University Presidents\u27 Perspectives of the Knowledge and Competencies Needed in 21st Century Higher Education Leadership

The purpose of this study was to identify the core knowledge and competencies needed for executive leadership in higher education administration as perceived by university presidents. Thirteen presidents shared the knowledge and competencies they perceived as being essential for an effective presidency. The respondents identified the important knowledge areas as: foundational; acquisition of cultural knowledge; and complex cognitive. They viewed personal attributes, management, and communications as the essential competency areas. The study found that presidents viewed themselves both as leaders and as managers. Results of this study should be helpful to organizations seeking to develop and/or implement degree programs to prepare individuals for the presidency. The results may also be helpful to those seeking to provide professional development materials and activities to prepare or develop individuals for this role

Taking Control of What Counts in Accountability: The Context Enriched Report Card

During the last two decades concerns about the quality of education have resulted in widespread calls for educational improvement and reform in many nations

Gender Related Differences in Career Patterns of Principals in Alabama

The purpose of this research was to determine the status of women administrators in the Alabama in terms of demographic and career patterns. A survey was sent to all principals in Alabama. Five hundred-fifty, or 42% of the principals responded. In Alabama, women principals are generally more recent in their position, are somewhat more likely to have come directly from the classroom, and have less mobility in acquiring the position

Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology

Gould E, Fraser H, Parker T, et al. Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology. 2023.Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different (mostly social science) fields, and has found substantial variability among results, despite analysts having the same data and research question. We implemented an analogous study in ecology and evolutionary biology, fields in which there have been no empirical exploration of the variation in effect sizes or model predictions generated by the analytical decisions of different researchers. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment), and the project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future