Understanding the gender and ethnicity attainment gap in UK higher education

In recent years the success rates of different groups of students in higher education (HE), have come under considerable scrutiny, with gender and ethnicity identified as key attributes predicting differential achievement of ‘good degrees’. A review of previous studies highlights the need for research which looks beyond ‘the deficit model’ to explain the attainment gap. This research used a mixed-methods approach to explore the academic and social experiences of students, as well as lecturers’ views on student achievement, in one UK University. Findings suggest that there are significant differences in motivation and confidence speaking English for different ethnic groups in this study, and a divergence in attendance and study time by gender – both of which may go some way to helping understand the gaps in attainment. In addition, male and BME students tended to over-estimate their likelihood of achieving a good degree outcome, compared to other groups

How Do Quantitative And Qualitative Factors Influence The Selection Of Comparable, Competitive, And Aspirant Groups Under The Proposed AACSB Accreditation Maintenance Process?

The AACSB Blue Ribbon Committee on Accreditation Quality was “formed to do a thorough review of AACSB International's accreditation standards and procedures and to propose changes appropriate for global quality leadership in the next decade...” Within the proposal from the Blue Ribbon Committee is a change from a reaffirmation process with a site visit every ten years to a maintenance program resulting in a team visit in the sixth year of the cycle. Under the old standards applicants were required to submit “to the appropriate accreditation committee chair, in care of the AACSB International office, five nominations for each team role; i.e., five names for chair, five names for advisor, five for member, and if accounting accreditation were applicable, five names for vice-chair and five names for accounting advisor.” The proposed standards include a team selection process whereby the “applicant submits three comparison groups selected from members of the Accreditation Council... AACSB International will develop an on-line system to assist the applicant to identify potential comparison schools, officially select schools for each comparison group, and continuously maintain comparison group listings in an AACSB International database. Some information is currently available. The on-line service, www.aacsb.edu/knowledgeservices, offers advanced search functions that produce institution lists based on optionally selected criteria.” This AACSB provided information as well as information from other sources constitutes the basis for the recommended comparison group selection process

A Regional Health Care System Partnership With Local Communities to Impact Chronic Disease

Regional health care systems have significant opportunities to adopt community-oriented approaches that impact the incidence and burden of chronic disease. In 1998, a vertically integrated, regional health care system established a community health institute to identify, understand, and respond to health needs from a community perspective. The project was implemented in four communities (two rural counties, a rural/urban transitional county, and an inner-city community) using five steps: 1) support or form a local community coalition; 2) hire and support a local coordinator; 3) prepare a formal community assessment; 4) fund locally designed interventions; and 5) evaluate each project. In four narrative case studies, we present the steps, challenges, and common principles faced at the local level by Carolinas Community Health Institute. The case studies were prepared using three data sources: reviews of written documents, interviews with the seven-member steering committee, and interviews with six key informants from each county. Data were coded and analyzed using standard qualitative software to identify common themes and sources of variance between cases. The project model was generally well accepted. Local autonomy and domain disputes were challenges in all four sites. Funding for local projects was the most frequently cited benefit. The project was successful in increasing local capacity and supporting well-designed interventions to prevent chronic disease. This approach can be used by large health care systems and by other organizations to better support local health initiatives

