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Finding Aid for the Donald J. Incerto Papers (HSF-66)
No full textThe Donald J. Incerto Papers is composed of training manuals, handbooks, workbooks, guides, correspondence, reports, binders, presentations, handwritten scientific calculations and notes, notes, documents, and miscellaneous materials, created, used, and/or kept by Donald J. Incerto while he worked at NASA Johnson Space Center between 1962 and 1987. Incerto would work in a variety of positions from the Apollo Program through the planning for the Space Station. The majority of the collection is composed of Incerto’s manuals, information and document binders, training materials, and planning documents for the development of the Space Shuttle Program in the late 1970s to early 1980s, and the planning of the Space Shuttle in 1986 and 1987. There are also a number of NASA contractor materials for programs from Apollo through the Space Shuttle. The materials for the planning of the Space Station are the most original items in the collection, as these items laid the groundwork for the United States’ eventual development of the International Space Station. Perhaps the most unique item in the collection is an original Apollo–Soyuz Test Project (ASTP) photo-map book, produced and used at NASA Johnson Space Center Flight Control (SSR) around 1975. This map book used oversized color satellite photographs of the Earth, which were glued back-to-back to create double-sided photographic map pages of the Earth for use by American and Soviet Union space personnel during the operations of the ASTP project
The Influence of Early-Childhood Teachers’ Perceptions, Attitudes, and Technology Proficiency on Educational Technology Use in Early-Childhood Classrooms
No full textEarly childhood is a critical time to form the foundations required for success in education and life. Additionally, the 21st century has catapulted the world into an age of technology. It is imperative to find balance between the use of traditional teaching methods and ways to implement developmentally appropriate technology in early-childhood classrooms. The purpose of this study was to investigate the impact of early-childhood teachers’ perceptions, attitudes, and technology proficiency on educational technology use in early-childhood classrooms. To help answer the research questions, a random sample of early-childhood educators was selected to answer two established scale surveys on attitude towards technology and technology proficiency. Additionally, interviews were conducted to ascertain how teachers perceive the use of educational technology as a developmentally appropriate practice. A mixed-methods design was employed, and examination of quantitative survey results and qualitative interviews provided insight into teachers’ perceptions, attitudes, and proficiency of technology use in early-childhood classrooms as compared to their age and years of service.
Findings indicated early-childhood teachers with more years of service are more likely to feel confident in their proficiency with technology skills, resulting in higher implementation in their early-childhood classrooms. Additionally, early-childhood teachers’ attitudes towards educational technology do not change based on years of service. Furthermore, as an early-childhood teacher’s technology proficiency increases, his or her attitude towards technology also increases. Finally, although answers varied, all participants shared a conviction for doing what is developmentally appropriate for early-childhood students and felt quality instruction should be the most important goal in all early-childhood classrooms. This study revealed the need for teachers to feel competent in their abilities to use educational technology in early-childhood classrooms, despite their years of service
Swarm intelligence application in solving robot inverse kinematic problems
No full textThis dissertation aims to find the inverse kinematic solution for redundant serial manipulators using the meta-heuristic method, Particle Swarm Optimization algorithm (PSO). Primarily this paper focuses on moving the end-effector to any desired pose in cartesian space accurately by converging position and orientation with the PSO algorithm. In order to prove the exactness of the study, the result has been compared with some of other PSO research that only examines converging the position. All demonstrations were performed by using humanoid human-sized with 7 degrees of freedom robot (DOF), Baxter. First, the Denavit-Hartenberg(DH) table of Baxter's left arm is created, and transformation matrices are calculated according to two different setups joint angles to calculate target position and orientation values. Furthermore, joint angles are picked randomly for each particle, and the particles' pose is calculated by applying forward kinematics. In order to obtain subsequent angle values, the PSO algorithm, conversion of quaternion to a rotation matrix, and Jacobian matrices are utilized. This research gives another perspective to solving inverse kinematic by using quaternions instead of Euler angles. The Euclidian function is used to compute the cost function, which estimates the distance between the target pose and particle's pose. In this study, the algorithm is tested with several different concepts. Conclusively, the validity of the algorithm is verified via Gazebo simulation. The result confirms that the algorithm functions well in accuracy and merit of the swarm intelligence in solving the inverse kinematics problem for any serial robotic manipulators
Finding Aid for the David L. Eichblatt Papers (HSF-61)
