Texas A&M University-Kingsville: AKM Digital Repository
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Comparison of two Texas accountability rating systems for effect on economically disadvantaged students
No full textEconomically disadvantaged students in public schools tend to perform low on state assessments including the State of Texas Assessments of Academic Readiness (STAAR) in Texas. From 2013 to 2017, the previous Met Standard/Improvement Required Accountability
Rating (MSIRAR) system dedicated one of the four indices to the economically disadvantaged student subpopulation. In 2018, the current A – F Accountability Rating (AFAR) system replaced the MSIRAR with a three-domain system whereby the economically disadvantage student subpopulation was one of 14 subgroups in Domain III. The purpose of this quantitative comparative study is to investigate if there are mean passing rate differences between the economically and non-economically disadvantaged student populations and within the former
MSIRAR system and the current AFAR system. Mills’s concept of the sociological imagination, a socio-psychological framework, served as the theoretical frame the study. Five research questions were investigated to determine differences in the mean passing rates (lower, the same, or increased) of scores on the five STAAR EOC assessments of economically and noneconomically
disadvantaged student populations within the former MSIRAR system and the current AFAR system. A two-way mixed between-within subjects ANOVA was the statistical
procedure employed. Findings indicated the change in accountability system decreased the STAAR EOC means performance levels of the economically disadvantaged student population. This study has implication for educational policy makers in the state of Texas and in other states for choice of accountability systems and the allocation of funding for economically disadvantaged students
Feasibility anaylsis of utilizing renewable energy in ranches and farms in Texas
No full textDue to the increasing demand for food, it is expected that the agriculture sector will have a greater role in the future. As a result, there will be higher energy demand to power all the agriculture related activities, such as harvesting crops or growing livestock. In Texas, the agriculture sector has a significant availability of lands that makes farms and ranches suitable for the possible energy generation through small scale wind turbines or solar panels. In this project, a technical feasibility analysis was
performed to determine the wind and solar energy potential for about 248,000 farms and ranches located
in Texas. Geospatial and temporal data analyses were performed in order to estimate the energy potential
and to understand the diverse trends surrounding them with data gathered from different databases. The
results obtained through the geospatial analysis were studied through an in-depth numerical examination for the farms and ranches being considered. Based on the results, the majority of farms in Texas have higher solar energy potential than wind energy potential, making the installation of solar panels to be more viable. Even though there is less wind energy potential, thousands of farms and ranches still have a considerable amount of wind potential that would be sufficient to power up different agricultural activities
Sensitivity of pavement management system decisions to the quality of pavement condition
No full textdeterrent factor for implementing Pavement Management Systems (PMS) by small and medium-size agencies is the cost of pavement condition data collection. Pavement condition data is an essential input for modeling pavement performance. The condition data triggers different
M&R efforts and defines the priority of interventions to improve pavement condition and determine budget requirements. The required budget to maintain a transportation system is dependent on the pavement distresses in the network. Limited budget for pavement management forces transportation agencies to reduce data collection frequency or use less expensive
approaches, such as rapid automated data collection. This study investigates the sensitivity of PMS decisions to the input condition data quality for the city of East Palo Alto in the San Francisco Bay area. The study pavement network has 251 sections which comprises 17 arterial road, 56 collectors and 178 residential/ local street sections. The PMS software package by the Metropolitan Transportation Commission (MTC) called StreetSaver was used to evaluate pavement distress effects on pavement performance. Seven pavement distresses including
alligator cracking, raveling, weathering, block cracking, longitudinal and transverse cracking, and distortions were used to evaluate the pavement performance. The main objective of this study is to define the impact of uncertainty on inspection data on the PMS required budget by changing the distress rate for alligator cracking. A global sensitivity analysis was performed with the parameter values changing as percentage of last inspected pavement distress value. Impacts of a combination of changes on PMS model outputs such as treatments and budget needs for 5 years were analyzed. It is concluded that accuracy in pavement distress data is important.
Inaccurate distress data leads to various treatment recommendation and increase in overall budget required. This study will help local agencies to improve pavement distress data collection and budget analysis
Complex Matter Space : a new perspective on mass, charge, and energy
No full textComplex Matter particles and Complex Matter Space are new fundamental views of matter, charge, and energy that we will present here, and the paradigm will be shifted from pure real or pure imaginary particles to Complex Matter Space. In Complex Matter Space, we assume that
the total mass of a particle is a complex quantity:M = m + iq , where m is the inertial mass in AMU and q is the charge in coulombs. Complex Matter Space explains antimatter, tachyons, and dark matter. Later research will incorporate the weak and strong nuclear forces and whether they should be real, imaginary, or complex. Also, while Relativistic Mechanics cannot recognize
velocities faster than the speed of light, c, we will investigate tachyonic Complex Matter particles as well. In theory, a charged particle of zero real mass would have imaginary mass and would behave differently than a massive particle, being able to travel faster than the speed of light. So far, all truly mass-less particles found (photons and gluons) have no net charge. A photon is theorized to be a wave packet of electromagnetic energy, but the electric and magnetic components cancel out, leaving no net charge. Gluons are more mysterious, as scientists do not currently have enough information about the strong force to know what a gluon might be made out of (See Quantum Chromodynamics and the Strong Force under Quantum Mechanics). We will research Complex Matter Space using Complex Analysis, Hilbert Space Methods,
Minkowski Geometry, and Computer Algebra Systems such as Maple
Teacher perceptions of the evaluation system including walkthroughs and administrator feedback in rural South Texas school districts.
