Thesis (doctoral)--Universität Leipzig, 1914. / Vita. Includes bibliographical references (p. [ix]-x).

AN ABSTRACT OF THE DISSERTATION OF Todd D. Sigler, for the Doctor of Philosophy degree in Education Administration Higher Education, presented on October 28, 2011, at Southern Illinois University Carbondale. TITLE: COLLECTIVE BEHAVIOR AND CAMPUS PUBLIC ORDER POLICING: A QUALITATIVE STUDY OF MIXED-ISSUE CAMPUS DISTURBANCES AT THREE MIDWEST PUBLIC UNIVERSITIES MAJOR PROFESSOR: Dr. Kathryn Ann Hytten The purpose of this qualitative study analyzed mixed-issue campus disturbance events at three similar public universities located in the Midwest region of the United States. Using a case study research design, the analysis draws from interviews conducted with campus police officers employed at the selected institutions assigned to work one or more disturbances during the last decade. A related purpose analyzed the element of space/location and territoriality where these disturbances occurred, including an assessment of the value and meaning of space to the police and how police use space to achieve public order maintenance objectives. As the primary social control agent, the police - through their interface with crowd participants - can influence positive or negative relationships that subsequently impact disturbance outcomes. The research methodology incorporated naturalistic qualitative methods including: (1) one-on-one interviews of 15 campus police officers - both front-line police officers and command officers divided among three campuses; (2) open source public documents such as task force reports and newspaper articles; and (3) closed-source documents, such as unpublished pre- and post-action reports completed by law enforcement or campus administration. Finally, I conducted field research observations of the disturbance locations combined with my own experience in campus law enforcement. Among some of the important findings are the importance of officer experience, consistent and recent training for officers in both traditional crowd control tactics, as well as crowd management skills, especially communication (accomplished through techniques such as dialogue policing and social media technology to recognize and mitigate triggering behaviors on both sides. Additional public order policing tactics include recognizing the importance of territoriality and the value of mitigating tactics such as crowd combing, and controlling space to reduce density. This study will support law enforcement officials in higher education with planning, developing and responding proactively to disturbances using public order policing strategies suitable for campus communities. Special emphasis is placed on the elaborated social identity model and the negotiated management model to explain police and crowd behaviors. Of value to crowd management practitioners is the critical need to interface crowd theory with practical public order policing techniques to develop an effective response.

Most educational studies highlight the gender gap in Science, Technology, Engineering, and Mathematics (STEM). Female students' interest and success in STEM are behind their male peers, especially in chemistry and physics classes. Females are less likely to pursue a STEM field in college. In addition, few women want to be scientists and engineers. The gender gap in STEM may be a result of traditional science teaching methods. Female students' expectations are not met, and as a result, their science interest decreases in these classrooms, as well as not pursuing STEM careers in specific chemistry, engineering, and physics. There is an increase in research and curriculum reform movements containing socioscientific issues (SSI) extending worldwide. SSI provides an opportunity to engage students in critical thinking. SSI-based science classrooms are based on real-world problems like climate change, genetic modification, and vaccination. Integrating SSI into science classrooms as a revolutionary method might renew the practices of our traditional science classrooms. However, few SSI-based educational research studies have focused on the gender gap issue. This dissertation investigated 216 middle and high school students' experiences in SSI-based classrooms with a mixed-methods approach. I investigated Model-Evidence Link diagram's effectiveness on the shiftiest in students' plausibility toward scientific model and scientific knowledge gaining in the quantitative part. I examined their experiences in SSI-based classrooms with the open-ended question survey in the qualitative part. SSI-based science activities provided gender equity conditions in science classrooms. Both genders evaluated the scientific model as more plausible by eliminating the alternative model as less plausible, and they gained scientific knowledge about Climate Change and Wetlands. The MEL diagram seemed more effective for the students' positive plausibility shifts toward the scientifically accepted model. Also, both genders had positive experiences in SSI-based classrooms in general. However, female students did not want to continue a STEM career except biomedical sciences. MEL design can be renewed by adding some initial and interval short activities and using some SSI topic-related posters and objects to prepare students for critical thinking and keep them more engaged during the activities. Also, adding student interviews and live recording the student discussions might give an understanding of the collaboration and student experiences in the SSI-based classrooms. / Math & Science Education