No full textThe David L. Eichblatt Papers is composed of memos, correspondence, photographs, booklets, manuals, notes, maps, design plans, articles, scientific test information, scientific data, and miscellaneous materials, documenting the service of David L. Eichblatt at NASA Johnson Space Center from 1964 to 2009. Most of this collection consists of data Eichblatt collected as an engineer while he worked constructing, planning, and testing the aerodynamics on different spacecraft for NASA and the U.S. Air Force—mostly with the Space Shuttle orbiter program. During this period, he was in charge of the simulation programs for the testing of the Space Shuttle orbiters. Eichblatt’s projects included testing flights by comparing tire speeds, rollouts, landing, touchdowns, nose wheel contact, tail cone effects, number of engines, engine weights and fuel, parachutes, wings and parawing models, in different weather conditions, runway conditions, and different gravity effects for spacecraft and aircraft used by NASA. The collection contains study booklets prepared by Eichblatt, such as a take-off and landing performance study for the space shuttle orbiter vehicle in 1970, with data collection and hand-drawn aircraft information in them. There are materials documenting Eichblatt’s role in the simulation programs for the Shuttle, including the landing dynamics program, which simulated orbiter separation and derotation of the Shuttle orbiter following touchdown through nose wheel contact. There are research materials on the feasibility for the use of the modified Boeing 747 Shuttle Carrier Aircraft (SCA) to transport the Shuttle orbiter in the 1970s. The collection includes a set of photographs, a hand drawing, and data collection used by Eichblatt during his role in testing for a lunar motorcycle between 1969 and 1970. The collection also includes a set of rare, square photographic prints documenting his involvement in the Australian landing sites evaluation and survey with the Assured Crew Return Vehicle (ACRV) in 1993. This was part of the U.S. and Russia examining whether Russia’s Soyuz spacecraft could serve as stop-gap lifeboat spacecraft as NASA was designing a lifeboat for use for their planned Space Station Freedom. These are very unique images of an international NASA partnership with Australian space exploration personnel. The collection has an article, landing observations information, meeting agendas, photographs, documents, English-Russian translations, and letters, from Eichblatt’s role as leader of NASA team of four Americans and one Australian to Russia and Kazakhstan to observe the landing and recovery of the Soyuz TM-16 crew and capsule
The influence of administrative support on teachers in Title I schools during the Coronavirus pandemic
Get PDFThe purpose of this study is to examine the influence of administrative support on teachers in Title I schools during the Coronavirus pandemic. This present study will add to the knowledge base by providing information on teachers' work experiences in Title I schools during the Coronavirus pandemic. This study included a review of data collected from interviews of elementary teachers in a Title 1 district. A purposeful sample of 12 teachers who worked in a Title 1 elementary school during the Coronavirus pandemic were interviewed. The interviews provided an in-depth understanding of the teachers’ perceptions concerning administrative support during the pandemic in Title 1 schools. The findings of this study showed that administrative support has a significant role in influencing on teachers’ perception of teaching, self-efficacy, decreasing stress, cultivating positive school culture, and lessening teacher burnout. The recommendations include ways district and school level administrators can create a collaborative learning environment where teachers and students are successful
Examining the Relationship between Principal Leadership Styles and the Impact on Teacher Burnout
No full textThe purpose of this study was to examine the relationship between principal leadership styles and teacher burnout. The study included a review of data collected using the Multifactor Leadership Questionnaire (MLQ-5X) and the Maslach Burnout Inventory (MBI-ES) from a purposeful sample of teachers from one large urban Title I high school in a southeast Texas school district. A purposeful sample of nine teachers were interviewed for the purpose of providing a more in-depth understanding of their perceptions of the principal's leadership style and their experiences with burnout. Quantitative data were analyzed using frequencies, percentages, and Pearson's product moment correlations (r), while qualitative data were analyzed using an inductive coding process. Quantitative data analyzed the five transformational leadership attributes and the three factors of burnout. Quantitative analysis revealed that there were no statistically significant correlations to the principal's transformational qualities and teacher burnout factors of emotional exhaustion, depersonalization, and personal accomplishment. The qualitative analysis revealed that teachers perceived the principal as highly transformational, supporting the quantitative data, while the burnout experiences were significant for emotional exhaustion among the participants indicating that teachers are overextended in their job responsibilities. The qualitative responses of the participants further revealed that school leaders and districts need formal professional development plans to help teachers build capacity as well as to manage stress and burnout
Federated Learning to Build Sentiment Analysis Models for Amazon Review Datasets without Labels
No full textIn Natural Language Processing, one of the most popular tasks is sentiment analysis which aims to predict the sentiment of a text. It has many practical applications in industries such as marketing and customer service. Performance of sentiment analysis models play a significant role to the success of these applications. To achieve a high accuracy, sentiment analysis usually trains analytical models based on labeled datasets, preferably to large-scale labeled dataset. However, large-size labeled dataset may not be available because of the high-cost in labeling. Therefore, researchers study alternative approaches aiming to learn high accurate and reliable models based on small-scale labeled datasets or using other existing labeled datasets from different categories. A centralized model is a machine learning model that utilizes a large dataset stored on a central server to perform sentiment analysis. Training a centralized model on a small, labeled dataset can result in inaccurate or incomplete predictions. While processing
labeled datasets of different categories on a centralized platform, it also comes with many challenges such as data heterogeneity, bias towards the categories that are overrepresented, requirement of large amount of computational power and resources, and the availability of good amount of labeled data for training. In addition, it is difficult to select appropriate data categories to train a reliable model for the new category. In this thesis, we propose a federated learning approach to overcome these challenges.
