A comparative study of Michigan's peace officers' basic training and their actual job experiences

Thomas, Joseph Edward, Jr Eastern Michigan University 2002 해외박사(DDOD)

The State of Michigan mandates the basic police academy curriculum for its peace officers. This responsibility was assigned to the Michigan Law Enforcement Officers Training Council (MLEOTC), which later became Michigan Commission on Law Enforcement Standards (MCOLES). Michigan, like most other states, was faced with an increased diversity in its customer base. These new customers demanded that their local law enforcement departments be more effective and efficient though public outcry and mandates, such as passing Michigan's “Proposal A” in 1994. The public began to demand that law enforcement solve social ills before they became law enforcement incidents. These demands determined what officers actually did on the job. In essence, the public separated law enforcement and policing. Law enforcement was viewed by the public as being reactive (traditional basic training), whereas policing was viewed as being proactive (what officers do on the job). The public chose policing over law enforcement. The focus of this research was to determine whether there are gaps or mismatches between Michigan's peace officers basic academy curriculum or training and what they do on the job. This study was designed to examine the approaches to law enforcement training and to determine how the training is reflected in what peace officers actually do in their work. The findings of this study were supported by descriptive research methods and use of the phenomenological approach. The analysis of the purposive sample of law enforcement policing activities revealed that there was a gap between what peace officers are trained to do in the state's basic police academy and what they actually do on the job. The study further revealed that the assumption by administrators or control groups that are responsible for the basic training of peace officers could have led to “turf differences” of group members. To avoid these pitfalls, this study encouraged continuing cultural analysis of persons or groups with training responsibilities. This study also suggested that using a professional model of law enforcement was better than adherence to traditional or vocational standards associated with Michigan's past basic peace officers training.

High school seniors' perceptions of career and technical education and factors influencing their decision to attend an area career technical center

Gaunt, David P Western Michigan University 2005 해외박사(DDOD)

This study explored the profile of CTE students with regard to their academic standing and their socioeconomic background, examined high school seniors' perceptions of career and technical education, and identified the people and other factors that influence students in their decision-making about CTE enrollment. A 29-question survey was administered to 451 seniors from seven public high schools served by the Wexford-Missaukee Area Career Technical Center, operated by an intermediate school district in northern lower Michigan. Significant findings indicate that the typical profile of CTE students with respect to socioeconomic status and academic standing would identify a CTE student as performing somewhat lower academically, living less often with both parents while more commonly residing without either parent present, and being more economically disadvantaged than their non-CTE counterparts. While more CTE students than non-CTE students perceive the Career Technical Center as an avenue to college, both groups identify strongly with the CTE connection to the workplace. Even more significantly, both groups strongly perceive that the Career Technical Center addresses the needs of students from all ability levels. The most influential people upon a student regarding a decision to attend, or not to attend, a CTE program, are friends and parents. CTE staff and high school counselors also play a fairly significant role in influencing CTE students to attend. Spending half of the day away from the high school is the most significant factor in influencing CTE students to attend. The opportunity for students to see the area center firsthand, and the opportunity to receive college credit, were also significant influencing factors.

Traffic Crash Prediction Utilizing Geospatial Analysis, Machine Learning, and Connected Vehicles’ Basic Safety Messages

Elrayah, Yassir E Eastern Michigan University ProQuest Dissertations 2020 해외박사(DDOD)