No full textThe purpose of this qualitative study was to examine teacher perceptions of the evaluation process including informal walkthroughs and administrator feedback in South Texas rural schools to determine whether teachers felt that there was a connection to teacher effectiveness and student achievement. The findings of this study may assist administrators in determining how teachers perceive the evaluation process.
This study may further allow teachers to understand the reasoning behind the process. Students may also benefit from this process as it may help produce more effective teachers who provide effective, targeted instruction. I gathered data from interviews conducted in the natural setting of the participants. Nine teachers from three different rural South Texas school districts were interviewed. I used open-ended questions and recorded the interviews to gather the evidence. Once interviews were transcribed, I was able to analyze the data and came up with 24 codes which yielded eight themes.
Key findings in this study indicated that teachers need more thorough training on the evaluation process, teachers expressed that the evaluation process is not tied to student achievement, evaluations do affect teacher growth, feedback given to teachers should be more specific, evaluations and walkthroughs do cause stress to teachers, administrators shouldincorporate multiple sources of data to fully evaluate teachers, frequent walkthroughs and evaluations are necessary and wanted by teachers, and administrators should provide teachers with additional resources. This study provided invaluable information that will benefit school systems by refining their processes to meet the teachers’ needs. Administrators should be able to provide teachers with valuable feedback and resources to help improve their teaching. Future studies could be performed to see if the implications mentioned and implemented made a difference on teacher growth and student achievement. The study should also be replicated in other parts of the state and in urban school districts to see if the findings are similar and/or are unique to rural South Texas school districts.
This study was relevant to determine whether gaps exist in the evaluation process. Both teachers and administrators may benefit from this study as it provides data on the thoughts, feelings, and recommendations regarding the evaluation process, walkthroughs, and administrator feedback. If warranted, administrators may be able to adjust or improve the system to improve teacher growth and student achievement
College, career, and military readiness : a qualitative study of select programs in Texas
No full textStates recognize that a workforce skill shortage exists and have started educational initiatives to prepare students for workforce readiness and postsecondary success. There is a growing consensus among states that the goal of our education system is to prepare students for a career, college, or the military by providing all students with experience that they will use to build the knowledge and skills necessary for entry into and success. According to Kreamer et al. (2014), more than half of the states in the U.S. use career-focused readiness indicators. One of those indicators is a way to prepare students for future success through a high school college and career readiness program that offers Industry Recognized Credentials (IRC), providing for stackable credentials that enable several opportunities (Stone, 2017). To fully prepare students to meet these skills demands, Texas Governor Abbott instituted House Bill 3 (HB3) of the 86th Legislature. HB3 supports the State of Texas’ mission to prepare every student for success in college, career, or the military. The Texas Education Agency (TEA) has supported this bill by including College, Career, and Military Readiness (CCMR) in the yearly school Texas A-F Accountability system. CCMR earnings and State Assessment of Academic Readiness (STAAR) assessments account for 40 percent of a school’s yearly report card. CCMR is an effort to prepare students with skills that are critical. CCMR administrators of rural schools include Superintendent, Principal, or CTE administrator.
This basic qualitative study sought to understand administrators’ perceptions regarding college, career, and military programs in high school and to determine the characteristics that comprise a successful college, career, and military readiness program. Ten Texas top ranking school CCMR administrators were interviewed. Administrators’ interviews were transcribed and sent to administrator for approval and correction. Themes and sub themes that emerged include dual credit classes, college preparation, certifications, programs of study, college, TSI, CCMR, accountability higher education, industry partners, employability skills, explore, track students, scheduling, early start, individual plan, personnel, and finance. The research findings of the study revealed best practices and processes that the district used to earn CCMR status that resulted in the district as a top-ranking Texas CCMR rural school
Perceptions of teacher leaders in a rural South Texas school that averted school closure
No full text“I know you’ve heard the rumor about the school closing down. That is not a rumor. That’s a fact.” Years of unacceptable academic ratings, dysfunctional school leadership, and constant budget deficits had finally caught up to a rural school in South Texas. Unfortunately, this is not the only school that has heard these words. Many schools across Texas face multiple challenges leaving the district facing closure. School closures tend to impact communities in ways we are just learning. Often, we fail to notice the impact of how experiencing a possible school closure affects teachers. School closures have become an acceptable option for poor performing schools and are seen more often especially in rural districts. The purpose of this qualitative inquiry was to examine how four teacher leaders supported a rural school district and ultimately helped that school district narrowly avoid closure through their efforts. This study allowed key teacher leaders to share their stories and the lived experience of working with a high needs rural school district that faced closure and provided the insight on how teacher leaders can support school turnaround. The research provided insight of the possible impact the threat of school closure had on the stakeholder’s morale and their experiences as the school went through the processes required to avoid closure. This study incorporated a basic qualitative design using in-depth interviews with four teacher leaders who experienced the threat of a school closure and examined their perceptions regarding the school districts implemented changes designed to avoid closure and improve the district
