a group of BI user experts. The collected items were grouped and categorized based on their similarities. In phase two of the study 257 survey responses were collected from BI users to measure the level of importance, i.e. value, they placed on SQ and IQ characteristics. Exploratory factor analysis (EFA) via principal component analysis (PCA) was then used to uncover the CVFs of SQ and IQ that influence BISI success. Two highly reliable CVFs for SQ of BISI with a cumulative variance of nearly 62% and three highly reliable CVFs for IQ of BISI with a cumulative variance of over 75% were subsequently identified. In phase three of the study, an extended conceptual model for IS success was validated to assess the uncovered CVFs of SQ and IQ, as well as their influence on the constructs of perceived SQ of BISI and perceived IQ of BISI. Employing partial least squares (PLS), a subset of structural equation modeling (SEM), the research model was then used to assess the dimensions of perceived SQ of BISI and perceived IQ of BISI as antecedents of the constructs of perceived user systems satisfaction and perceived user information satisfaction from BISI. The crossover effects of perceived user systems and information satisfaction from BISI were also analyzed. The results identified two SQ CVFs of BISI (integration flexibility SQ and reliability SQ) that demonstrated a significant positive impact on perceived SQ for BISI as well as three IQ CVFs of BISI (representation IQ, intrinsic IQ, and accessibility IQ) that had a significant positive impact on perceived IQ of BISI. The constructs of perceived user systems satisfaction and perceived user information satisfaction from BISI had explained variances of R2 = .576 and .589 respectively. Additionally, 12 items of SQ for BISI and 14 items of IQ for BISI were identified as possessing high reliability. This study makes two important contributions to the IS body of knowledge. First, it investigated the universal set of antecedents of SQ and IQ to establish the CVFs of IQ (integration flexibility SQ and reliability SQ) as well as the CVFs of IQ (representation IQ, intrinsic IQ, and accessibility IQ) for BISI success. Second, this study evaluated the crossover effects of system and information satisfaction in BISI success highlighting the importance that BI users place on the need to distinguish between the BI system, the IQ of the output produced, and the influence of IQ on perceived user system satisfaction from BISI. This study benefits stakeholders by focusing on what is important to BISI success and identifies those areas that are most likely to lead to better use of scarce resources while providing the greatest benefits.

Thesis (MComm (Statistics and Actuarial Science))--University of Stellenbosch, 2005. / Extremes are unusual or rare events. However, when such events – for example earthquakes, tidal waves and market crashes - do take place, they typically cause enormous losses, both in terms of human lives and monetary value. For this reason, it is of critical importance to accurately model extremal events. Extreme value theory entails the development of statistical models and techniques in order to describe and model such rare observations. In this document we discuss aspects of extreme value theory. This theory consists of two approaches: The classical maxima method, based on the properties of the maximum of a sample and the more popular threshold theory, based upon the properties of exceedances of a specified threshold value. This document provides the practitioner with the theoretical and practical tools for both these approaches. This will enable him/her to perform extreme value analyses with confidence. Extreme value theory – for both approaches - is based upon asymptotic arguments. For finite samples, the limiting result for the sample maximum holds approximately only. Similarly, for finite choices of the threshold, the limiting distribution for exceedances of that threshold holds only approximately. In this document we investigate the quality of extreme value based inferences with regard to the unknown underlying distribution when the sample size or threshold is finite. Estimation of extreme tail quantiles of the underlying distribution, as well as the calculation of confidence intervals, are typically the most important objectives of an extreme analysis. For that reason, we evaluate the accuracy of extreme based inferences in terms of these estimates. This investigation was carried out using a simulation study, performed with the software package S-Plus.

With extensive use of information systems in day-to-day business operations, many organizations are facing challenges to develop robust computer-based information systems that are secure and widely used by the user community. In order to develop information systems that are secure and useful, understanding what stakeholders consider important and value about the security and usability is critical. Security refers to confidentiality, integrity and availability and usability refers to efficiency, effectiveness and user satisfaction. Using Value Focused Thinking approach, this research first proposes the usability objectives based on the values of system developers and users. Using the security objectives proposed by Dhillon & Torkzadeh (2006) and the usability objectives, this research proposes hierarchies with the overall/over-arching goals of security (confidentiality, integrity, availability) and/or usability (efficiency, effectiveness and satisfaction). This research also analyzes a case of computer hacking and identifies which of the security and usability objectives that have not been met in that case study. The research contributions which include the usability objectives and security and usability hierarchies can be useful for theoretical as well as practical purposes.

