The JROTC program is one of service and commitment. Its mission is to build better citizens and give them a sense of pride in service to their fellow man. Today these core principles are still needed, but with the increase in the student dropout rate, the JROTC program can be one of many alternatives needed to help public education reach today's youth who are struggling to stay in school. The purpose of this mixed methods study was to examine the impact of the Air Force JROTC Leadership Program on the grade point average (GPA), attendance rate, disciplinary referrals, and dropout rate of JROTC students at an urban high school in southeastern Virginia. The study also addressed the perceptions of school administrators, Air Force JROTC instructors, teachers, JROTC students and their parents on students enrolled in the program during the 2005-2009 school years. Descriptive statistics were used to determine the means, standard deviations and frequency distributions for the groups in the study. Three independent sample t-tests and seven one-way Analysis of Variance (ANOVA's) were used to determine where there was a statistically significant difference for each group. The Tukey post hoc procedure was used to determine where the difference occurred in the variables. There were three major findings revealed in this study. The first finding indicated that students who participated in the JROTC program had lower grade point averages (M =2.47, SD = 1.17) than non-JROTC participants (M = 3.00, SD = 0.94). Second, administrators had higher levels of agreement (100%) than AFJROTC instructors, teachers, JROTC students and parents that leadership skills were developed in the AFJROTC program. Third, JROTC students (12%) and parents (7%) had lower levels of agreement than administrators, AFJROTC instructors and teachers that the AFJROTC program is used as a recruitment tool. Focus groups results showed strong support for the program from administrators, teachers, JROTC students and parents. These findings suggest that if school districts and educational leaders are to benefit from implementing the AFJROTC program they must understand that the program is not designed to impact academics. The program is designed to develop leadership skills along with helping students become better citizens. Educational leaders in school districts should read the findings and consider utilizing the program as a possible alternative to help students to develop skills to keep them from dropping out of school. / Ph. D.

For several decades music educators have proposed that the study of music has a significant impact on student academic achievement, attendance rates, and student conduct. In an era of higher student and teacher accountability, increasing budget cuts, the federal No Child Left Behind Act (NCLB), and stringent state standards of learning, a number of educators have argued that education in music can boost test scores, attendance, attitudes toward school, reduce discipline referrals, and increase overall academic achievement. The purpose of this study was to quantify general education claims by examining high school academic achievement data, attendance rates, and student conduct of the 2006 graduating class in one Southeast Virginia school division. In addition, this study briefly explores the impact that music education has on the human brain and on academic achievement at the elementary school and secondary school levels. Moreover, influences that integrating music has on academic achievement in general education courses, arts integration programs, and elements of an effective music education program are explored. Specific research studies provide evidence to support key concepts and the need for additional research. The research design includes the independent variables: subject and number of years enrolled in formal music courses or no formal music courses, gender, ethnicity, and enrollment in formal music courses or no formal music courses in high school, grades nine through twelve. The dependent variables include: academic achievement as measured by grade twelve weighted cumulative grade point average (GPA), attendance rate as measured by the number of absences in grade twelve, and student conduct as measured by the number of discipline referrals in grade nine through grade twelve. Four research questions were used to explore academic achievement, attendance rate, and student conduct with regard to music or no music courses taken in grades nine through twelve. Ethnicity and gender were reported using the common dependent variables among participants in three populations " entire study population, music population, and non music population. Conclusions were based upon sophisticated statistical tests including descriptive and inferential statistics, correlations, analysis of variance (ANOVA), and regression statistics. These tests confirmed the four research questions and null hypotheses that music students out perform their non music counterparts in academic achievement, attendance rate, and student conduct. Although the studied school division does not distinguish between excused and unexcused absences, music students had fewer days absent than non music students. / Ph. D.