Traffic crash prediction using different techniques and methodologies is essential for road safety. While many researchers have evaluated road safety using historical crash data, there are a few traffic crash prediction studies that predict the likelihood of crashes using emerging technology such as connected vehicles. This technology enables a connected vehicle to broadcast driving behaviors, in the form of basic safety messages, at a frequency of 10 Hz to a nearby connected vehicle. Additionally, different geospatial analysis techniques and prediction methodologies, such as machine learning, can support the analysis, visualization, and prediction of the traffic crash frequency. The primary objective of this study was to predict the likelihood of crash incidents using connected vehicles’ real-time driving behavior rather than historical crash data by developing and comparing different statistical and supervised machine learning predictive models. In addition, this study explored spatial and spatiotemporal patterns of crash incidents using geospatial analysis and unsupervised machine learning methodology. Moreover, it explored micro-level factors, such as road characteristics, and macro-level factors, such as population or points of interest density, which may impact traffic crash frequency. This study was based on a 3,000 connected-vehicle dataset, which was collected from the Safety Pilot Model Deployment Program in Ann Arbor, Michigan. The spatial analysis results using kernel density estimation showed that the city center and major road intersections were the most statistically significant high-risk locations. Additionally, the spatiotemporal analysis using emerging hotspot analysis showed that most of the city center roads had persistent hotspots, with some intensifying hotspots near road intersections and highway interchanges. Further, parametric and non-parametric correlation analysis and hierarchical regression models showed that some micro-level driving behavior variables and macro-level variables such as population, in relation to crash count, were statistically significant. Moreover, the results showed that the multinomial generalized mixed model with 91% prediction accuracy performed better than other statistical models. Finally, classification prediction, using supervised machine learning techniques, showed that both classification and regression tree and support vector machine algorithms, with multiple crash outcomes, performed well, with a high (94%) classification accuracy.

The practice of continuous improvement in higher education

Thalner, Deborah M Western Michigan University 2005 해외박사(DDOD)

Studies on the use of Total Quality Management (TQM) within higher education have primarily focused on the implementation of TQM as an institutional initiative. While TQM has been successful in business and industry and has seen some limited success in higher education, the most recent studies on its use in higher education indicate that it has not been successful institution-wide, and in many cases has been abandoned after two to three years. The problem, therefore, is one of a perceived need for continuous improvement in coupled with mixed results from previous attempts at implementation. This research study focused on higher education's use of continuous improvement methods; however, the focus was on specific departmental initiatives, rather than on institution-wide implementation. This study surveyed directors in departments of Financial Services, Facilities Management, Auxiliary Services, and Corporate Training within all public higher education institutions in Michigan. Out of a population of 148 directors surveyed, 54% responded to the survey. Directors of these departments were sent an e-mail with a link to a web-based survey. In addition to determining the level of continuous quality improvement (CQI) use in these departments, the survey also identified common drivers, obstacles, support factors, and outcomes derived from CQI. Key findings included that most had attempted CQI methods at some point in time and continued to pursue CQI. They were able to achieve the outcomes of improved service, quicker response, improved efficiencies, and increased financial returns, while at the same time seeing improved communications within their department and with the institution. These improvements could be realized regardless of institution type, department type, or type of CQI method used, and in spite of the obstacles encountered. In summary, TQM purists would suggest that TQM/CQI is no longer in place within higher education institutions as there is limited evidence of institution-wide continuing implementation. This study revealed, however, that department-based implementation is still in effect, and these departments continue to use CQI methods beyond the time period that current literature suggests it takes for higher education institutions to abandon CQI.

Correlation between the MEAP test and the Performance Series computer-adaptive test in mathematics

Torossian, Hosep Central Michigan University 2005 해외박사(DDOD)

Declining quality of the American public school education has prompted legislators to impose standards-based accountability across the nation, a shift that brought with it high-stakes testing. Further entrenching the ideal of testing for accountability, the No Child Left Behind Act imposed strict assessment guidelines on states, requiring annual testing of all students in grades three through eight. Most states administer norm-referenced and criterion-referenced tests in the traditional paper-and-pencil format, which at times is plagued with inefficiencies. The most critical of these inefficiencies is the delay between the time of administration to receipt of test results, which hinders meaningful and timely interpretation. One feature of Internet-based, computerized adaptive tests is their ability to provide instant feedback. The purpose of this research was to investigate the degree of correlation between the Performance Series Test (PST), a computerized adaptive test marketed by the Scantron Corporation, and the Michigan Educational Assessment Program (MEAP) test in mathematics. This research also investigated whether the PST can predict students' MEAP math scores. This study is significant because it not only investigated an efficient assessment technology that can be used to gauge student progress, but that can also aid in predicting student achievement in a high-stakes assessment. The research model helps educators design individualized instruction months ahead of taking the MEAP. A non-experimental, exploratory correlational research design was used in this study. Data collection tools included results from the MEAP test taken by 259 fourth-grade and 282 eighth-grade students using paper and pencil, and a computer-adaptive test, the PST. Student achievement scaled scores from the 2003--2004 school year were used, with the researcher obtaining data from an urban school district in southeastern Michigan. Pearson product-moment correlations between MEAP and PST scores for Grade 4 and Grade 8 were .742 (p<0.001) and .808 (p<0.001) respectively, indicating strong relationships between the two tests. Multiple regression analyses indicated the PST was the prominent predictor of MEAP scores, followed by ethnicity. The other predictor variables, which included gender, ethnicity, socioeconomic status, special education, and English-language proficiency, were insignificant predictors of MEAP in the presence of PST scores and ethnicity. The predictive value of PST allows for timely remediation of students who are at risk of failing the MEAP.