Nuclear energy is a source of carbon free power. With many countries striving to make deep carbon cuts in their energy sectors, nuclear energy could be a large part of the solution. One of the main obstacles standing in the way of the use of nuclear energy is the issue of used nuclear fuel disposal. According to the NEI, the U.S. creates about 2000 metric tons of used nuclear fuel per year and has generated around 76,000 metric tons of used nuclear fuel over the last 4 decades. While there are technical problems that need to be solved, it is primarily the public and political opposition to the disposal of used nuclear fuel that stands in the way of progress in this area. This work addresses this issue through Multi-Criteria Decision Analysis (MCDA). To make a decision among ten different fuel cycles, we have brought together five stakeholders: Nuclear Scientists and Engineers, Environmental Scientists, Economists, Political Scientists, and The General Public. Using Multi-Attribute Value Theory (MAVT), we have been able to develop decision models for each stakeholder as well as a model that combines them all and came to the conclusion that of the ten fuel cycles considered, the best decision is to continue to use On Site Dry Cask Storage. This decision is made with small sample sizes but the methodology could be applied at much larger scales and can potentially be used to choose a fuel cycle that encounters much less political and social opposition to its implementation.

The central issue of this thesis is investigating the eventuality of systemic break- downs in the international financial system through examining systemic depen- dence between bank and insurance sectors. Standard models of systemic risk often use correlation of stock returns to evaluate the magnitude of intercon- nectedness between financial institutions. One of the main drawbacks of this approach is that it is oriented towards observations occurring along the central part of the distribution and it does not capture the dependence structure of outlying observations. To account for that, we use methodology which builds on the Extreme Value Theory and is solely focused on capturing dependence in extremes. The analysis is performed using the data on stock prices of the EU largest banks and insurance companies. We study dependencies in the pre- crisis and post-crisis period. The objective is to discover which sector poses a higher systemic threat to the international financial stability. Also, we try to find empirical evidence about an increase in interconnections in recent post- crisis years. We find that in both examined periods systemic dependence in the banking sector is higher than in the insurance sector. Our results also in- dicate that extremal interconnections in the respective sectors increased,...

[pt] A partir da década de 90, a metodologia de Valor em Risco (VaR) se difundiu pelo mundo, tanto em instituições financeiras quanto em não financeiras, como uma boa prática de mensuração de riscos. Um dos fatos estilizados mais pronunciados acerca das distribuições de retornos financeiros diz respeito à presença de caudas pesadas. Isso torna os modelos paramétricos tradicionais de cálculo de Valor em Risco (VaR) inadequados para a estimação de VaR de baixas probabilidades, dado que estes se baseiam na hipótese de normalidade para as distribuições dos retornos. Sendo assim, o objetivo do presente trabalho é investigar o desempenho de modelos baseados na Teoria dos Valores Extremos para o cálculo do VaR. Os resultados indicam que os modelos baseados na Teoria dos Valores Extremos são adequados para a modelagem das caudas, e consequentemente para a estimação de Valor em Risco quando os níveis de probabilidade de interesse são baixos. / [en] Since the 90 decade, the use of Value at Risk (VaR) methodology has been disseminated among both financial and non-financial institutions around the world, as a good practice in terms of risks management. The existence of fat tails is one of the striking stylized facts of financial returns distributions. This fact makes the use of traditional parametric models for Value at Risk (VaR) estimation unsuitable for the estimation of low probability events. This is because traditional models are based on the conditional normality assumption for financial returns distributions. The main purpose of this dissertation is to investigate the performance of VaR models based on Extreme Value Theory. The results indicates that Extreme Value Theory based models are suitable for low probability VaR estimation.