Reducing student dropout is of extreme importance to the United States. The loss in revenue as well as in human terms is huge. Several problems exist concerning students placed at-risk for dropping out. These include no agreed upon method of calculating drop out rates, differing opinions on the causes of school dropout, and a body of literature that is sparse concerning educational approaches for keeping students placed at-risk in school. This study examined the impact of the Samantha Academy of Creative Education (SACE) on the students placed at-risk and the teacher perceptions of the SACE program by the teachers working in the program at a suburban high school of Southwest Texas. The population of this mixed-methods study consisted of secondary general education students from a large suburban high school in Southwest Texas who had been placed at-risk. One of these groups consisted of students that participated in the SACE program while the other group consisted of a similar group of students not participating in SACE. Statistical tests were conducted to determine if a difference existed between the two groups with regard to graduation rate, attendance rate, and core grade average. Perceptions of the SACE program by the teachers that worked within the SACE program were gathered. Results indicate that student placed at-risk who participated in the SACE program had higher core grade averages, higher rates of graduation, and higher rates of attendance compared to students placed at-risk within the same high school who did not participate in SACE. Teachers perceived that the SACE program was efficacious for students placed at risk because of three broad themes. This study further demonstrated that effective programs aimed at helping students placed at-risk can be developed within the context of a regular high school setting. Recommendations for further research and implications for practice were provided.

In Deutschland nehmen die Fahrgastzahlen und die Verkehrsleistung im Schienenpersonennah- und -fernverkehr in den letzten Jahrzehnten stetig zu. So stieg beispielsweise die Zahl der beförderten Fahrgäste im Schienenpersonennahverkehr von 1,96 Milliarden im Jahr 2004 auf 2,72 Milliarden im Jahr 2018. Dies entspricht einer Zunahme von fast 39%. Allerdings wird es für die Eisenbahnverkehrsunternehmen aufgrund des Fachkräftemangels immer schwieriger, die erforderlichen Transportleistungen durch Triebfahrzeugführer und Zugbegleiter abzudecken. Dies bedeutet, dass mit weniger Ressourcen mehr Transportleistung erbracht werden muss, so dass eine ressourcenschonende und gleichzeitig kosteneffiziente Personalplanung unerlässlich ist. Ziel dieser Arbeit ist die Entwicklung eines Lösungskonzepts zur optimierten und automatisierten Planung des Bahnpersonals, insbesondere zur Sicherstellung der Zugbegleitquoten von Zugbegleitern in Regionalzügen. Da es bereits eine Vielzahl von Publikationen zu Modellierungsansätzen und Lösungsmethoden im Zusammenhang mit der Schichtplanung des Bahnpersonals gibt, wird in einem ersten Schritt die relevante Literatur identifiziert und klassifiziert. Dies ist notwendig, um geeignete mathematische Formulierungen und Lösungsansätze zu ermitteln, die auch für den Spezialfall der Schichtplanungsprobleme für Zugbegleiter mit Zugbegleitquoten angewendet oder weiter modifiziert werden können. Durch die Systematisierung der relevanten Artikel nach Modellformulierungen, Zielsetzungen, betrachteten Rahmenbedingungen und Lösungsmethoden können Forschungslücken leicht identifiziert und Möglichkeiten für weitere Forschungen aufgezeigt werden. Nach einer Analyse der gegebenen rechtlichen Anforderungen, Regelungen aus Tarifverträgen, operativen Bedingungen und der Forderungen aus Verkehrsverträgen ist ein erstes Ziel dieser Arbeit die Entwicklung eines mathematischen Modells, das das gegebene Schichtplanungsproblem für Zugbegleiter mit Zugbegleitquoten darstellt. Um zunächst die Auswirkungen der neuen Restriktionen für die Zugbegleitquoten zu analysieren, können weitere in der Praxis notwendige Anforderungen (z.B. Personalkapazität an den Einsatzstellen) weggelassen