The LAIR at East Texas A&M
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7179 research outputs found
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High School Course-Completion Trajectories and College Pathways for All: A Transcript Analysis Study on Elective Computer Science Courses
No full textAbstract: Whereas researchers regard high school math and science coursework as the best indicator of college readiness for students in the United States, computer science coursework and its relationship to college attendance, particularly for minoritized students, have not received due attention despite its root in the mathematical and scientific reasoning ability. We examined students’ high school course completion patterns across subjects and grade levels with a special focus on elective computer science courses and whether the coursework pattern transitions worked differently for minoritized students in Texas, USA. Latent profile analysis and latent transition analysis revealed multiple patterns of coursework, including Regular, Trailing, and Computer Science-Intensive. However, high school students seemed to attempt computer science courses with an experimental attitude. High school girls, low-income, and Latinx and African American students were less likely to complete computer science courses, despite demonstrating a similar coursework pattern in the previous year. Similarly, students with limited English proficiency, those eligible for free- or reduced-price lunch programs, and Native American students systematically have a lower chance to attend college, despite sufficient academic preparation in high school. Findings highlight the challenges minoritized students face and how students approach elective computer science courses in high school
Design of Pd–Zn Bimetal MOF Nanosheets and MOF-Derived Pd3.9Zn6.1/CNS Catalyst for Selective Hydrogenation of Acetylene under Simulated Front-End Conditions
No full textNovel zinc–palladium–porphyrin bimetal metal–organic framework (MOF) nanosheets were directly synthesized by coordination chelation between Zn(II) and Pd(II) tetra(4-carboxyphenyl) porphin (TCPP(Pd)) using a solvothermal method. Furthermore, a serial of carbon nanosheets supported Pd–Zn intermetallics (Pd–Zn-ins/CNS) with different Pd: Zn atomic ratios were obtained by one-step carbonization under different temperature using the prepared Zn-TCPP(Pd) MOF nanosheets as precursor. In the carbonization process, Pd–Zn-ins went through the transformation from PdZn (650 C) to Pd3.9Zn6.1 (~950 C) then to Pd3.9Zn6.1/Pd (1000 C) with the temperature increasing. The synthesized Pd–Zn-ins/CNS were further employed as catalysts for selective hydrogenation of acetylene. Pd3.9Zn6.1 showed the best catalytic performance compared with other Pd–Zn intermetallic forms
Image Classification Based on Sparse Representation in the Quaternion Wavelet Domain
No full textIn this study, we propose a novel sparse representation learning method in the Quaternion Wavelet (QW) domain for multi-class image classification. The proposed method takes advantages from: i) the QW decomposition, which promotes sparsity and provides structural information about the image data while allowing approximate shift-invariance, to extract meaningful features from low-frequency QW subbands, ii) the dimensionality reduction method using Principal Component Analysis (PCA) for reducing the complexity of the problem, and iii) the sparse representation of the generated QW features to efficiently learn and capture the meaningful and compact information of this data. After the QW decomposition, the features extracted from low-frequency image sub-bands information are projected, by the PCA, into a new feature space with lower dimensionality. The features extracted from the training samples are used to construct a dictionary, while the features of the test samples are sparsely coded for the classification step. The sparse coding problem is formulated in a QW Least Absolute Shrinkage and Selection Operator (QWLasso) model applying quaternion l1 minimization. A novel Quaternion Fast Iterative Shrinkage-Thresholding Algorithm (QFISTA) is developed to solve the QWLasso model. The experiments conducted on various public image datasets validated that the proposed method possesses higher accuracy, sparsity, and robustness in comparison with several contemporary methods in the field including Neural Networks
Classification Trees with Synthetic Features for Multiclass Classification Problems
No full textIn data mining, classification is considered one of the problems under supervised machine learning. One popular method for solving classification problems is the classification tree. Most of the algorithms for classification tree are used for binary classifiers. We throw more light on binary classification in this work and extend the knowledge into a multiclass classification problems. The two main approaches for dealing with multiclass classifications are reducing the multiclass classification problem to a collection of binary classification problems and directly boosting the multiclass classification problems. We give notes on the concepts of multiclass classification problems, throw more light on the different methods that are under the two main approaches, use the first method to conduct experiments with reliable datasets, then use the concept of cross-validation to fit, test and compare the accuracy of different models. We make use of original scripts in R and use concepts such as variable importance, and voting when fitting model and making predictions
Examining Instructional Practices in a Charter School Setting: A Descriptive Single Case Study
No full textFew researchers have investigated what occurs inside charter schools with respect to teaching and learning. To address this gap in the literature, the researcher conducted a descriptive, single-case study to examine how teachers at charter schools use research-based instructional methods to increase student achievement. The site for this study is a charter school in Dallas, Texas. The researcher used Friedman and Friedman’s school choice theory to shape the research questions and data collection procedures and used an organizational-level logic model to analyze instructional methods (case) used by individual teachers to deliver the instruction presented to them during professional learning community meetings. The researcher gathered data from direct observations, teacher lesson plans, class schedules, and student grade-level information. The researcher reviewed unidentified aggregate student benchmark scores by content. Based on the evidence from the data triangulation of interviews, focus groups and direct observations, the researcher determined that the district developed professional development and flexible curriculum improved teacher pedagogy. The results of the study indicated that teachers were eager to increase their knowledge of research based instructional practices to support student learning loss. The 3rd-8th grade unidentified aggregate student benchmark data suggested gains in math and reading
