The LAIR at East Texas A&M
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An Exploration of Teachers’ Experiences with the Teacher Incentive Allotment Program and Their Motivation to Stay at High-Needs Schools
No full textTeacher attrition continues to be a major issue in public education today. Keeping schools staffed with quality teachers is a struggle across the United States. Hard to staff, low-income schools see the highest attrition rates among public schools. This phenomenological qualitative study explored teachers’ experiences with the Teacher Incentive Allotment (TIA) program in Texas. The TIA is designed to provide incentives to quality teachers and extra incentives to quality teachers willing to work in high-needs schools. This dissertation qualitative methods study included interviews and questionnaires from participants. Participants were selected from a school district in Texas that is participating in the TIA program passed in House Bill 3 (HB 3). A review of the literature showed a need for further exploration on the impact incentives—specifically the newly developed TIA incentives—have on teachers’ motivation to stay at highneeds schools. The purpose of this qualitative study was to examine the experiences of teachers participating in the TIA program and explore how the allotment factors into their motivation to stay on a high-needs campus. Using hermeneutical research methods, the researcher explored the participants’ lived experiences with the TIA phenomenon to provide insight to policy makers and school districts on the impact the TIA has on teachers’ motivation to stay at high-needs schools
Principal Component Analysis for Training Data Distillation and Augmentation
No full textThe process of training is an important step in machine learning methods. In some cases, there is a shortage of training data. That is why, training data augmentations is an important field of research development. In this thesis, we applied the well-known method of Principal Component Analysis (PCA) as a data distillation tool. We used distilled data for training data augmentation. Further, we demonstrate that augmenting training data with PCA-distilled data increases classification statistics. To do so, we used three machine learning methods (Neural Network (NN), Logistic Regression Model (LR), and Support Vector Machine (SVM) to classify four different numeric datasets such as Skin Lesion (SL), Diabetes (D), Heart Disease (HD), and Breast Cancer (BC ). The experimental results, shown in the thesis, validate the statement ”Augmenting the training data with PCA distilled data, increases classification statistics”
Virtual Offloading: Note-Taking in a Web Environment
No full textGiven the technological advancements made in recent years, and the ongoing pandemic, many college courses have adapted to an online format. This prompts the need for more research about how students learn in online learning environments. Undergraduate students viewed a video lecture and completed an immediate and delayed comprehensive test over its contents. Two cognitive offloading strategies—note-taking and re-watching lectures—were manipulated across four conditions to examine if offloading is beneficial during online learning. Additionally, we wanted to compare the effectiveness of each method to determine which is best for online learning. Results from both tests showed a benefit of note-taking, although we did not see evidence of offloading—performance on a test immediately following the lecture showed an overall benefit of notetaking. Additionally, those who rewatched the lecture prior to testing showed the most improvement between the tests. Contrary to our prediction, knowing they would have a chance to rewatch the video did not decrease the number of notes they took during the initial viewing
Early College High School Models: A Qualitative Study on Organizational Resilience
No full textTo investigate the perceptions of Early College High School leaders in Texas to generate an understanding of Early College High School model resilience and adaptive leader actions that affect student outcomes. The Early College High School movement is gaining national traction and is heavily focused on developing human capital, student experience, increasing opportunity for underrepresented students, and producing agile high school graduates armed with skills and knowledge as they enter their post-secondary journey
Disparity of Representation and the Pathway to the Principalship: The Phenomenological Experience of Female High School Principals
No full textIn comparison to men, the high school principal role in Texas is a position that few women obtain in their educational leadership journey. Even though women are statistically more prominently employed as teachers in K–12 public education in Texas, women are not equally represented in the superintendency. This disparity of representation starts at the educational leadership level of principal. Since the vast majority of educational leaders who move into the superintendent role were once principals at the high school level, women are at a clear disadvantage because the high school principal role is statistically likely to go to men more often than women in Texas. A review of the literature identified a need for further study regarding the pathway to the high school principal role and the barriers that pathway holds, especially for women in Texas. The purpose of this qualitative study was to explore the career pathways of current female high school principals in Texas and determine the barriers these women have faced along the way. Through the use of hermeneutic phenomenology, the researcher strove to determine and understand the essence of the lived experiences portrayed by the participating principals in relation to the phenomenon of social role theory in Texas. The researcher used semistructured interviews and NVivo software in order to allow each participant to describe the lived experience of becoming a high school principal in Texas and to collect themes and nodes of their responses. Data analysis from the interviews illuminated nine emergent theses across two research questions. The first research question regarding the pathway to the high school principal ship revealed the following two emergent themes; (a) advancing titles through lower grade levels and (b) pathway preparedness. The second research questions, regarding barriers women faced revealed the following emergent themes: (a) capitalizing on mentorship, (b) working conditions/discrimination, (c) family and home responsibilities, (d) aspirations and confidence, (e) sex role stereotypes, (f) financial support, (g) opportunities for growth and advancement. These emergent themes are a result of the participants sharing their lived experiences as current high school female principals in the state of Texas
Real Time Classification of Facial Expressions for Effective and Intelligent Video Communication
No full textReal-time video communication has become a bigger part of everyone\u27s lives lately as webconferencing, video conferencing, and video calls become increasingly common, and this development is not just because of the COVID-19 pandemic. For instance, the business world now relies less on the use of offices and more on real-time online communication for day-to-day work activities. This is because it is more cost-effective due to the advancement in communication technology. Video and web conferencing are now being deployed for business meetings, training events, lectures, presentations, conferences, and many more. They are also used for important events like medical consultations, counselling sessions, school lectures, friends and family communication, and so much more. However, one huge problem with real-time video communication is that in most cases, especially when communicating with more than one person, it becomes difficult to read and understand facial expressions, which are important for effective communication. To tackle this problem, there have been relevant studies on how to make the computer recognize facial expressions during real time video communication but most of these studies have only considered seven facial expressions namely “Happy”, “Sad”, “Fear”, “Anger”, “Disgust”, “Surprise”, and “Neutral” because the dataset is readily available. So, this research proposed a system that not only recognizes the seven most common facial expressions listed above, but also recognizes four more facial expressions namely “Pain”, “Tired/Exhausted”, “Lack of Interest”, and “Showing Interest” during a real-time video communication. The system would recognize eleven facial expressions in total. To achieve this, I built two convolutional neural network (CNN) models to be able to recognize these eleven facial expressions. The first model (which I named CNNM9 because it has nine classifications) classifies facial expressions as either “Happy”, “Sad”, “Fear”, “Anger”, “Disgust”, “Surprise”, “Pain”, “Tired/Exhausted”, or “Neutral” with an accuracy of about 78%. While the second model (which I named CNNM3 because it has three classifications), classifies facial expression as either “Showing Interest”, “Lack of Interest”, or “Neutral” with an accuracy of about 90%
Career and Technical Education Teachers’ Perceptions of Professional Development Needs: A Q Methodology Study
No full textCareer and Technical Education (CTE) teachers have unique professional development needs due to their teaching content and route to teacher certification. A literature review revealed little to no research investigating CTE teachers\u27 perceived needs for professional development in Texas. Additionally, the literature suggests that teachers who enter the profession through alternative certification may not have the necessary pedagogical skills to succeed in the classroom. The researcher designed this Q methodology study to investigate the professional development needs of CTE teachers in a suburban school district and compare the results of university-based certified teachers and alternatively certified teachers within the population. The Q methodology allows teachers to rank factors based on their opinions providing a quantitative way to collect qualitative information
