Elementary Education Capstone

This capstone project focuses on developing and implementing a literacy unit centered on textual evidence. The unit includes three lesson plans designed to help students understand how to find, analyze, and use textual evidence to support their ideas. Each lesson builds on the previous one, using a mix of direct instruction, guided practice, and independent work to gradually increase student confidence and skill in citing evidence. To measure student understanding, a variety of assessments were integrated throughout the unit. These included formative assessments, such as class discussions and written responses, as well as summative assessments that evaluated students’ ability to apply their learning in more structured tasks. The results of these assessments helped determine how well students grasped the concept of textual evidence and where additional support was needed. Overall, this capstone demonstrates how a well-structured unit on textual evidence can improve students’ literacy skills. It highlights the role of explicit teaching, interactive activities, and ongoing assessment in fostering critical reading and analytical thinking. The findings from this project contribute to best practices in literacy education and offer insights into effective strategies for teaching textual evidence in a classroom setting

The Influence of Reward and Reward Sensitivity on Executive Functioning in Adults

Executive Functions (EFs) are a critical aspect of advanced human mental processing and higher-order functioning. The performance of EFs within adults was evaluated to examine the extent that reward presence and participant reward sensitivity influences such EFs performance. Previous research has indicated that the presence of a reward to children with low reward sensitivity tended to exhibit improved EFs when compared to children with high reward sensitivity. Similar trends were illustrated within studies on adults participants and urged for further exploration. Participants completed a Reward-Responsiveness Scale via a self-report survey to be designated as either high or low reward sensitivity, and were then tasked to complete a Color-Word Stroop Task both in the presence of and without a reward. Results indicated contrary to previous trends that the presence of a reward and participant reward sensitivity did not demonstrate improved EFs performance in participants. These findings did not indicate a relationship between reward presence and reward sensitivity with EFs as previously hypothesized, but provided insight into the innerworkings of EFs as a whole

Rescuing behavioral development after prenatal alcohol exposure in mice

Due to the difficulty of detecting a pregnancy, prior to 6 weeks of gestation, ~30% of pregnant women report drinking alcohol during the first trimester. Prenatal alcohol exposure (PAE) can be extremely dangerous for the development of a child, often leading to an increased risk of developing fetal alcohol spectrum disorders (FASDs), which can affect a child’s ability to learn, control behavior, or regulate emotions. Alcohol initially stimulates an inflammatory cells in the central nervous system, known as microglia, causing a fetal anti- inflammatory response which alters the vascular and neurological in the fetal brain. Repeated or chronic alcohol exposure forces the microglia to remain in an inflammatory state that leads to the development of FASDs. Here, we present our preliminary investigation into the behavioral effects of PAE on mice exposed to ethanol during the first trimester of pregnancy. The behavioral impact of the PAE is evaluated using a series of three tests including: open field tests used to measure the activity levels; object recognition tests used to assess memory and recall; and social interaction tests to investigate preference of a differing social stimuli. This is the first step in the projects overall aim to use in-utero pharmacotherapy to inhibit the post-PAE chronically active microglia to prevent the development of FASDs

The Integrated Teacher: A Mixed Methods Study On How Professional Development In Comprehensive Wellbeing Practices Affect Special Education Teacher Stress And Efficacy

This Improvement Science Dissertation in Practice (ISDiP) sought to examine the effects of mindfulness-based and trauma-informed instruction on special education teachers\u27 (SETs’) perceived levels of stress and self-efficacy to improve teacher wellbeing, reduce attrition, and foster a stronger sense of school community. This study was conducted in a large, urban public school district in the Northeastern United States using a mixed-methods explanatory sequential design within a participatory action research framework. The research addressed the following questions: Does participating in an eight-week virtual training in mindfulness exercises positively influence the perceived levels of jobrelated stress among SETs? Does participating in an eight-week virtual training in trauma-informed practices positively influence the self-efficacy of SETs? How do SETs experience the impact of mindfulness training on their perceived levels of job-related stress? How is the self-efficacy of SETs impacted by trauma-informed training? Eight SETs (n=8) participated in eight one-hour virtual intervention sessions outside of contracted school hours, engaging with mindfulness and traumainformed strategies. Findings from pre- and post-intervention surveys indicated a slight statistically insignificant increase in participants\u27 stress levels. Similarly, self-efficacy levels slightly increased, but this change was also not statistically significant. However, qualitative findings suggested that participants perceived these interventions as beneficial in managing stress, fostering emotional resilience, and improving their ability to support students with exceptionalities (SWEs). Participants also reported feeling more connected to their peers and experiencing greater professional fulfillment. While the quantitative data did not demonstrate statistically significant changes, these findings suggest that mindfulness-based and trauma-informed practices hold promise in supporting SETs’ wellbeing. Future research should explore long-term implementation strategies and consider larger sample sizes to further examine the impact of these interventions on teacher retention, school culture, and student outcomes

Host Traits and Temperature Predict Biogeographical Variation in Seagrass Disease Prevalence