An optimization model for designing a resilient green supply chain network for dairy industries
No full textThe effectiveness and resiliency of the dairy industry are crucial for maintaining a constant supply of dairy products to consumers around the globe. To enhance the planning and management of the dairy supply chain, it is required to develop an integrated planning where the production, distribution, and logistics are modelled simultaneously. In this research, the key objectives, such as the identification of crucial links in the supply chain, the evaluation of risks and disruptions, and cost-effectiveness as well as environmental impacts are considered. The aim of the study is to create a resilient dairy supply chain network design considering the key objectives between farms and factories. The optimization model developed in this research can optimally determine daily production quantity, transportation route, and transported quantity. The model yields optimal solutions that are both financially viable and environmentally sound. Implications for the dairy sector are examined, along with the trade-offs that were made to attain these results. The model can enhance the resiliency of the network while minimizing the disruptions and reducing costs as well as environmental impacts
Predicting customer churn using deep neural networks
No full textOne of the major problems for customer relationship management in a company is retaining their existing customers. When customers choose to switch to a different service provider, it is called customer churn. Customer churn is a severe problem for any business as it affects both the profit as well as the reputation of the company. This thesis explores the effectiveness of using deep neural networks in predicting customer churn. In this thesis, two types of deep neural network models were used: convolutional neural networks and regular neural networks. These networks were tested on three publicly available datasets: a bank churn dataset and two telecom datasets. The two telecom datasets are referred to as telco and Cell2Cell datasets. As part of the pre-processing of the data, data imputation was performed, followed by the encoding of the categorical values. Regularization has been applied to the layers of the networks to avoid overfitting of the models. The learning rate of optimization algorithm used in the networks are exponentially decayed for quicker convergence of the network parameters. The training of the networks is monitored using early stopping callbacks. The configuration of neural network models along with the aforementioned steps achieved better churn prediction accuracies than the existing neural models on these datasets. On Cell2Cell dataset, an accuracy of 80% was achieved while existing models gave an accuracy of 71%. On telco dataset, a prediction accuracy of 86% was achieved while precious models provided 83% prediction accuracy. An accuracy of 87% was achieved for the bank churn dataset. Additionally, the churn prediction models using deep neural networks were compared with other machine learning techniques such as decision tree, naive Bayes, support vector machines, and random forest, and the results showed that the churn prediction models using deep neural networks provided better prediction accuracies
Nepali immigrants' beliefs, efforts, and challenges in maintaining heritage language in California, North Carolina, and Texas
No full textMaintenance of a heritage language (HL), a non-renewable social resource, is critical to improve immigrant children’s academic and professional outcomes, maintain linguistic ecology, cultural diversity (Skutnabb-Kangas, 2004), and foster peace and harmony in society. This qualitative study investigated the beliefs, efforts, and challenges of 15 first-generation Nepali immigrants in maintaining HL in California, North Carolina, and Texas. There were two datasets; the first dataset was collected from 15 semi-structured interviews (California=5, North Carolina=5, and Texas=5) and the second from document reviews (n=30) published by six Nepali organizations (California=2, North Carolina=2, and Texas=2). Qualitative data analysis included descriptive statistics, coding, and content analysis. Two frameworks - Family Language Policy (Spolsky, 2004) and Capacity, Opportunity, and Desire (Grin, 2003) - guided the development of research and interview questions and analysis of data for this study.
The majority (93%) of Nepali immigrant parents in this study held positive beliefs towards the maintenance of HL across generations, as they (73%) saw integrative values of Nepali HL in the United States. Parents’ language beliefs were influenced by U.S. mainstream educational, social, economic, and political forces and differed regarding their children’s speaking, reading, and writing skills. All 15 parents wanted their children to be fluent in Nepali speaking, putting less effort into developing literacy skills. Parents shouldered the key responsibilities in maintaining the Nepali HL and made efforts at family and community levels. The 15 Nepali immigrant parents spoke Nepali with their children, socializing children to Nepali HL and culture, and providing semi-formal and structured instructions in basic Nepali literacy. Nepali immigrants faced practical challenges to maintain HL, which include the lack of teaching-learning resources, language teaching skills, teaching time, children’s interest and motivation, and support from extended family. Despite parents’ efforts, children’s preference of English use with parents, siblings, and peers revealed a possibility of language shift to English gradually.
Findings indicate that Nepali HL maintenance, particularly creating effective environment for children to practice and develop Nepali HL, in the United States requires an active and dedicated support of Nepali families and communities. It would be beneficial for Nepali communities to collaborate with U.S. local governments, non-profits, and schools to find resources and legitimize community-managed Nepali HL schools. Future research that examines children’s perspectives, dynamics of first-generation Nepali immigrants’ beliefs over time, and effectiveness of community-managed HL schools would help better understand the status and dynamics of Nepali HL maintenance