Multiple Ssid Framework for RSS-Fingerprint Based Indoor Positioning Systems

Abed, Ahmed Western Michigan University ProQuest Dissertations 2019 해외박사(DDOD)

Location-Based Indoor positioning systems significance stems from the bloom of recent applications in various fields such as in tracking services for an elder or a patient within large living communities, mobile robot localization, and several other security applications. Currently, Global Positioning Systems (GPS) are the most widely used location-sensing technique. However, satellite-based GPS signals require line of sight (LOS) to work correctly, which is something cannot be achieved inside buildings. Fortunately, wireless LAN can be employed in indoor positioning systems (IPS), and since all large buildings such as malls, hospitals, airports, schools, and museums have hundreds of Wi-Fi access points, it can provide accurate IPS without any additional infrastructure. Of special significance, the Wi-Fi fingerprinting-based techniques that offer a much less complex when compared to other methods such as the angle of arrival (AOA) and time difference of arrival (TDOA). Wi-Fi fingerprinting-based techniques use the received signal strength (RSS) to build radio maps. However, RSS value is a function of the distance between the Mobile System (MS) and Access Point (AP), which varies due to the multipath propagation phenomenon and human body blockage. Furthermore, fingerprinting approaches have several disadvantages such as labor, computational cost, and diversity (in signals and environment). In this dissertation, a novel approach that uses Multiple Service Set Identifiers (MSSID) to tackle these challenges is presented. MSSID means each AP can be configured to transmit N signals instead of one signal, to serve different clients’ categories simultaneously. IPS MSSID-based framework using three different realizations is proposed, implemented, and verified inside the College of Engineering and Applied Sciences (CEAS) building at Western Michigan University.First, a MSSID Probabilistic Neural Network (PNN)-based multi-classifier is proposed with a spatial voting scheme as a tool to determine the location of the user. Spatial voting is designed specifically to tackle the negative impact of multi-path propagation. The performance of the proposed system compared to some of the conventional methods such as K-Nearest Neighbors (K-NN) and multi-class support vector machine (SVM). Experimental results show that spatial voting of three PNN classifiers can significantly mitigate the adverse effects of RSS variation. The precision of the proposed system for PNN and K-NN at distance error of 2m is 90% and 85%, respectively. As a comparison to the proposed systems, the precision of the traditional techniques for PNN and K-NN is 82% and 78%, respectively. In addition, the experimental results show that the average distance error for PNN-based proposed system is less than 0.73 m when the length of AP (L) is 18. Furthermore, the distance error of proposed system shows high stability where it has lowest standard deviation as compared with other traditional techniques.Second, an MSSID-based adaptive K-nearest neighbor (K-NN) is proposed to tackle the challenges associated with static K-NN based-systems. The K-nearest neighbors (KNN) is selected for its significant performance with ease of realization. However, the static nature of K-NN, that is, in using a constant number of the nearest neighbors, leads to a serious shortcoming in its accuracy. In addition, the nature of the RSS-IPS challenges such as fading due to the multipath of electromagnetic waves inside buildings would mislead the solution of nearest neighbors. These reasons often result in lower perform than expected because of the increase in the distant neighbors’ biasing error. In this part, we address these challenges by proposing a new method based on multiple services set identifiers (MSSID) to select adaptively the appropriate nearest neighbors, and reject undesired ones. The ensemble technique is utilized to enhance the performance by combining the outputs of three adaptive K-NN estimators. The experimental results demonstrate the superiority of the adaptive K-NN based-proposed system over static KNN. The results show that the precision of the proposed system for the adaptive K-NN at distance error of 2m is 73%, and the average distance error is less than 1.3 m. As a comparison to the proposed systems, the precision of the traditional K-NN at distance error of 2m is 61%, and the average distance error is 1.85 m.Third, an MSSID- based particle swarm optimization (PSO) system is proposed. PSO technique is designed to select the most informative APs at each clustered area and combined with the K-means clustering method to confine location of the user into a smaller area and thus enhance positioning accuracy. WLAN-fingerprint based methods require recording RSS data of the surrounding APs, which results in including much more than the needed number of APs. Therefore, eliminating redundant or non-informative APs not only reduces the computational cost but also improves performance accuracy. At each cluster, PSO is applied to select the best joint combination of APs decided by the minimum mean of distance error. The results show that the proposed system outperforms other commonly proposed selection methods such as random, strongest APs, and Fisher criterion. Moreover, with reduction of 68% AP vector’s length (L=11), the results report that the proposed system achieves a positioning accuracy of 0.85 m over 3000 m2, with an accumulative density function (CDF) of 88% with a distance error of 2 m.The use of the multiple SSID technique supports IPS classifiers and produces higher precision than with single SSID. The proposed algorithms show a notable improvement over its counterpart with single SSID along with the distance error and reduction of RSS-vector’s length.

