The LAIR at East Texas A&M
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The Effect of a Resource Management Intervention on Academic Performance and Self-Regulated Learning
No full textResource management is a component of self-regulated learning that involves the processes involved in selecting and using resources to fulfill learning goals. An effective learner is able to select the most appropriate resources for learning. While many interventions have focused on providing new resources or identifying the most effective ones, few have addressed whether students are using these resources in an effective manner. The present study explored a strategic resource use exercise for improving academic performance and investigated a potential mechanism of resource management. Undergraduate organic chemistry students (N = 498) were randomly assigned to either the strategic resource use (SRU) or control condition. All students completed a pre-exam survey asking about their desired grade on the exam and rated their motivation and confidence to achieve that grade. Students in the treatment group also completed the SRU exercise after the pre-exam prompt, asking them to make a specific plan for which resources they would use to study. The SRU exercise had no overall effect on exam performance on average; however, there was a significant interaction between experimental condition and baseline metacognitive awareness. Students with below average metacognitive awareness in the treatment group performed better on exams, while students with above average metacognitive awareness performed worse on exams, indicating a potential expertise reversal effect. There was no association between reported explore, exploit, and prune behaviors and academic performance
Effects of a Prosociality Intervention on Prek-12 Teachers’ Occupational Wellness and Colleague Relationships
No full textThe issue of teacher stress and burnout are long-documented issues within the education system (Agyapong et al., 2023; Brasfield et al., 2019; Jones and Ali, 2021; Pressley, 2021; Wettstein et al., 2021). These were only exacerbated by the COVID-19 pandemic (Baker et al., 2021; Herman et al., 2021; Hesham Abdou Ahmed, 2023; Pressley, 2021; Westphal et al., 2022). These have led to high levels of attrition and turnover in the teaching profession (Bastian & Fuller, 2023; Carver-Thomas et al., 2021). As a result, many teachers are reporting low levels of occupational wellness (Carroll et al., 2022; Farley & Chamberlain, 2021; Keeley, 2024). In efforts to address this problem, the current study sought to implement an 8-week prosociality task-related intervention to help with improving teacher wellness and colleague relationships and job satisfaction (two variables related to teacher wellness). It was hypothesized that participation in this intervention would lead to higher levels in the outcome variables of teacher wellness, colleague relationships, and job satisfaction. Although significant differences were not found to support the hypothesis, a medium or large effect size was found for the measurements of all the outcome variables, presenting encouraging potential for this intervention if and when it is replicated in the future. Future research is also discussed
Code-Switching: A Study on College Students’ Languaging Practices
No full textMy linguistic background is composed of many contrasting elements. I grew up speaking Spanish and English in rural Texas, and I have an accent. Words would have a southern drawl, and when saying words that were similar in English and Spanish, I would pronounce them with a Spanish accent. In contrast, many of my language arts teachers prior to high school put great value on Standard English. My accent was often corrected and dismissed, and while it wouldn’t affect my ability to navigate a classroom, I would hold it back in class nonetheless. Due to all these components, I had to find a way to balance language in my life. I needed to speak English at school, but I couldn’t stop speaking Spanish entirely because I valued my heritage far too much. I went from speaking Spanish (sometimes “Spanglish”) at home and with my older family to slang-filled English with my friends and my younger family, and finally, to academic English in front of my teachers. I would make this switch multiple times a day without even realizing it. Furthermore, I hadn’t realized the effects that code-switching subliminally had on my life. I found myself subconsciously turning to Standard English in most situations, and I had become hesitant of the language I grew up with.