The present study aimed to examine how a manipulated majority position affects attitude change for intergroup and non-intergroup issues. Specifically I wanted to see how norms of tolerance and norms of prejudice differed. The study employed a 3 (majority manipulated position: positive, neutral, or negative) X 2 (issue type: intergroup or non-intergroup) ANCOVA. Additionally, I wanted to examine how participants’ perceived societal direction affects attitude change for intergroup issues with a 3 (majority manipulated position: positive, neutral, or negative) X 3 (perceived direction of attitude: support, stay the same, negative) ANOVA. Participants were randomly assigned to view a majority manipulation position. Attitude change was determined by a difference between a pre-and post-manipulation score. In partial support of my hypothesis intergroup issues elicited more norm-consistent attitude change than non-intergroup topics, however this was driven by a prejudicial social norm effect. No effect was found for perceived societal direction.

It has been argued that marketing contributes to society by finding solutions to a diverse range of social issues. Importantly, research within the (social) marketing domain recognises that the concept of exchange is a fundamental aspect of influencing people to take on positive social issue behaviours (Andreasen, 1995; Rothschild, 1999). However, regardless of the influence of social marketing, ultimately the behavioural exchange resides with the individual. This infers that exchange can be considered from the individual’s (i.e., consumer’s) point of view, of intrapersonal or self-exchange (Gould, 1994). Furthermore, the conditions that facilitate or constrain this form of exchange are found within the individual – and relate to for example, individual differences. However, in recent years there has been limited interest in exchange theory within the marketing domain and, in particular, exchange as a fundamental consumer behaviour phenomenon (Anderson et al, 1999; Gould, 1994). This study seeks to extend current consumer behaviour and social marketing knowledge in the areas of exchange theory and personality. Based on an examination of the extant literature, a model of determinants and outcomes of Social Issue Exchange was developed and empirically tested. The Social Issue Exchange Model proposed in this study accounts for a number of associations which includes a representation of personality termed pro-social orientation along with social issue involvement, attitude toward social issues, subjective assessment of negative consequences and feelings. The determinants of social issue exchange included the multi-component variable pro-social orientation comprising the traits risk aversion, locus of control, consideration of future consequences, susceptibility to normative influence and social responsibility along with the variables social issue involvement and attitude towards social issues. The outcomes of social issue exchange include the variables of subjective assessment of negative consequences and feelings. The study adopted a quantitative methodology using an Internet administered questionnaire that allowed for the measurement of the determinants and outcomes of social issue exchange. The construction of the questionnaire followed a sequential process which involved developing new measures, utilising and adapting existing measures and then pre-testing these measures to ensure the development of a psychometrically sound and respondent-friendly survey instrument. The final survey used Excess Alcohol Consumption and Speeding social issues as stimuli for the study. Data collection resulted in 1146 (comprising 559 for Speeding social issue, and 587 for Excess Alcohol Consumption social issue) useable surveys for subsequent analysis. Analysis included a number of statistical procedures including correlation analysis, exploratory factor analysis, reliability analysis and tests of the model via Partial Least Squares (PLS) analysis. Overall, the findings provided support for the proposed Social Issue Exchange Model. In terms of the measurement model, the findings show that pro-social orientation accounted for different amounts of variance in the five traits, with consideration for further consequences accounting for the most variance and susceptibility to normative influence accounting for the least. In terms of the inner model, all the hypothesised paths were supported with the exception of attitude towards social issues and social issue exchange. A comparison of the smaller models (i.e., Speeding and Excess Alcohol Consumption) with the overall model indicated that largely the relationships were consistent, with the exception of social issue involvement and attitude towards social issues which was not supported in the Excess Alcohol Consumption model. The findings provide a number of theoretical and practical implications for research. From a theoretical perspective, broadening the concept of exchange to account for self-exchange in the context of social issue behaviours contributes to the body of knowledge on exchange. Moreover, aggregating traits to form the multi-component construct pro-social orientation takes a holistic approach to personality and thereby, provides greater clarification of the psychological processes that drive individuals to respond positively or negatively to social issues and associated behaviours. From a practical perspective, this study may lead to a better understanding of how personal characteristics can shape an individual’s response to social issues as well as their behaviours. In summary, the importance of understanding the processes that influence individuals’ social issue behaviours provides a justification for this study. Accordingly, this study offers valuable insights into how ‘exchange’ is an integral feature of individual behaviour change, as well as positive social change for society.