und der Planungshorizont auf einen Tag begrenzt werden. Nach der Modellierung des Problems mit weiteren Restriktionen soll in dieser Arbeit ein geeigneter Lösungsansatz entwickelt werden, der vor allem die Lösbarkeit großer realer Instanzen gewährleistet. Die generierten Schichtpläne müssen den gesetzlichen, vertraglichen und betrieblichen Anforderungen genügen und die dadurch entstehenden Kosten minimieren. Da in der Praxis ein Planungszeitraum von einem Tag weder betriebswirtschaftlich sinnvoll noch kosteneffizient ist, wird als nächstes Ziel die Ausdehnung des Planungszeitraums auf mehrere Tage angestrebt. Diese Ausdehnung sollte sich sowohl auf das Modell als auch auf den entwickelten Lösungsansatz auswirken. So können weitere mehrtägige Restriktionen integriert werden, wie z.B. die gleichmäßige Verteilung der von einem Zugbegleiter besetzten Fahrten. In der Forschung ist es wichtig, eine Vergleichbarkeit bzw. eine Bewertung der Qualität des Modells oder des Lösungsansatzes herzustellen. Aus diesem Grund sollte eine Arc-Flow-Formulierung des Schichtplanungsproblems für Zugbegleiter mit Zugbegleitquoten formuliert werden, um kleine Instanzen optimal zu lösen und untere Schranken für reale Instanzen zu setzen. Um die Lösung der Arc-Flow-Formulierung zu beschleunigen und zu verbessern, wird die Anwendung von gültigen Ungleichungen validiert. Der Zweck dieser Arbeit, der sich aus den oben genannten Zielen ableitet, lässt sich in fünf Forschungsfragen zur Schichtplanung für Zugbegleiter mit Zugbegleitquoten zusammenfassen: Q1 Wie ist der aktuelle Forschungsstand zu Schichtplanungsproblemen für das Bahnpersonal und welche Forschungslücken können identifiziert werden? F2 Wie können Schichtplanungsprobleme für Zugbegleiter mit Zugbegleitquoten modelliert werden? F3 Wie können Instanzen von Schichtplanungsprobleme für Zugbegleiter mit Zugbegleitquoten im Hinblick auf die Anforderungen der Praxis gelöst werden? F4 Wie kann das entwickelte mathematische Modell und der hybride Lösungsansatz auf einen mehrtägigen Zeitraum ausgedehnt werden? Was ist das Potenzial eines integrierten Ansatzes im Gegensatz zum sequenziellen, tageweisen Ansatz? F5 Kann eine Arc-Flow-Formulierung des Schichtplanungsproblems für Zugbegleiter mit Zugbegleitquoten verwendet werden, um die Lösungsqualität des bisherigen Ansatzes zu bewerten oder sogar zu verbessern? Können gültige Ungleichungen das Verhalten der Arc-Flow-Formulierung in Bezug auf Rechenzeiten und untere Schranken verbessern?:List of Figures IV List of Tables V List of Algorithms VII List of Abbreviations VIII List of Symbols X 1 Introduction 1 1.1 Motivation 1 1.2 Basics of railway crew scheduling 3 1.3 Purpose and research questions 5 1.4 Structure of this work 6 1.5 Research design 10 2 Large-scale optimization techniques 16 2.1 Column generation 16 2.2 Dantzig-Wolfe decomposition for linear programs 18 3 Railway crew scheduling: models, methods and applications 22 3.1 Introduction 23 3.2 Crew planning in railway operations 25 3.2.1 Crew management in strategic and tactical planning 25 3.2.2 Crew scheduling in operational planning 25 3.2.3 Real-time crew re-scheduling in disruption management 27 3.2.4 Technical terms of crew scheduling 28 3.2.5 Special characteristics of transportation modes 29 3.3 Overview of RCSP literature 32 3.3.1 Planning stage 32 3.3.2 Mode 33 3.3.3 Crew type 33 3.3.4 Model 34 3.3.5 Objective 34 3.3.6 Solution method 34 3.3.7 Country 35 3.4 Model formulations, objectives and constraints of RCSP 40 3.4.1 Model formulations 40 3.4.2 Objectives 44 3.4.3 Constraints 48 3.5 Solution methods 50 3.5.1 Integer programming methods 51 3.5.2 Heuristics 54 3.5.3 Column generation 56 3.5.4 Meta-heuristics 64 3.6 Conclusion and further research opportunities 67 3.7 Decision support tools and railway crew scheduling in practice 69 4 Schichtplanung von Zugbegleitpersonal unter Berücksichtigung von Prüfquoten 74 4.1 Einleitung 75 4.2 Planungsprozesse im Schienenpersonennahverkehr 76 4.3 Problembeschreibung 78 4.3.1 Klassifikation 79 4.3.2 Betriebliche und rechtliche Rahmenbedingungen 80 4.4 Modellierung als