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WE’RE HERE: THE “OUTSIDER WITHIN “THE LIVED EXPERIENCES OF BLACK WOMEN COMMUNITY COLLEGE STUDENTS AT AN HISPANIC SERVING INSTITUTION
Get PDFThis qualitative research study sought to explore the lived experiences of Black women community college students as they pursued higher education at Hispanic-serving institutions. Students who were enrolled at a community college in the Inland Empire region of Southern California were interviewed in focus groups and one-on-one interviews. A hermeneutic phenomenology was used as the tool for analysis, and digital storytelling was used to provide a visual representation of the lived experiences of the students. These data points can be shared beyond the pages of this study. With limited research on understanding the unique needs of Black women students in community college, this study shed light on this subject in an effort to implement change. The key themes that came out of this study included (a) the need for support, (b) community care, and (c) racialized and genderized assumptions. These themes further reinforced the lack of support that surrounds Black women community college students and the critical role the institution plays in implementing these changes. The academy would be greatly served by gathering additional research about Black women community college students, creating culturally competent leadership and campuses and gaining a greater understanding of the impact Black women have in their communities
EFFECTS OF VOLUNTARY REMOVAL ON AN IMMIGRANT FAMILY
Get PDFThis study explores the effects on the family system when undocumented parents voluntarily leave the U.S. to gain legal status while their children remain behind. This study looks into the financial, emotional, and relational burden caused by the separation in order to gain legal status. This information is important to find possible alternatives and resources that can help families who go through a similar situation. There is an estimate of 1.1 million undocumented immigrants that can be led to leave the U.S. to gain legal status and spend years in their home country, which could potentially mean separation of families (Three- and Ten-Year Re-Entry Bars Policy Brief, 2023). This case study used qualitative interviews to gather information from each family member. Interviews were conducted via Zoom to and transcribed for analysis. Major themes and sub-themes were identified. Analysis revealed a number of effects on family dynamics and interpersonal relationships due to voluntary leave from the U.S. to gain legal status
IMPACT OF RESOURCE SCARCITY ON UNDOCUMENTED STUDENTS IN HIGHER EDUCATION
Get PDFBackground: Much progress has been made in understanding the impacts of identifying as an undocumented student in higher education, but knowledge of the scarcity of resources impacting undocumented students remains limited. Objective: This descriptive study examined the relationship between accessibility to social support and the psychological well-being of undocumented students in higher education. Methods: Quantitative data was gathered cross-sectionally from participants recruited using nonprobability sampling methods. The Kessler Psychological Distress Scale and Social Support Survey Scale were used to gather data on participants\u27 psychological distress and social support. A descriptive analysis was performed to yield summary statistics of participants’ demographics, psychological well-being, and social support. Results: All participants identified as Hispanic or Latino, most are attending a 4-year college, and most participants’ parents have less than a college education. The data suggests that 100% of participants reported struggles with mental health. Additionally, most reported less than favorable levels of social support throughout their academic career in higher education.
Conclusion: The mental health of undocumented students may be more complex than anticipated, where mental well-being may be impacted by factors beyond the levels and types of social support received. Future research should consider exploring other factors that might impact the mental wellness of undocumented students. Furthermore, Colleges serving undocumented students should ensure that this vulnerable group receives adequate educational support in efforts to boost their mental health
Building Confidence, Diminishing Stress: A Clinical Incivility Management Initiative for Nursing Students
Get PDFObjective: The aim of this study was to evaluate the effectiveness of an interactive program designed to reduce nursing students’ perceived stress and improve self-efficacy and readiness to professionally address incivility during clinical practice. Background: Incivility in clinical settings adversely impacts learners, educators, institutions, and healthcare systems, undermining safety and the teaching–learning process. Despite its increasing global prevalence, effective interventions remain largely unexplored. Methods: Our mixed-methods study, conducted from March to April 2024, involved senior baccalaureate pre-licensure nursing students (N = 35) from a California State University. The three-week, one-hour-per-week, interactive clinical incivility management program was developed through an extensive literature review. Pre- and post-intervention differences were assessed using a 10 min self-administered online survey that included the Uncivil Behavior in Clinical Nursing Education (UBCNE; 12 items), Perceived Stress Scale (PSS; 10 items), General Self-Efficacy Scale (GSE; 10 items), and a sample characteristics questionnaire (11 items). A one-hour face-to-face focus group (n = 11) then provided qualitative data on personal experiences of clinical incivility. Quantitative data were analyzed using SPSS version 27, while qualitative data