The traditional issue selling process refers to strategic actions taken at a subsidiary in order to gain attention from the HQ. This study aims to broaden the theories on issue selling to also cover internal issue selling, which refers to the individual level of issue selling within a subsidiary. Further is attention and initiative taking worth investigating when studying issue selling, whereas these underlying constructs of issue selling are highlighted in the paper. For this specific study we have performed a case study with L’Oréal Sweden to investigate how the individuals are selling issues within the subsidiary. This micro-level focus of the issue selling process have the potential to contribute to an understanding of the process and the underlying constructs of issue selling on a macro perspective. The findings of this study indicate a tendency that issue selling exists on a subsidiary level. Thereby it could be argued that ideas and initiatives raised by the individuals within a subsidiary have the potential to generate in strategic and organizational improvements on a macro perspective for the MNC.

Issue tracking is one of the vital parts in maintaining computer  systems.  It is utilized in anything from small independent companies to large enterprises. The tracking does not just provide developers and other personnel with crucial information regarding their systems current state, but additionally stores useful documentation if any error reoccurs in the future. However, if the tracking issue would be deficient in some way, the complete process of developing or maintaining a system could affected negatively in great extent. This thesis work has looked into a scenario where the tool has been to slow, overly complicated and obsolete. It has made a large negative impact on the work force that uses the tool and made tracking issue to a discouragement. The thesis work has thence investigated features of the existing tool, suggested a better solution to use based upon these findings, followed by the development of a web application. When the application was finished, its usability was tested by the intended staff and performance tests were conducted. The test results showed that the application had been implemented successfully in many aspects. Unfortunately, due to deficient technical choices, the project did struggle with implementing all features as expected. The thesis work did consequently learn the hard way the importance of a choosing development techniques very thoroughly.

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This thesis presents an in-depth investigation on the subject of how natural language processing and machine learning techniques can be utilized in order to perform a comprehensive analysis of programming issues found in different open source project repositories hosted on GitHub. The research is focused on examining issues gathered from a number of JavaScript repositories based on their user generated textual description. The primary goal of the study is to explore how natural language processing and machine learning methods can facilitate the process of identifying and categorizing distinct issue types. Furthermore, the research goes one step further and investigates how these same techniques can support users in searching for potential solutions to these issues. For this purpose, an initial proof-of-concept implementation is developed, which collects over 30 000 JavaScript issues from over 100 GitHub repositories. Then, the system extracts the titles of the issues, cleans and processes the data, before supplying it to an unsupervised clustering model which tries to uncover any discernible similarities and patterns within the examined dataset. What is more, the main system is supplemented by a dedicated web application prototype, which enables users to utilize the underlying machine learning model in order to find solutions to their programming related issues. Furthermore, the developed implementation is meticulously evaluated through a number of measures. First of all, the trained clustering model is assessed by two independent groups of external reviewers - one group of fellow researchers and another group of practitioners in the software industry, so as to determine whether the resulting categories contain distinct types of issues. Moreover, in order to find out if the system can facilitate the search for issue solutions, the web application prototype is tested in a series of user sessions with participants who are not only representative of the main target group which can benefit most from such a system, but who also have a mixture of both practical and theoretical backgrounds. The results of this research demonstrate that the proposed solution can effectively categorize issues according to their type, solely based on the user generated free-text title. This provides strong evidence that natural language processing and machine learning techniques can be utilized for analyzing issues and automating the overall learning process. However, the study was unable to conclusively determine whether these same methods can aid the search for issue solutions. Nevertheless, the thesis provides a detailed account of how this problem was addressed and can therefore serve as the basis for future research.

In this study, I investigate how the issue of immigration affects Latino voter turnout. I hypothesize that U.S. Latino citizens who view immigration as highly important and helpful to the United States will be more likely to turn out to vote in midterm and presidential elections. In addition to a contextual analysis on elections in Arizona and California, I perform a probit regression analysis on survey data from Pew Hispanic's 2004 National Survey of Latinos on Politics and Civic Participation. The results are mixed with respect to the initial expectations. While respondents who view immigration as important and helpful are more likely to turn out than those who view immigration as important and hurtful, the results suggest that respondents who find immigration as unimportant may not be less likely to turn out. Further, there are some differences between Latino subgroups, although these differences are minor. Ultimately, the hypotheses presented in this study find moderate support.