Set-Covering-Problem 81 4.5 Modellierung der Schichtplanung der Zugbegleiter mit Prüfquoten 83 4.6 Beispiel 84 4.7 Zusammenfassung und Ausblick 88 5 A hybrid solution approach for railway crew scheduling problems with attendance rates 89 5.1 Introduction 90 5.2 Crew scheduling problem with attendance rates 90 5.3 Hybrid solution approach 92 5.4 Computational results 94 5.5 Conclusions and further research 95 6 Solving practical railway crew scheduling problems with attendance rates 97 6.1 Introduction 98 6.2 Related work 100 6.3 The crew scheduling problem with attendance rates 102 6.3.1 Analytics-based design 102 6.3.2 Problem description and practical requirements 103 6.3.3 Problem formulation 104 6.4 Solution approaches for the MCSPAR 107 6.4.1 A multi-period column generation algorithm 107 6.4.2 Solving the pricing problem 109 6.5 Artifact evaluation 112 6.5.1 Considered transport networks and experimental design 112 6.5.2 Evaluation and comparison of algorithms 114 6.6 Conclusions and further research 116 7 Valid inequalities for the arc flow formulation of the railway crew scheduling problem with attendance rates 118 7.1 Introduction 119 7.2 Related work 121 7.3 Problem description and practical requirements 122 7.4 Arc flow formulation 124 7.5 Valid inequalities 130 7.5.1 Model specic valid inequalities 130 7.5.2 Symmetry breaking constraints 131 7.5.3 Parallel arcs 132 7.5.4 Fixed arcs 132 7.6 Computational results 133 7.6.1 Small-sized instances 134 7.6.2 Bounds for real-world instances 138 7.6.3 Improve heuristic solution 139 7.7 Conclusion 140 8 Conclusion 144 8.1 Summary 144 8.2 Future research 148 A Declarations of authorship 151 Bibliography 155 / In Germany, the number of passengers and the transport performance in regional and long-distance rail passenger transport increase constantly over the last decades. For example, the number of passengers carried in regional rail passenger transport rose from 1.96 billion in 2004 to 2.72 billion in 2018. This represents an increase of almost 39%. However, it is becoming increasingly difficult for railway companies to cover the required transport services by drivers and conductors due to the shortage of skilled workers. This implies that a greater transport performance must be achieved with fewer resources, thus resource-saving and at the same time cost-efficient planning of personnel is essential. This work aims to develop a solution concept for optimized and automated railway crew scheduling, especially ensuring attendance rates for conductors in regional trains. Since there already exists a variety of publications concerning modeling approaches and solution methods related to railway crew scheduling, the first step is to identify and classify relevant literature. This is necessary to determine suitable mathematical formulations and solution approaches which can also be used or further modified for the special case of railway crew scheduling problems with attendance rates for conductors. By systematizing the reviewed articles according to model formulations, objectives, constraints and solution methods, research gaps can easily be identified and opportunities for further research can be revealed. After an analysis of the given legal requirements, regulations from labor contracts, operating conditions and claims under transportation contracts, a first goal of this work is the development of a mathematical model which represents the given problem with attendance rates for conductors. In order to first analyze the effect of the new constraints on attendance rates, further requirements necessary in practice can be omitted (e.g. personnel capacity at crew bases) and the planning horizon can be limited to one day. After modeling the problem with further requirements, this work aims to develop a suitable solution approach which, above all, guarantees the solvability of large real-world instances. The generated shift schedules have to meet legal, contractual and operational requirements and thereby minimize the resulting costs. Since in practice a planning period of one day is neither operationally reasonable