were analyzed using Colaizzi’s method. Results: Clinical incivility prevalence was 71.4% (n = 25 out of 35). No statistically significant differences were found in UBCNE, PSS, and GSE scores between pre- and post-intervention. However, professional responses to clinical incivility significantly improved after the intervention (t = −12.907, p \u3c 0.001). Four themes emerged from the qualitative data: (a) uncivil behaviors or language from nurses, (b) emotional discouragement and low self-confidence, (c) resource and personnel shortages at clinical sites for education, and (d) the necessity for interventions to manage clinical incivility. Conclusions: Nursing schools and clinical agencies should collaborate to establish monitoring systems, enhance communication, and implement evidence-based policies and interactive interventions to prevent and manage clinical incivility experienced by nursing students from clinical sites
ENHANCING EMAIL SPAM DETECTION THROUGH ENSEMBLE MACHINE LEARNING: A COMPREHENSIVE EVALUATION OF MODEL INTEGRATION AND PERFORMANCE
Get PDFEmail spam detection and filtering are crucial security measures in all organizations. It is applied to filter unsolicited messages; most of the time, they comprise a large portion of harmful messages. Machine learning algorithms, specifically classification algorithms, are used to filter and detect if the email is spam or not spam. These algorithms entail training models on labelled data to predict whether an email is spam or not based on its features. In particular, traditional classification machine learning algorithms have been applied for decades but proved ineffective against fast-evolving spam emails. In this research, ensemble techniques by using the meta-learning approach are introduced to reduce the problem of misclassification of spam email and increase the performance of the combined model. This approach is based on combining different classification models to enhance the performance of detecting the spam emails by aggregating different algorithms to reduce false positives and false negative rates, and increase the accuracy of the combined model.
The paper proposed ensemble techniques where various machine-learning algorithms are combined to improve the accuracy and strength of spam detection systems. Using different algorithms, it tries to create an appropriate systematic behaviour to increase the detection rates and reduce the number of misclassification cases. In this research, four machine learning algorithms were selected to build the meta-learning model; these algorithms have been chosen based on their proven effectiveness in spam detection systems, such as Naive Bayes (NB), Support Vector Machine (SVM), Decision Tree (DT), and K-Nearest Neighbours (KNN). The selected algorithms were applied individually on different datasets. Subsequently, an ensemble model was created using the stacking method to collect all the predictions of the models then aggregate and use them as input features for the final classifier that is based on the Logistic Regression algorithm.
This study demonstrates the effectiveness of an ensemble approach for email spam detection by aggregating multiple weak machine learning algorithms to produce a strong machine learning model. The purpose of this research is to enhance the accuracy and robustness of the predictive model to detect spam emails. As a result, the proposed approach produced a better performance with 95.8% accuracy
ACTIVITIES TAILORING WITHIN AGILE SCRUM ROLES: A CASE OF NIGERIAN HEALTHCARE INFORMATION SYSTEMS DEVELOPMENT
Get PDFDeveloping quality agile healthcare information systems requires understanding regulatory compliance and evolving healthcare needs through activities tailored within agile scrum roles. Agile scrum, a widely adopted philosophy, offers significant advantages in managing software development processes. This research explores how activities within the agile scrum roles are tailored to agile healthcare information systems development within the Nigerian context. This study adopted a qualitative case study methodology and interviewed 12 agile practitioners developing healthcare information systems within Nigeria using semi-structured open-ended interview guide questions. The practitioners were selected based on a snowballing process, a sunset of purposive sampling techniques from our network of experts. In this study, we used the data analysis techniques informed by the grounded theory, which includes open coding constant comparison, memoing, and theoretical saturation to analyse the data. We identified 33 tailored activities performed by the scrum roles comprising product owner, scrum master and self-organising development team. The activities include adherence to medical regulatory standards, clinical quality assurance testing, documentation, and healthcare knowledge sharing, which are specific for developing quality agile healthcare information systems in the Nigerian context. We systematically mapped the practices into four high-level memos that comprise Activities Tailoring for Healthcare Information Systems Development, Tailoring Activities Within the Product Owner’s Roles, Tailoring Activities within the Scrum Master’s Roles, and Tailoring Activities within the Self-organising Team Role, which are the descriptive theory emerged from the grounded theory conceptual data analysis process. Our primary contribution to this research is a detailed account of 33 tailored activities within Scrum roles and the memos presented, which are necessary for developing quality agile healthcare information systems software. Agile practitioners need more tailoring skills and adequate resources, local regulatory standards, data security infrastructures, and support from the government to deal with technical debt and issues with nonfunctional requirements
