RESUMEN
Researchers have long struggled to accurately identify the needs of English learner (EL) students and the factors that facilitate their postsecondary success. Although prior research suggests that EL students disproportionately select into community colleges, there is a dearth research that examines transfer to four-year schools among community college English learner (CCEL) students. In this study, we examined whether and to what extent community college students' linguistic status shapes the relationship between engagement and intent to transfer to a four-year institution. Using data from the Community College Survey of Student Engagement, we used logistic regression to examine how, if at all, the relationships between the multiple forms of student engagement and intent to transfer might differ by linguistic status, net of various student and school-level controls. Ultimately, our findings suggest that students' returns to engagement do differ by linguistic status, with CCEL students experiencing the greatest gains relative to their intent to transfer. Not only are CCEL students are more likely to engage in academic discourse, internalize teachers' pedagogical offerings, and recognize institutional supports than their non-CCEL peers, but they appear to derive greater benefits from both academic engagement and instruction in the use critical thinking skills than their non-CCEL peers. We conclude with recommendations for educators, policymakers, and researchers seeking to improve CCEL students' educational attainment and engagement.
RESUMEN
Objective: For many students, community college is a convenient first step toward a bachelor's degree. Yet, although more than 80% of those who enroll in community colleges intend to transfer to a 4-year institution, fewer than 35% do so within 6 years. Quantitative data reveal the presence of a transfer gap and there is extensive research on college choice for high school students, but little qualitative research has been done to examine the transfer process for community college students to identify what drives their decisions. Method: In this article, we draw on interviews with 58 community college students in Texas to examine how they made transfer decisions. Results: We find that their decision-making and transfer pathways were complex and nonlinear in ways that were particular to the uncertainty of the community college context. For a subset of students, we identify minor hurdles that could derail their decision-making, lengthen their timelines to transfer, or lead to a failure to transfer. Contribution: By illuminating student pathways to transfer using qualitative research, our work identifies potential areas where policy and practice could strengthen transfer to improve student outcomes.
RESUMEN
Broad higher education contexts shape how community college students and postsecondary personnel approach transfer from community colleges to baccalaureate-granting institutions. We leverage the concept of strategic action fields, an organizational theory illuminating processes that play out as actors determine "who gets what" in an existing power structure, to understand the role of political-ecological contexts in "vertical" transfer. Drawing on interviews with administrators, transfer services personnel, and transfer-intending students at two Texas community college districts and with administrators, admissions staff, and transfer personnel at public universities throughout the state, we examine how institutional actors and students create, maintain, and respond to rules and norms in the community college transfer field. Our results suggest university administrators, faculty, and staff hold dominant positions in the field, setting the rules and norms for credit transfer and applicability. Students, who hold the least privilege, must invest time and energy to gather information about transfer pathways and policies as their primary means of meeting their educational aspirations. The complex structure of information-wherein each institution provides its own transfer resources, with little collaboration and minimal alignment-systematically disadvantages community college students. Although some community college personnel voice frustration that the field disadvantages transfer-intending community college students, they maintain the social order by continuing to implement and reinforce the rules and norms set by universities.
RESUMEN
BACKGROUND: Acetaminophen (N-acetyl-para-aminophenol) is the most widely used over-the-counter or prescription painkiller in the world. Acetaminophen is metabolized in the liver where a toxic byproduct is produced that can be removed by conjugation with glutathione. Acetaminophen overdoses, either accidental or intentional, are the leading cause of acute liver failure in the United States, accounting for 56,000 emergency room visits per year. The standard treatment for overdose is N-acetyl-cysteine (NAC), which is given to stimulate the production of glutathione. METHODS: We have created a mathematical model for acetaminophen transport and metabolism including the following compartments: gut, plasma, liver, tissue, urine. In the liver compartment the metabolism of acetaminophen includes sulfation, glucoronidation, conjugation with glutathione, production of the toxic metabolite, and liver damage, taking biochemical parameters from the literature whenever possible. This model is then connected to a previously constructed model of glutathione metabolism. RESULTS: We show that our model accurately reproduces published clinical and experimental data on the dose-dependent time course of acetaminophen in the plasma, the accumulation of acetaminophen and its metabolites in the urine, and the depletion of glutathione caused by conjugation with the toxic product. We use the model to study the extent of liver damage caused by overdoses or by chronic use of therapeutic doses, and the effects of polymorphisms in glucoronidation enzymes. We use the model to study the depletion of glutathione and the effect of the size and timing of N-acetyl-cysteine doses given as an antidote. Our model accurately predicts patient death or recovery depending on size of APAP overdose and time of treatment. CONCLUSIONS: The mathematical model provides a new tool for studying the effects of various doses of acetaminophen on the liver metabolism of acetaminophen and glutathione. It can be used to study how the metabolism of acetaminophen depends on the expression level of liver enzymes. Finally, it can be used to predict patient metabolic and physiological responses to APAP doses and different NAC dosing strategies.