nor cost-efficient, the next goal is to extend the planning period to several days. This extension should affect both the model and the developed solution approach. This allows further restrictions concerning several days to be integrated, such as the uniform distribution of attended trips. In research, it is important to establish comparability or an assessment of the quality of the model or solution method. For this reason, an arc-flow formulation of the crew scheduling problem with attendance rates should be formulated to solve small-sized instances optimally and provide lower bounds for real-world instances. To accelerate and improve the arc-flow formulation solution, the application of valid inequalities will be validated. The purpose of this work derived from the above mentioned objectives can be summarized into five research questions on railway crew scheduling with and without attendance rates for conductors: Q1 What is the current state of research for railway crew scheduling problems and which research gaps can be identified? Q2 How can railway crew scheduling problems with attendance rates for conductors be modeled? Q3 How can instances of railway crew scheduling problems with attendance rates be solved with regard to real-world requirements? Q4 How can the developed mathematical model and hybrid solution approach be extended to a multiple day period? What is the potential of an integrated approach in contrast to the sequential day-by-day approach? Q5 Can an arc-flow formulation of the railway crew scheduling problem with attendance rates be used to evaluate or even enhance the solution quality of the previous approach? Can valid inequalities improve the performance of the arc-flow formulation concerning computing times and lower bounds?:List of Figures IV List of Tables V List of Algorithms VII List of Abbreviations VIII List of Symbols X 1 Introduction 1 1.1 Motivation 1 1.2 Basics of railway crew scheduling 3 1.3 Purpose and research questions 5 1.4 Structure of this work 6 1.5 Research design 10 2 Large-scale optimization techniques 16 2.1 Column generation 16 2.2 Dantzig-Wolfe decomposition for linear programs 18 3 Railway crew scheduling: models, methods and applications 22 3.1 Introduction 23 3.2 Crew planning in railway operations 25 3.2.1 Crew management in strategic and tactical planning 25 3.2.2 Crew scheduling in operational planning 25 3.2.3 Real-time crew re-scheduling in disruption management 27 3.2.4 Technical terms of crew scheduling 28 3.2.5 Special characteristics of transportation modes 29 3.3 Overview of RCSP literature 32 3.3.1 Planning stage 32 3.3.2 Mode 33 3.3.3 Crew type 33 3.3.4 Model 34 3.3.5 Objective 34 3.3.6 Solution method 34 3.3.7 Country 35 3.4 Model formulations, objectives and constraints of RCSP 40 3.4.1 Model formulations 40 3.4.2 Objectives 44 3.4.3 Constraints 48 3.5 Solution methods 50 3.5.1 Integer programming methods 51 3.5.2 Heuristics 54 3.5.3 Column generation 56 3.5.4 Meta-heuristics 64 3.6 Conclusion and further research opportunities 67 3.7 Decision support tools and railway crew scheduling in practice 69 4 Schichtplanung von Zugbegleitpersonal unter Berücksichtigung von Prüfquoten 74 4.1 Einleitung 75 4.2 Planungsprozesse im Schienenpersonennahverkehr 76 4.3 Problembeschreibung 78 4.3.1 Klassifikation 79 4.3.2 Betriebliche und rechtliche Rahmenbedingungen 80 4.4 Modellierung als Set-Covering-Problem 81 4.5 Modellierung der Schichtplanung der Zugbegleiter mit Prüfquoten 83 4.6 Beispiel 84 4.7 Zusammenfassung und Ausblick 88 5 A hybrid solution approach for railway crew scheduling problems with attendance rates 89 5.1 Introduction 90 5.2 Crew scheduling problem with attendance rates 90 5.3 Hybrid solution approach 92 5.4 Computational results 94 5.5 Conclusions and further research 95 6 Solving practical railway crew scheduling problems with attendance rates 97 6.1 Introduction 98 6.2 Related work 100 6.3 The crew scheduling problem with attendance rates 102 6.3.1 Analytics-based design 102 6.3.2 Problem description and practical requirements 103 6.3.3 Problem formulation 104 6.4 Solution approaches