Eastern michigan university : System against individual:journeys through an alienated world as evidenced in expressionist drama by friedrich in toller's transfiguration(1991),and mr.zero in rice's the adding machine(1923)

Kim Hae Ryong Eastern Michigan University 1988 국내석사

An investigation of the relationship between administrator personality and teacher job satisfaction from a sample of Michigan K--12 public schools

Francisco, Mark A Central Michigan University 2005 해외박사(DDOD)

The purpose of this study was to determine if there was a relationship between the personality of public school administrators and the job satisfaction of teachers. Within the parameters established through theories and practices in leadership and personality over the last century, a third construct was proposed parallel to leader and follower personality studies (Gilbert, 1999; Kahler, 1996), and how perceived administrative listening skills affected teacher job satisfaction (Tackett, 2000). The Kahler (1982) model of personality provided the framework for understanding administrator personality according to specific traits pertinent to the six personality styles of Feeler, Thinker, Believer, Reflecter, Funster, and Doer. A study of principal personality and school climate among Michigan Lutheran schools (Weisenbach, 2004) provided additional grounding for the collected data. This study focused on 33 (of 82 invited) administrators and their staff (totaling 294 teachers of 495 invited) from various Michigan K--12 school districts. Administrators with direct supervisory responsibility of teachers were surveyed using the Kahler Personality Pattern Inventory (PPIRTM) (Kahler, 1996). Respondents included principals, assistant principals, and department heads. Teaching staff were surveyed using the abridged Job Description Index (Smith, 1997), according to the six facets of work on present job, people at work, supervision, promotion, pay, and the job in general. Teacher survey data was tallied from individuals and averaged for each school building, then correlated with the site administrators' personality data. Individual facets of administrator personality and teacher job satisfaction were also analyzed for significance in relationship. The results provided the information necessary to identify a personality factor among administrators that affected the job satisfaction of teachers known as a Phase change. Kahler (1996) described a Phase change as a shift in one's personality with a change in one's accompanying motivators, preferences, and stressors as a result of long term and intense distress followed by the satisfactory resolution of that distress. Phase change was evident in half of the administrators surveyed. Even with a small sample population of administrators and teachers, the conclusions drawn from the study indicated that an aspect of personality defined as a Phase change among administrators had a positive effect upon average teacher job satisfaction.