In my junior year of high school, I learned about code-switching. It didn’t take long before I understood that this was the language practice that I had been subconsciously using all of my life. Even with the knowledge of code-switching, I did not have the tools to properly combat this issue in my life. I was able to explore the topic further in a college course I took with my thesis advisor, Dr. Gavin Johnson. Not only was I provided with more resources to explore code-switching and how it affects others, Perez 3 but also I was able to apply what I was learning by conducting a small-scale study at the East Texas A&M University campus
Experiences of School Based Agricultural Educators at the Middle School Level
No full textA middle school (MS) agricultural education program is the starting point for many students to explore agricultural industries and occupations associated with food, fiber and natural resources (National Council for Agricultural Education, 2002). “Middle school is an important time in the development of agricultural education students and plays an important role in increasing agricultural literacy in our society,” (Jones, Doss, and Rayfield, 2020). MS agricultural programs have been recognized since 1988 (Golden et al., 2014), yet there has been minimal research regarding these programs. This phenomenological study explored the experience(s) of School Based Agricultural Educators or SBAEs and examined how those teaching experiences influenced the participant’s view on teaching agriculture at the MS level. Purposive sampling techniques were utilized to attain a sample of five participants who have been teaching agriculture at the MS level in Texas. This research identified three common themes amongst MS SBAEs: Positive experiences with actively engaged students, opportunities for innovative teaching, and unique needs of middle school students. Participants in this study shared an overwhelmingly positive outlook on teaching MS agriculture and had a wealth of experiences associated with it. These themes show some of the opportunities that MS SBAEs can experience which the Self-Efficacy Theory states will promote high self-efficacy development. This directly impacts a person’s perceived self-efficacy which is the foundation of their inspiration, motivation, performance, accomplishments, and emotional well-being. These findings lead the researchers to highlight the need for undergraduate pre-service teacher preparation programs and professional development that draw attention to the cognitive and developmental differences found between middle school and high school students for both curriculum and experiential learning opportunities at the MS level. We recommend similar studies, both qualitative and quantitative, be replicated regionally and nationally to determine if other groups of MS SBAEs report similar experiences
Image Distillation with Machine Learning Image Modification and K-Means Clustering
No full textImage dataset distillation synthesizes a representative set which preserves the features of the original larger training set that leads to significant decreasing of computer resources. This work develops efficient dataset distillation method based on gradient image modification with k-means clustering representation for model training. It targets significant reduction in dataset size while maintaining model performance. First, we modify the training images, then apply k-means method to cluster them, after that we take the mean of every cluster as distilled images. Experimental results for the proposed approach are conducted on the benchmark image datasets Digit-MNIST, Fashion-MNIST, and CIFAR-10. The thesis completes with comparing our experimental result with those obtained by contemporary method
Characterization of Zinc-binding Heptapeptides as a Replacement for the His Tag in Improved Protein Purification Efficiency
No full textZinc-binding peptides play a critical role in various biological and biochemical applications, particularly in metal coordination and protein purification. The ability of peptides to bind metal ions is essential for protein stability and affinity-based purification techniques such as immobilized metal affinity chromatography (IMAC). Traditional purification strategies often rely on polyhistidine (His Tag) sequences. However, alternative peptide motifs with enhanced metal-binding properties could improve efficiency and selectivity. In this research, the zinc-binding properties of novel acetylated heptapeptides, ac-X1-X2-Gly3-Pro4-Tyr5-X6-X7, where X1X2X6X7 = His1Cys2His6Cys7 (HCHC), Asp1Cys2His6Cys7 (DCHC) and Asp1Asp2His6Cys7 (DDHC) were investigated. The zinc-binding properties of the heptapeptides were studied through advanced techniques including Ultra Violet-Visible (UV-Vis) Spectroscopy, molecular modeling, pH-dependent affinity studies, and zinc chelating resin binding experiments. These techniques were used to assess whether the heptapeptides could serve as an effective alternative to the His Tag (7×His) for metal-affinity purification applications. Following the competitive Zn-binding studies, Zn(II)-chelating resin experiments were conducted on the heptapeptides to show their binding efficiencies using divalent zinc, coordinated by iminodiacetate, coupled to 6% cross-linked agarose beads, to mimic the IMAC process. The binding efficiencies of the heptapeptides were compared to the standard 7×His Tag using ion mobility – mass spectrometry with an internal standard method. Further analyses were conducted through UV-Vis spectroscopy to quantify the binding efficiency and selectivity of the peptides. The results indicated that the ZBP HCHC exhibited superior binding to the Zn(II)-resin compared to the 7×His Tag, maintaining strong retention under conditions typically used in IMAC purification. HCHC was not only able to bind Zn(II) more effectively than the His Tag but also demonstrated efficient elution from the resin under mild pH 3.9 conditions. This characteristic is particularly advantageous for affinity purification workflows, as it reduces the need for harsh elution conditions that can compromise protein integrity and yield. The improved performance of HCHC in both competitive binding, UV spectroscopy and resin-based assays highlights its potential as a superior alternative to the traditional His Tag in metal-affinity purification, offering enhanced binding efficiency, selectivity, and ease of recovery
