Selecting a college or university: A study of students and their parents

This case study investigated the decision-making process of high-achieving high school students and their parents in selecting a college or university. The conceptual framework that guided this study included theoretical and empirical research framed around a three-phase model of college choice. Parental influence dominated the first phase of this model. The search phase, which was the second and the most crucial one, included financial considerations related to this decision, admissions considerations during the search phase, the psychology of decision making, and advertising strategies for teenagers. Once students completed the search phase they developed expectations of the institutions they considered prior to making the final decision. The study employed qualitative methods using individual interviews with students and their parents. ^ Six high-achieving high school seniors from a South Florida high school and their parents were selected to participate in this study. Of these students, four were female and two were male. Participants were individually interviewed on two separate occasions over a three-month period. Students and their parents were interviewed separately, with one exception, during the first set of interviews and together during the second. The data obtained from these interviews were transcribed and these transcripts were coded, categorized, analyzed, and sorted into major themes and submitted to interpretive analysis. ^ In-depth descriptions of participants' experiences during the decision-making process are described in the study. Financial factors—which included the cost of college, the socio-economic status of the family, and scholarship possibilities—drove the selection process for these students and their parents, most of whom reported their family incomes between the lower-middle to upper-middle class range. All of these students took advantage of the Bright Futures Scholarship Program, other scholarship opportunities, and the lower tuition costs of in-state public institutions. The effectiveness of recruitment techniques, such as brochures, campus visits, the development of college Web sites, and the overall impact of Internet resources, was assessed by the researcher. ^ As these students had progressed through the search phase, they developed perceptions of potential institutions as they were assisted by those around them. The value of familiarity with institutions and the use of heuristics were quite evident in the final analysis of this study, based on what the students communicated about how their knowledge of and comfort in these institutions affected their decisions. Parental influence played an important role in the selection process for the students in this study as the parents clearly directed the process, by the constant advice they gave their children and by the financial limitations they communicated to them. ^

Optimization models for selecting bus stops for accessibility improvements for people with disabilities

Bus stops are key links in the journeys of transit patrons with disabilities. Inaccessible bus stops prevent people with disabilities from using fixed-route bus services, thus limiting their mobility. The Americans with Disabilities Act (ADA) of 1990 prescribes the minimum requirements for bus stop accessibility by riders with disabilities. Due to limited budgets, transit agencies can only select a limited number of bus stop locations for ADA improvements annually. These locations should preferably be selected such that they maximize the overall benefits to patrons with disabilities. In addition, transit agencies may also choose to implement the universal design paradigm, which involves higher design standards than current ADA requirements and can provide amenities that are useful for all riders, like shelters and lighting. Many factors can affect the decision to improve a bus stop, including rider-based aspects like the number of riders with disabilities, total ridership, customer complaints, accidents, deployment costs, as well as locational aspects like the location of employment centers, schools, shopping areas, and so on. These interlacing factors make it difficult to identify optimum improvement locations without the aid of an optimization model. This dissertation proposes two integer programming models to help identify a priority list of bus stops for accessibility improvements. The first is a binary integer programming model designed to identify bus stops that need improvements to meet the minimum ADA requirements. The second involves a multi-objective nonlinear mixed integer programming model that attempts to achieve an optimal compromise among the two accessibility design standards. Geographic Information System (GIS) techniques were used extensively to both prepare the model input and examine the model output. An analytic hierarchy process (AHP) was applied to combine all of the factors affecting the benefits to patrons with disabilities. An extensive sensitivity analysis was performed to assess the reasonableness of the model outputs in response to changes in model constraints. Based on a case study using data from Broward County Transit (BCT) in Florida, the models were found to produce a list of bus stops that upon close examination were determined to be highly logical. Compared to traditional approaches using staff experience, requests from elected officials, customer complaints, etc., these optimization models offer a more objective and efficient platform on which to make bus stop improvement suggestions.

Relative importance of false positives in the selection process

This study investigated the role of contextual factors in personnel selection. Specifically, I explored if specific job factors such as the wage, training, available applicant pool and security concerns around a job, influenced personnel decisions. Additionally, I explored if the individual differences of decision makers played a role in how the previously mentioned job factors affected their decisions. A policy-capturing methodology was employed to determine the weight participants place on the job factors when selecting candidates for different jobs. Regression and correlational analyses were computed with the beta weights obtained from individual regression analyses. The results obtained from the two samples (student and general population) revealed that specific job characteristics did indeed influence personnel decisions. Participants were more concerned with making mistakes and thus less likely to accept candidates when selecting candidates for jobs having high salary and/or high training requirements.