SUNY Oswego
For more information about SOAR and how to submit your work visit our SOAR- SUNY Open Access Repository guide or contact Marissa Caico in Archives & Special Collections.
Sub-communities within this community
Recent Submissions
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UFLI Foundations: Literacy Intervention and AssessmentThis is a poster reflecting the results of a literacy intervention. The poster focuses on the pre/post intervention assessment results of one focus student.
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Let Young Black Girls Reclaim Their Voices and Reconnect With Their Ancestors A How to Guide By Using Legendborn By Tracy DeonnHow to allow young black girls reclaim their voices and reconnect with their ancestors in an ELA classroom
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UFLI Foundations Literacy Assessment and InterventionThe focus of this project was to identify a student within the focus school who demonstrates reading difficulties. The goal was to find a student who would benefit from the structured support of UFLI Foundations intervention lessons. Furthermore, this project was designed to measure the effectiveness of these lessons on improving the focus students' scores on multiple reading measures. These measures are used to indicate a student's level of reading proficiency.
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Organized for Success: Using Simple Assistive Technology to Support Spelling and Vocabulary GrowthThis project explores the impact of a simple assistive technology, a Word-Wall, on the spelling and vocabulary growth of a 3rd grade student with a learning disability. By reducing cognitive load and promoting independence, the tool supported meaningful engagement with writing tasks and improved the student's confidence and language outcomes.
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UFLI Foundations Literacy Assessment and InterventionThis poster presents the data from an intervention project with students in first grade.
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Using Assistive Technology to Support Self-Regulation in Students with Disabilities Who Struggle with Seated EngagementUsing the SETT framework, I have developed an intervention plan for a student classified with an emotional disturbance. This plan is expected to help the student succeed in the General Education setting.
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UFLI Foundations Literacy Assessments and InterventionThis project was designed to implement an effective reading program as a tier two intervention for students testing below grade level in reading and writing. This program provides explicit and systematic phonics instruction. It regularly progress monitors students to see if students are demonstrating growth. Students are assessed using four different assessments to see where in the UFLI scope and sequence they should begin their reading instruction, how the student groups are formed, and how much growth the student achieved. After implementing 20 UFLI lessons, I administered post tests to measure my student’s growth and determine if UFLI is the correct intervention for my student.
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Monitoring Disease Dynamics of Local Amphibian Populations in Oswego CountyAmphibian populations are declining worldwide, in part due to major pathogens such as ranaviruses and the fungus Batrachochytrium dendrobatidis. SUNY Oswego has been conducting a longitudinal study since 2012, field-sampling Oswego County amphibian populations and processing those samples in the laboratory to examine disease prevalence and potential influencing factors.
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UFLI Foundation Assessment and InterventionThe focus of this project was to assess our focus student using universal (ORF) and diagnostic (PAST, CORE, Spelling) screeners. Then, applying our initial findings to implement UFLI as a reading intervention strategy. Through this project the hope was to provide my focus student with the skills and knowledge to become a stronger, more proficient reader.
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UFLI Foundations Literacy Assessment and InterventionThe objective of this project was to implement UFLI Foundations, a reading intervention program that delivers explicit phonics instruction. In this intervention, I customized instruction to each student's individual literacy needs as demonstrated from assessment and progress monitoring data which I collected and analyzed. The primary focus was to improve my students' understanding and fluency with longer words by targeting skills such as prefixes, closed and open syllables, and compound words.
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UFLI Foundations Literacy Assessment and InterventionThis project was intended to act as a Tier II intervention for a student performing below grade level in oral reading fluency. I was able to conduct an initial assessment, followed by diagnostics to pinpoint where the student was most challenged. Over the course of 20 UFLI Foundations lessons, I aimed to increase the student's foundational reading skills and provide tools to help her read longer words.
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UFLI Foundations Literacy Assessment and InterventionThis project was focused on providing students with literacy instruction using UFLI Foundations, a reading intervention program. UFLI is an explicit and systematic phonics curriculum that aims to support students by receiving instruction in phonics based on their reading needs. Students were assessed using multiple measures to determine areas of targeted intervention. This intervention targeted students' understanding of final spelling patterns and their ability to read multisyllabic words. UFLI Foundations is a tier 2 intervention and was delivered in small groups to benefit students learning.
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Science Fiction in the Modern ClassroomSo often pushed to the margins of literary merit, we believe Science Fiction represents an interdisciplinary, mature, captivating, and boundary pushing artistic tradition waiting to be integrated into an ELA curriculum.
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Graphic Organizers: Assistive Technology for ComprehensionGraphic organizers have long been used in schools as assistive technology to help students structure their thoughts. They support comprehension by organizing information visually, making it easier to focus on key ideas and understand texts more effectively.
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Machine Learning Based Survival Analysis for Breast Cancer Using Clinical and Genetic DataThis project studies patient data from the TCGA PanCanAtlas to find clinical and genetical factors affecting survival. Using machine learning, it explores links between gene changes, tumor features, and outcomes. The goal is to improve predictions and support personalized treatment in breast cancer care.
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Exploring Development of Inpatient-Outpatient Decision Support SystemPatient care can be viewed as the prevention, treatment, and management of illness and the preservation of physical and mental well-being through the use of modern medicine. The setting where patient care takes place can be narrowed down by two categories: Inpatient and Outpatient care. Both of these treatment methods have benefits and drawbacks as one requires hospitalization and the other does not. The purpose of this project is to construct a decision support system based on laboratory screening of patients to determine whether it is more optimal to have a patient visit in a hospital (inpatient) or an outpatient setting.
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UFLI Foundations Literacy Assessment and InterventionsThe focus of this project was to assess and design interventions for a small group of students within an inner-city elementary school. Utilizing the UFLI Foundations explicit and systematic intervention structure, the goal was to increase the focus students' literacy knowledge and confidence as a reader. Progress monitoring was to be used as a guide for the intervention instruction and these lessons took place over the course of five weeks.
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AI METHODS FOR THE FUTURE OF PREVENTIVE HEALTHCAREThis study bridges health informatics and AI to shift healthcare from treatment to prevention. By analyzing behavioral patterns and health data, it enables early risk detection, personalized care plans, and proactive interventions reducing chronic diseases and fostering long-term well-being.
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Predictive Modeling of HIV Diagnosis Rates Using Machine Learning TechniquesIn this study, a machine learning model is developed to predict HIV diagnosis rates based on demographic and geographic factors. Regression methods, including Linear Regression, Random Forest, and XGBoost, are used to assess data on age, gender, race, state, and county. The findings back up focused measures to reduce transmission and the distribution of resources in public health campaigns.
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Machine Learning-Based Sleep Apnea Risk PredictionThis study aims to develop a machine learning-based model to predict the risk of sleep apnea using sleep patterns, physiological parameters, and lifestyle factors. The dataset consists of key attributes such as sleep duration, quality of sleep, physical activity levels, stress levels, BMI category, blood pressure, heart rate, and daily steps. Various preprocessing techniques, including feature scaling, categorical encoding, and handling class imbalance, will be applied to enhance model performance. Feature selection methods will identify the most influential factors, and machine learning models such as Random Forest, XGBoost, and Neural Networks will be evaluated. The model's performance will be assessed using accuracy, precision-recall scores, and AUC-ROC to ensure effective classification of individuals at risk of sleep apnea.