An evaluation of the Renaissance Zone programs of Michigan

Zhu, Yuanlei Western Michigan University 2005 해외박사(DDOD)

This dissertation analyzes whether the Renaissance Zone (RZ) programs in the state of Michigan are effective in helping distressed urban areas. The unique ES202 data permits us to use both establishment level data and aggregated zip level data to examine the impact of RZ programs on the establishment number and the firms' employment, real wage, and life duration. Based upon the presumption that different firms are sensitive to the tax incentives in different ways, this study examines the impact on all firms, on new firms, dead firms, and existing firms, on manufacturing and service firms, and on large and small firms. Selection biases on observed and unobserved variables usually arise from compiling data to conduct program evaluation when comparing the business outcomes of zone areas due to RZ programs to those of non-zone areas or comparison areas without RZ programs. To correct for the observed selection bias and to also test if the findings are robust and consistent with different specification of the control groups, this study chooses two comparison groups, the 2 nd round RZ and the propensity score picked group. To remove the possible unobserved selection bias, I apply three model specifications to the estimation of employment and real wage effects on unbalanced panel data: (1) fixed effect model, (2) random growth rate model, and (3) lagged dependent variable model, and Difference-in-Difference tests to the estimation of duration effect. I find that RZ programs cause fewer firms to start up, and fewer firms to close down in zone areas than those firms in non-zone areas at the same time. I also find that the Renaissance Zone programs raise employment by around 9% for service firms and around 3.8% for small firms. For manufacturing firms and large firms, the employment effect of RZ programs is not significant. Contrary to its mostly positive employment effect, the RZ program appears to cause the real wage to drop by 10.8% for manufacturing firms, by 11.7% for service firms, and 6.5% for small firms. The real wage effect is not significant for all firms taken together and for large firms. It is also found that employment and real wage effects change over time for manufacturing, service, large and small firms. Finally, based upon Cox proportional hazard function estimations and Difference-in-Difference tests, it appears that RZ programs do not help firms to last longer.

Change in Attribution Perspective, Shame, and Academic Identity for Freshmen on Probation Enrolled in University Academic Recovery Courses: A Mixed Methods Study

Robinson, Christine L Western Michigan University ProQuest Dissertations 2019 해외박사(DDOD)

Student retention is critical to the success of the student, the college or university, and society in general. Consequently, institutions of higher education continue to focus efforts on student retention strategies and one such strategy utilizes academic recovery courses to support probationary freshmen. Previous research studies of these courses largely focus on academic outcomes without examining the “why” or “how” behind such outcomes. Some studies also discuss constructs including attribution perspective, shame, and academic identity. However, the relationship between these constructs has not been researched, particularly with regard to any change that may occur for probationary freshmen engaged with an academic recovery course. This sequential, mixed-methods study, framed by Shame Resilience Theory (Brown, 2006), Attribution Theory (Weiner, 2008), and Academic Identity (Marcia, 1963; Was & Isaacson, 2008), researches change in these constructs for probationary freshmen enrolled in an academic recovery course at one mid-sized research university in the Midwest, and explores how students made meaning of their academic recovery process. A pre- and post-course survey was utilized in the quantitative phase of the study. Results indicated a statistically significant difference between mean shame scores for male and female probationary freshmen indicating that females experienced more shame while on probation than males. Concerning academic identity, over 50% of probationary freshmen resided in a moratorium academic identity status, while those with an achieved identity status represented 27.7% of the students. Relationships were found between the constructs wherein academic identity was statistically correlated with shame and attribution perspective. As moratorium identity decreased, achieved identity increased; as moratorium identity increased, shame increased; and as moratorium identity increased, attribution perspective decreased. Concerning construct change and racial groups, White students experienced a significant change in shame from pre- to post-course such that their post-course shame score was four points lower than the pre-course shame score. With regard to academic standing, higher attribution perspective scores significantly correlated with retention compared to academic dismissal. Post-course interviews, utilized in the qualitative phase of the study, revealed several major themes. Probationary freshmen experienced difficulty transitioning from high school to college with regard to insufficient life management skills, underdeveloped academic identity, selfawareness and shame resilience, and hardships that occurred during the semester. Factors contributing to positive growth for the freshmen included the importance of having a champion, improved life management skills, a positive attribution perspective, improved self-awareness and shame resilience, and improved academic identity. This study is the first to examine change in constructs for probationary freshmen engaged in an academic recovery course, and for which a mixed-methods approach gave voice to the students regarding their experiences. Results reveal how colleges and universities can better support probationary freshmen through the employment of academic recovery courses. The study opens up further research ideas to continue addressing the challenge of retention for this at-risk population.