Extra-curricular activities in secondary schools

Thesis (M.A.)--Boston Universit

Caught In the Middle: The Challenge of Middle Level Education

There is widespread evidence that a mismatch exists between what middle level schools offer and what 10 to 14 year olds need. More and more of these “early adolescents” are experimenting with drugs and alcohol, becoming pregnant, and dropping out. These issues and the increased incidents of violence at this age cause many parents to view with anxiety their children\u27s transition from the relatively safe elementary school to the unknown, often maligned middle or junior high school. Prospective teachers most often choose not to work in the middle grades because they don’t think they can work with “those kids”. Who are these 10 to 14 year old kids that are caught in the middle, no longer children, but not yet adults? Providing educational programs that best serve their needs is the challenge of middle level education toda

Applying coupon-collecting theory to computer-aided assessments

Computer-based tests with randomly generated questions allow a large number of different tests to be generated. Given a fixed number of alternatives for each question, the number of tests that need to be generated before all possible questions have appeared is surprisingly low.Comment: 19 pages; bibliographic information added as follows. To appear in Bingham, N. H., and Goldie, C. M. (eds), Probability and Mathematical Genetics: Papers in Honour of Sir John Kingman. London Math. Soc. Lecture Note Series. Cambridge: Cambridge Univ. Pres

How Sublime (and Prolific) was Byron? What the Reviewers Said

Cet article propose un survol des livres, des articles et des critiques (et lettres) écrits sur Lord Byron et son oeuvre de son vivant et peu de temps après sa mort, soit de 1807 à 1830 environ, de sorte à déterminer à quel point les contemporains de Byron le trouvaient « sublime ». Walter Scott, en faisant le compte rendu de Childe Harold 4, affirmait avec enthousiasme qu’il s’agissait de « la poésie la plus sublime », mais d’autres, comme William Hazlitt, étaient d’avis que « l’auteur de Childe Harold et de Don Juan est… un poseur, encore qu’il soit provoquant et sublime ». En parlant de Don Juan, John Wilson Croker s’exclamait quant à lui : « Quelle sublimité! quelle légèreté! quelle audace! quelle tendresse! quelle majesté! quelle insignifiance! quelle variété! quel ennui!1 ». Ma discussion sur un grand nombre de ces jugements sur l’oeuvre de Byron par ses contemporains nous permettra de determiner si le terme « sublime » définit adéquatement l’esprit de la poésie de Byron, surtout ce « sublime » tel qu’il a été compris par Longin, Burke et d’autres

Determining the Mechanism of Yield Stability in Alfalfa

Year-to-year stability of crop yields is important for farmers and, hence, is an important goal of plant breeding programs. Especially in perennial crops like alfalfa, farmers need to know that they can count on consistent yields over a period of three or more years. Alfalfa varieties are composed of a population of many genetically distinct plants (or genotypes), unlike corn hybrids or soybean lines, which are genetically uniform

Informed selection of future climates

Analysis of climate change is often computationally burdensome. Here, we present an approach for intelligently selecting a sample of climates from a population of 6800 climates designed to represent the full distribution of likely climate outcomes out to 2050 for the Zambeze River Valley. Philosophically, our approach draws upon information theory. Technically, our approach draws upon the numerical integration literature and recent applications of Gaussian quadrature sampling. In our approach, future climates in the Zambeze River Valley are summarized in 12 variables. Weighted Gaussian quadrature samples containing approximately 400 climates are then obtained using the information from these 12 variables. Specifically, the moments of the 12 summary variables in the samples, out to order three, are obliged to equal (or be close to) the moments of the population of 6800 climates. Runoff in the Zambeze River Valley is then estimated for 2026 to 2050 using the CliRun model for all 6800 climates. It is then straightforward to compare the properties of various subsamples. Based on a root of mean square error (RMSE) criteria, the Gaussian quadrature samples substantially outperform random samples of the same size in the prediction of annual average runoff from 2026 to 2050. Relative to random samples, Gaussian quadrature samples tend to perform best when climate change effects are stronger. We conclude that, when properly employed, Gaussian quadrature samples provide an efficient and tractable way to treat climate uncertainty in biophysical and economic models. This article is part of a Special Issue on “Climate Change and the Zambezi River Valley” edited by Finn Tarp, James Juana, and Philip War

Informed selection of future climates

Analysis of climate change is often computationally burdensome. Here, we present an approach for intelligently selecting a sample of climates from a population of 6800 climates designed to represent the full distribution of likely climate outcomes out to 2050 for the Zambeze River Valley. Philosophically, our approach draws upon information theory. Technically, our approach draws upon the numerical integration literature and recent applications of Gaussian quadrature sampling. In our approach, future climates in the Zambeze River Valley are summarized in 12 variables. Weighted Gaussian quadrature samples containing approximately 400 climates are then obtained using the information from these 12 variables. Specifically, the moments of the 12 summary variables in the samples, out to order three, are obliged to equal (or be close to) the moments of the population of 6800 climates. Runoff in the Zambeze River Valley is then estimated for 2026 to 2050 using the CliRun model for all 6800 climates. It is then straightforward to compare the properties of various subsamples. Based on a root of mean square error (RMSE) criteria, the Gaussian quadrature samples substantially outperform random samples of the same size in the prediction of annual average runoff from 2026 to 2050. Relative to random samples, Gaussian quadrature samples tend to perform best when climate change effects are stronger. We conclude that, when properly employed, Gaussian quadrature samples provide an efficient and tractable way to treat climate uncertainty in biophysical and economic models