Federated Learning (FL) is a type of decentralized Machine Learning (ML) that lets us train data analytical models on local data without transferring data to a central server. When Federated Learning is applied to sentiment analysis, one server and multiple clients collaborate to train a reliable and accurate sentiment analysis model. In our scenario, each client trains a local sentiment analysis model based on a labeled review dataset of a specific category, and the server makes use of the FedAvg algorithm to aggregate the parameters from the trained client models to build a global model for the new category that has no available labeled dataset. We evaluate the performance of our design based on a prototype implementation using Amazon review datasets. Compared with the centralized sentiment analysis, the proposed FL-based sentiment analysis performance is 10% better. This validates the potential of federated learning in training better data analytical models for categories with no large-scale labeled datasets
Sense of Belonging and the Imposter Phenomenon among International College Students
Get PDFThis study examined the association between the imposter phenomenon (IP) and a sense of belonging and planned to examine the differences between international students and domestic students on these psychological experiences. In addition, the study also explored the effect of the imposter phenomenon and sense of belonging on the subjective well-being of individuals by examining the students' self-reported happiness. I hypothesized that lower levels of belonging would be associated with higher feelings of being an imposter. The study was conducted with a total of 127 domestic students, including 65 first-generation students and 62 continuing-generation students, recruited from the University of Houston-Clear Lake Psychology Participant Pool. Participants completed the Social Connectedness and Social Assurance Scale (Lee & Robbins, 1995), the University Belonging Questionnaire (Slaten et al., 2017), the Clance IP Scale (1985), and the General Happiness Scale (Lyubomirsky & Lepper, 1999). No significant differences were found between the first-generation students and continuing-generation students except for subjective happiness, with first-generation students reporting less happiness than their peers. Across all participants and consistent with my hypotheses, I found a significant negative correlation between belonging and imposter phenomenon, and between subjective happiness and imposter phenomenon. The results suggest that students who feel more belonging are also more likely to feel happy and less likely to feel like an imposter, reminding us of the importance for universities to cultivate a sense of belonging for their students
Examining the Relationship Between Teachers' Perceptions of School Climate and Student Achievement of Middle School Students
Get PDFABSTRACT
EXAMINING THE RELATIONSHIP BETWEEN TEACHER’S PERCEPTIONS OF
SCHOOL CLIMATE AND STUDENT ACHIEVEMENT OF
MIDDLE SCHOOL STUDENTS
Tanya Wiser Edwards
University of Houston-Clear Lake, 2023
Dissertation Chair: Antonio Corrales, EdD
The purpose of this mixed-methods study was to examine the relationship between teacher’s perceptions of school climate and student achievement of middle school students. Two hundred twenty middle school teachers, from a large urban school district located in the Southwestern region of the US, participated in the New Jersey School Climate Survey. Student achievement was measured using the Reading and Mathematics STAAR test. Data collected from the survey and interviews revealed that administrative support, building relationships, teaching and learning, and school safety are crucial factors that contribute to having a positive school climate. Because states are holding schools accountable for student achievement, and improving school climate, this study could provide significant contributions to school districts, administrators, and to the global discussion on the relationship between school climate and student achievement
Finding Aid for the Space Exploration Clippings Collection (HSF-4)
Get PDFThe Space Exploration Clippings Collection is composed of photocopied newspaper and magazine articles made from original clippings collected since 1965 by Jeanette Bernstein Getz of Houston, Texas. Having been interested in science and human spaceflight, she began saving the articles while working as a medical secretary for the famed Houston cardiovascular surgeon Dr. Michael DeBakey. In 2007, Getz donated the collection to the University of Houston-Clear Lake Archives and Special Collections, due to their holding of the Johnson Space Center History Collection. The collection has articles from a wide variety of newspapers and magazines, though there is a large focus on Houston-based publications