Diseases are ubiquitous in natural systems, with broad effects across populations, communities and ecosystems. However, the drivers of many diseases remain poorly understood, particularly in marine environments, inhibiting effective conservation and management measures. We examined biogeographical patterns of infection in the foundational seagrass Zostera marina by the parasitic protist Labyrinthula zosterae, the causative agent of seagrass wasting disease, across \u3e20° of latitude in two ocean basins. We then identified and characterized relationships among wasting disease prevalence and a suite of host traits and environmental variables. Host characteristics and transmission dynamics explained most of the variance in prevalence across our survey, yet the particular host traits underlying these relationships varied between oceans, with host size and nitrogen content important in the Pacific and host size and density most important in the Atlantic. Temperature was also a key predictor of prevalence, particularly in the Pacific Ocean. The strength and shape of the relationships between prevalence and some predictors differed in our large-scale survey versus previous experimental and site-specific work. These results show that both host characteristics and environment influence host–parasite interactions, and that some such effects scale up predictably, whereas others appear to depend on regional or local context

Business Education 4.0: A Pedagogical Emphasis on Innovation, Flexibility, and Scalability

Higher education institutions (HEIs) face increasing competition, not only from peer institutions but also from technology companies and software developers. The traditional educational model in HEIs is losing its appeal in comparison to more targeted and embellished learning offered by specialized outlets. This study proposes an innovative educational model aiming to help higher education avoid obsolescence. The proposed model, dubbed Business Education 4.0, treats content as building blocks that can be used to build personally tailored courses. The model guides students through creating their modularized custom courses, delivers course materials, analyzes student performance, offers students continuous support, and gathers feedback. Two pilot cases were conducted to evaluate the practicality of the proposed model, and a follow-up survey was used to collect feedback, which was significantly positive

The Expression Pattern of α6 and β4 Integrin Receptor Subunits in Cultured Chick Forebrain Neurons

Previous data suggest that a laminin receptor is localized in the axons of chick forebrain neurons mediating the axon-growth promoting properties of laminin. Many heterodimers from the integrin family of proteins have previously been identified as laminin receptors, including the α6β4 heterodimer. We tested the role of β4, β1, and α6 integrins in laminin-induced increases in axonal growth using function blocking antibodies. Axons of neurons grown on laminin treated with β4 integrin function blocking antibodies or α6 integrin function blocking antibodies were significantly shorter compared to untreated cultures or cultures treated with a β1 integrin function-blocking antibody. These data are consistent with the hypothesis that the α6β4 heterodimer acts as the axonal laminin receptor in embryonic chick forebrain neurons and is important in axonal development and growth. To directly test whether α6 or β4 integrin was localized to axons, we transfected cultured forebrain neurons from embryonic chick with DNA constructs encoding both α6 and β4 integrin genes. Immunostaining was performed to both α6 and β4 integrins and visualized via fluorescent microscopy. Preliminary results show α6 and β4 integrin expression in axons as well as dendrites

Optimal Prediction of Bitcoin High and Low Prices: An Exploratory Analysis

The purpose of this paper is to provide traders with a trader friendly model that would enable them to accurately predict Bitcoin’s high price and low price so that they are able to make more informed decisions for improved risk management when trading the highly volatile asset – Bitcoin. To achieve this purpose, this paper poses the following research question: Which statistical model-frequency combination best predicts – in terms of Mean Absolute Percent Error (MAPE), Akaike Information Criterion (AIC), and Schwart Information Criterion (SIC) – Bitcoin’s high price and low price? This paper also poses the objective of ensuring that the research question is both answered and that the statistical model-frequency combination selected is trader friendly or in other words, both easy to implement and interpret. To answer the research question and to meet the objectives of this paper, this paper develops two types of statistical models – Ordinary Least Squares (OLS) and Autoregressive Distributed Lags (ARDL). These models are developed across multiple frequencies – daily, weekly, and monthly. These statistical models and frequencies are chosen due to their trader friendliness, which aligns with the objective of this paper. Results for each of these models training sets show that the ARDL Bull Weekly model best predicts Bitcoin’s high price while the ARDL Bull Monthly model best predicts Bitcoin’s low price. To test the robustness of these two models, each model is tested on 7 robustness tests that incorporate out of sample data that covers various market conditions from 2011 to 2024. Results for the robustness tests show that both the ARDL Bull Weekly model and ARDL Bull Monthly model are highly robust for the out of sample data and market conditions they are tested on. This is evident in both models’ remarkable average mean absolute percentage error (MAPE) across out of sample robustness tests of 1.3% (ARDL Bull Weekly) and 3.28% (ARDL Bull Monthly). This indicates that these models could be used by traders to accurately predict Bitcoin’s high price and low price so that they are able to make more informed decisions for improved risk management

The Influence of Social Media on Substance Use Tendencies

The purpose of this research study is to investigate the relationship between social media usage and substance use tendencies among college students. Our study surveys Sacred Heart University students with an aim to understand their attitude towards social media’s influence on substance use on college campuses and collect data to analyze if there is a positive correlation between higher levels of substance use and higher levels of social media use