Not in This House: How Perceptions of Masculinity Affect the Marginalization of Same-Gender-Loving Members in Black Greek-Letter Fraternities
No full textThe research aims to discover marginalization within Black Greek Letter Fraternities(BGLFs) through the lens of duly initiated members who identify as same-gender-loving. The purpose of this study is to explore the perceptions of masculinity among duly initiated BGLF members who are same-gender-loving (SGL). This qualitative study utilizes a phenomenological approach to explore the lived experiences and perceptions of five to ten SGL BGLF members; this study will also provide a versatile and detailed account of the perceptions and experiences of masculinity in BLGFs. Moreover, this study will build on the existing pool of research about BGLFs, hegemonic masculinity, homophobia, and anti-homophobic bias present within these societies giving a chance to allow same-gender-loving members of BGLFs’ voices to be heard
Connecting Learning Sciences and Early Learning Outcomes: A Content Analysis of Preschool Early Literacy Apps
No full textThe purpose of this study was to examine the most popular educational preschool apps available to consumers to establish their alignment with early literacy learning outcomes and learning science principles. More specifically, this study examined (a) the descriptive characteristics of popular educational apps detailed in the Apple App Store, (b) the extent to which these mobile apps are intended to support the acquisition and growth of early literacy skills for preschool children as defined by national early literacy learning outcomes, (c) the presence of Learning Science principles within app activities, and (d) how app customer ratings align to content. This study used content analysis methods to conduct an organized investigation of the content of the ever-increasing mobile apps intended for children. Data were collected from a sample of young children’s mobile apps that were offered in Apple’s App Store. This study also sought to explore the degree to which mobile apps intended for the education of young children are designed in accordance with the core principles of the learning sciences. An essential part of this study was an examination of the content of educational apps, particularly those apps that claim to teach early literacy skills. A frequency analysis was used to determine the number and percent of apps supporting each Learning Science pillar and the acquisition and growth of early literacy skills as defined within the Head Start Early Learning Outcomes Framework (HSELOF). The pillars of active learning, meaningful learning, and engaged learning rated high within a majority of the apps. The pillar of social interaction was difficult to find in each app. The literacy apps in this sample had a central focus on alphabet knowledge activities. A log linear analysis was used to determine if the presence of any one Learning Science pillar could predict the presence of other pillars. A connection between active learning and engaged learning was the most significant. Last, app customer ratings were also compared to the HSELOF alignment using a frequency analysis. When examined, the apps rated 4.5 stars and higher, and all were aligned with alphabet knowledge skills
Cultural Reflexivity in Counselor Professional Identity Development of International Doctoral Students
No full textInternational counseling students in the United States come from a variety of different nationalities and cultures. From cultural to individual aspects, the experiences and the development of their identities are complex by nature. This interpretative phenomenological analysis explored the experiences of cultural reflexivity among international counseling students (N=5) that helped them to formulate their sense of counselor professional identity. Four main themes were identified, Unique Cultural Identities, Counseling Around the World, From Cultural Reflection to Cultural Integration, and Empower to Self-Advocacy. This study showed that cultural reflexivity is a common practice within international counseling students (ICS) individual processes, and that cultural integration is an essential aspect of their professional identity development as counselors. Concepts around ICS’ conceptualization of counseling and cultural identity were explored, and applicable implications were provided for counselor education, clinical practice, supervision, and leadership and advocacy
Effect of Supporting Base System on the Flexural Behavior and Toughness of the Lighting GFRP Poles
No full textDue to the high risk of common traffic electric poles, the use of glass fiber reinforced polymer (GFRP) material in electric poles has become essential due to its excellent advantages such as high strength to weight ratio, corrosion resistance, and electrical insulation, which keeps people safe. To reduce the accidental effect of street lighting poles on humans, the generated energy during the collision must be absorbed. Experimental and numerical investigations were carried out to identify the efficiency of tapered GFRP electric poles with handle doors using steel sleeve bases until the occurrence of failure. Six full-scale cantilever bending tests were performed to investigate the strength and ductility of the GFRP pole. Moreover, finite element (FE) models were developed using Abaqus software and verified against tests to provide alternative tools instead of lab experiments. An extensive parametric study was carried out to predict the effect of the GFRP pole wall thickness, base plate geometric (length, diameter, and wall thickness), electric cable hole diameter, material properties, and base sleeve geometric (length and wall thickness) on the toughness of the GFRP pole. Based on the results of the load–displacement (P–) curves, the flexibility of the GFRP poles was directly proportional to their length and the local buckling failure often occurred at the handle door. Strengthening the zone of the handle door using a steel ring was investigated to prevent the local buckling failure at this part. However, the wall thickness of the GFRP pole, base sleeve height, base plate dimensions, and base plate material properties were the most effective parameters to enhance accidental energy absorption through large deformation kinematics. The base sleeve thickness had a slight direct effect on the ductility and toughness of the GFRP pole