for the MCSPAR 107 6.4.1 A multi-period column generation algorithm 107 6.4.2 Solving the pricing problem 109 6.5 Artifact evaluation 112 6.5.1 Considered transport networks and experimental design 112 6.5.2 Evaluation and comparison of algorithms 114 6.6 Conclusions and further research 116 7 Valid inequalities for the arc flow formulation of the railway crew scheduling problem with attendance rates 118 7.1 Introduction 119 7.2 Related work 121 7.3 Problem description and practical requirements 122 7.4 Arc flow formulation 124 7.5 Valid inequalities 130 7.5.1 Model specic valid inequalities 130 7.5.2 Symmetry breaking constraints 131 7.5.3 Parallel arcs 132 7.5.4 Fixed arcs 132 7.6 Computational results 133 7.6.1 Small-sized instances 134 7.6.2 Bounds for real-world instances 138 7.6.3 Improve heuristic solution 139 7.7 Conclusion 140 8 Conclusion 144 8.1 Summary 144 8.2 Future research 148 A Declarations of authorship 151 Bibliography 155

The rise in the number of students who drop out of high school has gained national attention. High school dropout rates in the state of Louisiana are a primary concern to school administrators in the state. The Graduation Coach Program is an intervention implemented in several high schools across Louisiana to assist students with completing their high school education. Many of the programs' attributes are based on Maslow's hierarchy of needs, students' needs, and the presence of positive adult relationships that might improve student achievement. The purpose of this study was to compare archival attendance and graduation rates among independent groups from years before and after the implementation of the Graduation Coach Program in 4 Louisiana public high schools. Attendance rates included data from 5 years before and 7 years after the program (n = 48), and due to limitations in the archival records, graduation rates included data from 2 years before and 7 years after the program (n = 36). Two independent-samples t tests were conducted, and no significant differences were found between the groups for both measures. Due to power limitations in the group sizes, further research is recommended to include additional campuses that implement the program. Positive social change implications include providing these initial research findings to the study districts' administration to assist with decision making and planning for the Graduation Coach Program used at their campuses. Through continued efforts and research, high school administrators may ultimately improve high school attendance and graduation rates to address the high school dropout problem in Louisiana.

This study was designed to investigate the correlational relationship between four school elements listed on the Texas Academic Progress Report (TAPR) and the academic achievement of 8th grade African American male students. Data for this study was provided from the Texas Education Agency's (TEA) Office for Public Information Requests. The study included four independent variables: percent of socioeconomically disadvantaged students, average years of teachers' experience, attendance rate and average class size in mathematics. The dependent variable was the 8th grade African American males' performance on the mathematics STAAR exam. The study examined scores from the mathematics STAAR exam for the years 2012-2014. The sample population included 1,540 schools and 47,169 individual test results. The results of the correlational analysis indicate that none of the independent variables were correlated to each other, but each of the independent variables had a statistically significant correlation with the dependent variable at the p < .05 level. The study also sought to explore the variance in academic achievement that could be explained by the four independent variables when used as a model. The results of the simple multiple regression suggest that not only were the results statistically significant at the p < .01 level, but the model explained 32.4% of the variance in 8th grade African American males' performance on the STAAR mathematics exam in the years 2012-2014.