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Imapct of regular attendance at religious services on stress levels and academic performance
No full textStress and its derivatives are one of the main issues for college students, affecting their GPA. Therefore, going to church might help to regulate stress
Mindfulness meditation: The role of guidance on effective introspection and modulation of levels of depression, anxiety, and perceived stress on college students.
No full textStudy looks at levels of depression, stress, and anxiety in college students, and whether or not mindfulness meditation would affect those levels within a couple of weeks. Current literature states that mindfulness meditation may be effective, but not as affective for novice interviewers. This study uses a fully novice sample, and asks whether being led by a more experienced meditator modulates the effect meditation has on depression, stress, and anxiety
Gender Differences in Love Expression and Love Reception: Exploring the Relationship Through the Lens of the Five Love Languages
No full textI will be describing the relationship between men and women and their preferred love language. I will be researching what their primary love language is and how that compares with the opposite sex
Exploring the Correlation Between Smartphone Notification Frequency and Fear of Missing Out (FOMO) Among Students at a Private Christian College: A Gender-Based Analysis
No full textThis study will look at whether there is a correlation between smartphone notification frequencies and levels of FoMO? It will also look into whether gender plays a statistically significant role in this correlation
Why do we serve?: Motivators and barriers to volunteering among undergraduate students.
Get PDFVolunteerism during an individual’s college years can potentially influence a lifetime of service. This research focuses on the motivators and barriers undergraduate students at a private Christian university face, focusing on differences between helping and non-helping majors. Data is gathered through convenience sampling via surveys administered to current undergraduate students at Southern Adventist University. With the importance universities place on service learning, this research will show ways in which students can be motivated to engage in service opportunities. It will additionally showcase potential barriers that can be addressed to further service engagement among students leading to a lifetime of service
The Effects of Sleep on the Friendship Quality of College Students
No full textMy presentation will explain if the quality of sleep has any affect on the friendship quality of college student
Optimization of Memory Management Using Machine Learning
No full textMemory overload can cause undesirable behaviors in a system. Proactive actions for memory safety may address this problem. Our contribution is to use machine learning models to classify different states of system memory using a dataset collected from a Raspberry Pi device. Several experiments were done on three datasets. For the first dataset, k-nearest neighbors had the best F1 score to classify medium and high RAM usage classes. For the second dataset, an artificial neural network had the best F1 score for each class. For the third dataset, logistic regression had the best F1 score for each class. The sliding windows used for classifications were created using inputs of 10 seconds of memory data usage to predict the next second of usage. This approach could eventually be used to classify and prevent memory overload scenarios
Dashboard to Quickly Estimate the Cost and Duration of an NYC Green Taxi Trip
Get PDFBefore hailing a New York City (NYC) taxi, residents and tourists do not easily know how much the trip will cost them or how long it may take. Taxis are still heavily used, even with the increase of ride-hailing services like Uber, and a new system has yet to be built to provide customers with these two metrics before taking a trip. This project aims to give riders a quick way to estimate a ride’s cost and duration through an interactive dashboard that allows filtering by pickup and drop-off neighborhoods. This is accomplished by analyzing three years of public data made available by the city of New York and presenting it to users through an interactive dashboard
Impact and Insights Gained from Emergency Preparedness IPE Simulation
No full textAHSRA 2024 Background Numerous studies have shown the benefits of interprofessional education (IPE) training and simulation (Banks et al., 2019; Carney et al., 2019; Dobbs-Oates & Wachter, 2016). The IPE collaboration competencies are essential for students to experience and achieve during their university years (IPEC, 2016; IPEC, 2011). The World Health Organization (2010) highlighted the need for students to participate in collaborative practice learning opportunities. There is a gap in the literature in that there are minimal studies from the education perspective. More research needs to be done to build the body of evidence. There is a need to incorporate simulation into pre-licensure/pre-certification education which can provide an opportunity for future healthcare workers to engage in life-like scenarios and gain practical knowledge in a safe, intentional, and orderly environment (Pinar, 2015). The findings from this EP-IPCP study will add to the empirical body of knowledge to impact educators and managers on the benefits of incorporating emergency preparedness simulation into the curriculum.
Research Question
This study explored students\u27 perceptions of how participating in an emergency preparedness interprofessional collaborative practice simulation impacts them for readiness for practice.
Methods -
Design
This study utilized a mixed method design with both quantitative and qualitative survey questions. The study received IRB approval from Southern Adventist University.
Sample
The sample consisted of 531 undergraduate and graduate students and volunteers. Specifically students from the schools of Education, Journalism/Communication, Nursing, Religion, and Social Work all participated in the study.
Data Collection
Immediately following the simulation, students were invited to participate in the online survey via a QR code. The online survey was created using Google Forms. All data is anonymous and password protected.
Data Analyses
The data automatically populates Google Sheets for ease of analysis. Descriptive statistics were conducted on the quantitative data and qualitative thematic analysis was conducted on the qualitative data.
Current Phase
Currently, this study is a longitudinal study beginning in 2015. Data has been collected every semester and is planned to continue.
Results
The results indicated that the majority (65%) of the students felt better prepared To assist in a classroom disaster. The vast majority (74%) felt they could better contribute to their local community as a result of participation in a disaster simulation. Additionally the vast majority (86%) felt that spirituality is an important element in disaster preparedness.
Implications
The EP-IPCP simulation is valuable for students and educators. Students learn how to respond to an emergency situation in a safe and controlled environment. They learn how to identify the needs of others and learn about their own reactions in a disaster scenario. As Educators we learn how students react to the disaster scenario and guide them to more effective practices and relating to their personal reactions. As SDA Educators it is our responsibility to train and equip students to be prepared to respond should the need arise. Because we know that disasters will continue to increase, we need to be proactive in preparing our students to be ready to assist people physically and spiritually
Using Generative Artificial Intelligence for Suggesting Software Architecture Patterns from Requirements
No full textThe job of software architects is vital for translating a list of requirements into a successful software product. Specifically, they are in charge of evaluating a list of requirements that the user entrusts to them, and craft an architecture that not only works, but also follows best practices. Because constructing a robust software architecture from requirements is often a complex process, our contribution is a solution that uses generative artificial intelligence (GAI) to suggest architecture patterns that best fit the given requirements with a description about how to use them in a project. The proposed solution fine tunes the Llama 2 LLM using QLoRA and SFTTrainer provided by the Hugging Face APIs with a custom dataset of requirements and patterns. The results of the experiments conducted on the fine-tuned model were moderately satisfactory, as the model correctly predicted the software architecture pattern in 70% of the test cases and provided a detailed usage explanation