Maxent Estimation of Aquatic Escherichia Coli Stream Impairment

Background: The leading cause of surface water impairment in United States’ rivers and streams is pathogen contamination. Although use of fecal indicators has reduced human health risk, current approaches to identify and reduce exposure can be improved. One important knowledge gap within exposure assessment is characterization of complex fate and transport processes of fecal pollution. Novel modeling processes can inform watershed decision-making to improve exposure assessment. Methods: We used the ecological model, Maxent, and the fecal indicator bacterium Escherichia coli to identify environmental factors associated with surface water impairment. Samples were collected August, November, February, and May for 8 years on Sinking Creek in Northeast Tennessee and analyzed for 10 water quality parameters and E. coli concentrations. Univariate and multivariate models estimated probability of impairment given the water quality parameters. Model performance was assessed using area under the receiving operating characteristic (AUC) and prediction accuracy, defined as the model’s ability to predict both true positives (impairment) and true negatives (compliance). Univariate models generated action values, or environmental thresholds, to indicate potential E. coli impairment based on a single parameter. Multivariate models predicted probability of impairment given a suite of environmental variables, and jack-knife sensitivity analysis removed unresponsive variables to elicit a set of the most responsive parameters. Results: Water temperature univariate models performed best as indicated by AUC, but alkalinity models were the most accurate at correctly classifying impairment. Sensitivity analysis revealed that models were most sensitive to removal of specific conductance. Other sensitive variables included water temperature, dissolved oxygen, discharge, and NO3. The removal of dissolved oxygen improved model performance based on testing AUC, justifying development of two optimized multivariate models; a 5-variable model including all sensitive parameters, and a 4-variable model that excluded dissolved oxygen. Discussion: Results suggest that E. coli impairment in Sinking Creek is influenced by seasonality and agricultural run-off, stressing the need for multi-month sampling along a stream continuum. Although discharge was not predictive of E. coli impairment alone, its interactive effect stresses the importance of both flow dependent and independent processes associated with E. coli impairment. This research also highlights the interactions between nutrient and fecal pollution, a key consideration for watersheds with multiple synergistic impairments. Although one indicator cannot mimic the plethora of existing pathogens in water, incorporating modeling can fine tune an indicator’s utility, providing information concerning fate, transport, and source of fecal pollution while prioritizing resources and increasing confidence in decision making. Methods We used the ecological model, Maxent, and the fecal indicator bacterium Escherichia coli to identify environmental factors associated with surface water impairment. Samples were collected August, November, February, and May for 8 years on Sinking Creek in Northeast Tennessee and analyzed for 10 water quality parameters and E. coli concentrations. Univariate and multivariate models estimated probability of impairment given the water quality parameters. Model performance was assessed using area under the receiving operating characteristic (AUC) and prediction accuracy, defined as the model’s ability to predict both true positives (impairment) and true negatives (compliance). Univariate models generated action values, or environmental thresholds, to indicate potential E. coli impairment based on a single parameter. Multivariate models predicted probability of impairment given a suite of environmental variables, and jack-knife sensitivity analysis removed unresponsive variables to elicit a set of the most responsive parameters. Results Water temperature univariate models performed best as indicated by AUC, but alkalinity models were the most accurate at correctly classifying impairment. Sensitivity analysis revealed that models were most sensitive to removal of specific conductance. Other sensitive variables included water temperature, dissolved oxygen, discharge, and NO3. The removal of dissolved oxygen improved model performance based on testing AUC, justifying development of two optimized multivariate models; a 5-variable model including all sensitive parameters, and a 4-variable model that excluded dissolved oxygen. Discussion Results suggest that E. coli impairment in Sinking Creek is influenced by seasonality and agricultural run-off, stressing the need for multi-month sampling along a stream continuum. Although discharge was not predictive of E. coli impairment alone, its interactive effect stresses the importance of both flow dependent and independent processes associated with E. coli impairment. This research also highlights the interactions between nutrient and fecal pollution, a key consideration for watersheds with multiple synergistic impairments. Although one indicator cannot mimic theplethora of existing pathogens in water, incorporating modeling can fine tune an indicator’s utility, providing information concerning fate, transport, and source of fecal pollution while prioritizing resources and increasing confidence in decision making

Health Literacy Levels Among Adult Support Group Members and the General Adult Public : A Focus Group Approach

Health literacy has been identified as lacking in 47% of Americans (The National Academies, 2004). While health literacy reports of studies conducted in the southern section of the United States are available (DeWalt et al., 2004; Kennen et al. 2005), this research team found limited research that provides health literacy levels of the southeast, rural Georgia population. The purpose of this exploratory study was to examine and compare health literacy of health-related support group members and non group members in southeast Georgia utilizing a focus group methodology developed by Kreuger (1994). After Institutional Review Board approval at a local university, the research team utilized 5-10 established Health-related Support Groups of 6-10 individuals in the southeastern part of the United States. An additional four focus groups composed of persons not associated with a health-related support group were also used for comparative purposes. Participants were recruited with the assistance of local health care providers. The initial open-ended questions consisted of items such as: “Describe your experience reading health resources.” What makes a health resource difficult to read, as well as easy to read? The moderator utilized additional probing questions and reframing comments as necessary (Kreuger, 1994). The data were analyzed by the qualitative content analysis method described by Berg (1989). The themes that emerged across groups reflected confusion about medication directions, health terms, and communication from health care providers and doubt about the integrity of and inability to read the small print of health information. Prevention and faith in God were identified as important to self-care. Rationales for themes and future research ideas are discussed