The Current Status of Faculty Development Internationally

Excerpt: One of the valuable and exciting changes that have occurred in higher education in the last few decades is the steady growth in faculty development programs internationally. From the first programs that were established in the mid-part of the 20th century, there are now several countries where essentially all colleges and universities have such programs...

The Evaluation of College Teaching

There are few tasks at a university more important than the evaluation of teaching. Without it, professors themselves are unable to determine the direction of needed improvement and thereby become vulnerable to the process of stagnation. Without it, academic units are unable to identify and encourage professors who truly are effective in the classroom with their students

Building faculty capacity for better teaching and learning

Enhancing faculty capacity for teaching in ways that promote greater levels of student engagement and significant learning is an essential part of all other institutional changes designed to advance higher quality student learning. In this session, participants will lay out a general strategy for campus leaders to cultivate that faculty capability and then identify specific actions needed to implement such a strategy. Participants will also identify key elements of effective teaching and learning centers and brainstorm ways to build a teaching- and learning-centered institutional culture

Mapping information literacy outcomes and other intellectual skills into students\u27 educational experiences

The 2007 report, College Learning for the New Global Century, outlines a cluster of intellectual and practical skills that are critical components of a liberal education: inquiry and analysis; critical and creative thinking; written and oral communication; quantitative literacy; information literacy; and teamwork and problem solving. The learning outcomes associated with information literacy relate to and incorporate many of the learning outcomes in all of these skill clusters. Participants in this session will address how these information literacy and related learning outcomes can be mapped into student learning experiences at three levels: in an individual course, in an academic sequence (e.g., first-year, sophomore year, and capstone courses), and across the curriculum and co-curriculum. Participants will consider: Who is responsible for ensuring that information literacy learning outcomes are integrated into courses across the curriculum? How can campus experts in pedagogy, assessment, instructional technology, information literacy, and faculty development work together across their administrative silos

Seasonal forecasts of North Atlantic tropical cyclone activity in the North American Multi-Model Ensemble

The North American Multi-Model Ensemble (NMME)-Phase II models are evaluated in terms of their retrospective seasonal forecast skill of the North Atlantic (NA) tropical cyclone (TC) activity, with a focus on TC frequency. The TC identification and tracking algorithm is modified to accommodate model data at daily resolution. It is also applied to three reanalysis products at the spatial and temporal resolution of the NMME-Phase II ensemble to allow for a more objective estimation of forecast skill. When used with the reanalysis data, the TC tracking generates realistic climatological distributions of the NA TC formation and tracks, and represents the interannual variability of the NA TC frequency quite well. Forecasts with the multi-model ensemble (MME) when initialized in April and later tend to have skill in predicting the NA seasonal TC counts (and TC days). At longer leads, the skill is low or marginal, although one of the models produces skillful forecasts when initialized as early as January and February. At short lead times, while demonstrating the highest skill levels the MME also tends to significantly outperform the individual models and attain skill comparable to the reanalysis. In addition, the short-lead MME forecasts are quite reliable. At regional scales, the skill is rather limited and mostly present in the western tropical NA and the Caribbean Sea. It is found that the overall MME forecast skill is limited by poor representation of the low-frequency variability in the predicted TC frequency, and large fluctuations in skill on decadal time scales. Addressing these deficiencies is thought to increase the value of the NMME ensemble in providing operational guidance

The West African Monsoon Onset: a concise comparison of definitions

The onset of the West African Monsoon (WAM) marks a vital time for local and regional stakeholders. Whilst the seasonal progression of monsoon winds and the related migration of precipitation from the Guinea Coast towards the Soudan/Sahel is apparent, there exist contrasting man-made definitions of what the WAM onset means. Broadly speaking, onset can be analyzed regionally, locally or over a designated intermediate scale. There are at least eighteen distinct definitions of the WAM onset in publication with little work done on comparing observed onset from different definitions or comparing onset realizations across different datasets and resolutions. Here, nine definitions have been calculated using multiple datasets of different metrics at different resolution. It is found that mean regional onset dates are consistent across multiple datasets and different definitions. There is low inter-annual variability in regional onset suggesting that regional seasonal forecasting of the onset provides few benefits over climatology. In contrast, local onsets show high spatial, inter-annual and inter-definition variability. Furthermore it is found that there is little correlation between local onset dates and regional onset dates across West Africa implying a disharmony between regional measures of onset and the experience on a local scale. The results of this study show that evaluation of seasonal monsoon onset forecasts is far from straightforward. Given a seasonal forecasting model, it is possible to simultaneously have a good and bad prediction of monsoon onset simply through selection of onset definition and observational dataset used for comparison