17 resultados para interviewer effects, multi-level, random interviewer assignment, panel survey, political opinion
Resumo:
This dissertation is a multi-level, cross-cultural study of women in leadership conducted with both macro-society data and individual-level data aggregated to the country level. The research questions are, “What macro and micro forces are hindering or advancing women into business or political leadership?” “How do these forces impact the level of women’s involvement in business and political leadership in a particular country?” Data was collected from 10 secondary sources, available for 213 countries, and includes about 300 variables for business leadership (N=115) and political leadership (N=181). To date, most women in leadership research has been Western- or US- based, and little rigorous empirical, multi-level research has been done across countries. The importance of cross-cultural studies on women in leadership stems from the potential to better understand why some countries have more women in positions of both business and political leadership; and the factors that affect women’s involvement in such positions in different countries. A “Levels of Women’s Participation in Leadership” country model is tested using cluster and discriminant analyses. Results indicate that the factors that affect women’s participation in leadership in countries with fewer women leaders are different from the factors that affect women’s participation in countries with high levels of participation. This dissertation proposes that initiatives to increase participation of women in leadership need to consider the relevant factors that significantly affect countries at certain Levels of Women’s Participation in Leadership.
Resumo:
During the past decade, there has been a dramatic increase by postsecondary institutions in providing academic programs and course offerings in a multitude of formats and venues (Biemiller, 2009; Kucsera & Zimmaro, 2010; Lang, 2009; Mangan, 2008). Strategies pertaining to reapportionment of course-delivery seat time have been a major facet of these institutional initiatives; most notably, within many open-door 2-year colleges. Often, these enrollment-management decisions are driven by the desire to increase market-share, optimize the usage of finite facility capacity, and contain costs, especially during these economically turbulent times. So, while enrollments have surged to the point where nearly one in three 18-to-24 year-old U.S. undergraduates are community college students (Pew Research Center, 2009), graduation rates, on average, still remain distressingly low (Complete College America, 2011). Among the learning-theory constructs related to seat-time reapportionment efforts is the cognitive phenomenon commonly referred to as the spacing effect, the degree to which learning is enhanced by a series of shorter, separated sessions as opposed to fewer, more massed episodes. This ex post facto study explored whether seat time in a postsecondary developmental-level algebra course is significantly related to: course success; course-enrollment persistence; and, longitudinally, the time to successfully complete a general-education-level mathematics course. Hierarchical logistic regression and discrete-time survival analysis were used to perform a multi-level, multivariable analysis of a student cohort (N = 3,284) enrolled at a large, multi-campus, urban community college. The subjects were retrospectively tracked over a 2-year longitudinal period. The study found that students in long seat-time classes tended to withdraw earlier and more often than did their peers in short seat-time classes (p < .05). Additionally, a model comprised of nine statistically significant covariates (all with p-values less than .01) was constructed. However, no longitudinal seat-time group differences were detected nor was there sufficient statistical evidence to conclude that seat time was predictive of developmental-level course success. A principal aim of this study was to demonstrate—to educational leaders, researchers, and institutional-research/business-intelligence professionals—the advantages and computational practicability of survival analysis, an underused but more powerful way to investigate changes in students over time.