\u3c\u3eAb Initio\u3c/i\u3e Calculations of the Electronic Structure of Aluminum, Aluminum Oxide, and Aluminum Nitride Using DFT Formulation
No full textFirst-principles calculations based on density functional theory (DFT) have been used to investigate the electronic structures of aluminum (Al), aluminum oxide (Al2O3), and aluminum nitride (AIN) ab initio. In the VASP code, the GGA potential has been used for this. The main goal is to examine how aluminum’s partial density of states (s-DOS, p-DOS, and d-DOS) alters when it forms bonds with various atom kinds. In order to determine the distribution of electronic states and important characteristics controlling the electrical and optical properties of Al, Al2O3, and AIN, the density of states (DOS) in the valence and conduction bands will be examined. The analysis of the valence and conduction bands is expected to highlight the presence of band gaps in Al2O3 and AIN. These materials have potential applications in semiconductor and optoelectronic devices. In addition, the study will investigate the electron transfer mechanisms between Al and its neighboring atoms, providing insights into the bonding characteristics and charge redistribution upon compound formation. The results are expected to reveal significant hybridization between the s and p orbitals of aluminum with the oxygen and nitrogen neighbors leading to modifications in the electronic band structure
Historical Thinking Skills in Action: A Content Analysis of State and National History Standards
No full textThe subjects of this study were the representation of (a) historical thinking skills in U.S. History standards across 11 states and (b) the National Curriculum Standards for Social Studies. The study focused on the historical thinking skills identified by frameworks developed by key scholars Wineburg and Lévesque in the study of historical thinking. The researcher sought to answer the following research question: To what extent do high school U.S. History standards across 11 states embed historical thinking skills? The states included in this study were selected as part of a purposeful sample for their regional and political diversity and for various quality levels identified by the Fordham Institute. Using qualitative content analysis, the researcher examined patterns in how historical thinking skills are incorporated into content standards across the nation. The mixed-methods analysis revealed significant disparities in historical thinking skill integration, with skill representation ranging from 100% integration in Minnesota to 39% in Texas. Significance emerged as the most prevalent skill (92 total standards), while corroboration was the least represented (6 total standards). State standards predominantly emphasized conceptual skills (significance, continuity and change, progress and decline) over document-based skills, suggesting that students may develop awareness of important historical events without the critical skills needed to evaluate historical evidence. These findings have important implications for curriculum development, teacher preparation, and assessment practices, particularly as states like Texas prepare for a state social studies standards revision. In an era of information overload and misinformation, this study underscores the urgent need for more comprehensive integration of historical thinking skills to prepare students not only for academic success but for thoughtful citizenship in the United States’ complex democracy
Comparing the Strength of the Confidence-Accuracy Versus Response Time-Accuracy Relationship for Eyewitness Identification
No full textResearch indicates that eyewitness identification (ID) accuracy increases with faster IDs and those supported with immediate high confidence, but it is not clear which measure, confidence or response time, is the better reflector of accuracy. It is also important to know how well these patterns hold up across important factors affecting eyewitness ID accuracy such as memory strength for the perpetrator’s face. We conducted four pre-registered experiments to investigate these issues across different levels of target memory strength (via encoding time or image quality) and ID procedure (showups vs. lineups of different filler quality). Correct IDs were faster than false IDs regardless of memory strength, and this difference was greater for lineups than showups. There was a consistently strong positive CA relationship for those who made an ID, but the RTA relationship was significantly weaker. Both relationships were weaker for those who made a rejection decision, but the CA relationship remained stronger than the RTA relationship. We conclude that immediate confidence may be a more important reflector of accuracy than response time, regardless of the quality of the memory for the perpetrator’s face
Teaching Machine Learning to Undergraduate Electrical Engineering Students
No full textProficiency in machine learning (ML) and the associated computational math foundations have become critical skills for engineers. Required areas of proficiency include the ability to use available ML tools and the ability to develop new tools to solve engineering problems. Engineers also need to be proficient in using generative artificial intelligence (AI) tools in a variety of contexts, including as an aid to learning, research, writing, and code generation. Using these tools properly requires a solid understanding of the associated computational math foundation. Without this foundation, engineers will struggle with developing new tools and can easily misuse available ML/AI tools, leading to poorly designed systems that are suboptimal or even harmful to society. Teaching (and learning) these skills can be difficult due to the breadth of skills required. One contribution of this paper is that it approaches teaching this topic within an industrial engineering human factors framework. Another contribution is the detailed case study narrative describing specific pedagogical challenges, including implementation of teaching strategies (successful and unsuccessful), recent observed trends in generative AI, and student perspectives on learning this topic. Although the primary methodology is anecdotal, we also include empirical data in support of anecdotal results