Effects of Computer Assisted Instruction and PCLogo Programs on Math Performance of Seventh and Eighth Grade Students with Learning Disabilities

The purpose of the study was to investigate the effects of computer assisted instruction and Logo programming on the math performance of seventh and eighth grade students with learning disabilities. The sample included thirty (N=30) subjects with learning disabilities. The computer programs used were Deluxe Math Munchers and LOGO for Windows. A three group pretest-posttest experimental design was used to determine if a relationship existed between the three different methods of instruction and achievement, and whether or not a significant difference existed in performance based on grade levels. The 30 subjects were randomly assigned to one of three groups, two experimental groups and one control group. The subjects were pre- and post-tested using the KeyMath revised. A two-way analysis of variance and a one-way analysis of variance showed significant effects on math performance between computer assisted instruction and traditional math instruction as well as between Logo programming instruction and traditional math instruction. The results showed no significant effects between math performance based on grade . Sample size and length of study were limitations of the study . Recommendations include future research using subjects matched on math performance, age, IQ, and the number of years of learning disabilities services

Thermobarometric studies on the Levack Gneisses: Footwall rocks to the Sudbury Igneous Complex

Granulite and amphibolite facies gneisses and migmatites of the Levack Gneiss Complex occupy a zone up to 8 km wide around the northern part of the Sudbury Igneous Complex (SIC). Orthopyroxene- and garnet-bearing tonalitic and semipelitic assemblages of granulite facies grade occur within 3 km of the SIC together with lenses of mafic and pyroxenitic rock compositions normally represented by an amphibole +/- cpx-rich assemblage; amphibolite facies assemblages dominate elsewhere in this terrain. These 2.711-Ga gneisses were introduced by (1) the Cartier Granite Batholith during late Archaean to early Proterozoic time and (2) the SIC, at 1.85 Ga, which produced a contact aureole 1-1.5 km wide in which pyroxene hornfelses are common within 200-300 m of the contact. A suite of 12 samples including both the opx-gt and amphibole-rich rock compositions have been studied. Garnets in the semipelitic gneisses are variably replaced by a plg-bio assemblage. Thermobarometric calculations using a variety of barometers and thermometers reported in the literature suggest that the granulite facies assemblages formed at depths in the 21-28 km range (6-8 kbar). Textures and mineral chemistry in the garnet-bearing semipelitic rocks indicate that this terrain underwent a second metamorphic event during uplift to depth in the 5-11 km range (2-3 kbar) and at temperatures as low as 500-550 C. This latter event is distinct from thermal recrystallization caused by the emplacement of the SIC; it probably represents metamorphism attributable to intrusion of the Cartier Granite Batholith. These data allow two interpretations for the crustal uplift of the Levack Gneisses: (1) The gneisses were tectonically uplifted prior to the Sudbury Event (due to intrusion of the Cartier Batholith); or (2) the gneisses were raised to epizonal levels as a result of meteorite impact at 1.85 Ga

Frugal Innovation: Core Competencies to Address Global Sustainability

The call for global sustainability is echoed by societal, environmental, and economic needs across the globe. In answering this call, a design innovation process that properly considers the needs and context of citizens in the developing world is necessary in order to develop appropriate, adaptable, affordable, and accessible solutions, products and services. This process, called “Frugal Innovation,” is rapidly becoming a standard against which sustainable solutions are assessed. Through an exploration of Frugal Innovation Core Competencies (Frugal Innovation Lab, Santa Clara University), and corresponding case studies of field solutions, a model is presented to begin sustainably addressing global human needs

Novel pathogen introduction rapidly alters the evolution of movement, restructuring animal societies

Animal social interactions are the outcomes of evolved strategies that integrate the costs and benefits of being sociable. Using a novel mechanistic, evolutionary, individual-based simulation model, we examine how animals balance the risk of pathogen transmission against the benefits of social information about resource patches, and how this determines the emergent structure of spatial social networks. We study a scenario in which a fitness-reducing infectious pathogen is introduced into a population which has initially evolved movement rules in its absence. Pathogen introduction leads to a rapid evolutionary shift, within only a few generations, in animal social-movement strategies. Generally, animals adopt a dynamic social distancing behaviour, trading more movement away from individuals (and less intake) for lower infection risk, but there is considerable individual variation in these social movement strategies. Pathogen-adapted populations are more widely dispersed over the landscape, and thus have lessclustered social networks than their pre-introduction, pathogen-naive ancestors. Running simple epidemiological models on these emergent social networks, we show that diseases do indeed spread more slowly through pathogen-adapted animal societies. The post-introduction, pathogen-adapted movement strategy mix is stongly influenced by a combination of landscape productivity and diseasecost. Our model suggests how the introduction of an infectious pathogen to a population rapidly changes social structure. While such events might make populations more resilient to future disease outbreaks, this is at the cost of social information benefits. Overall, we offer both a general modelling framework and initial predictions for the evolutionary consequences of wildlife pathogen spillovers

Zero-variance principle for Monte Carlo algorithms

We present a general approach to greatly increase at little cost the efficiency of Monte Carlo algorithms. To each observable to be computed we associate a renormalized observable (improved estimator) having the same average but a different variance. By writing down the zero-variance condition a fundamental equation determining the optimal choice for the renormalized observable is derived (zero-variance principle for each observable separately). We show, with several examples including classical and quantum Monte Carlo calculations, that the method can be very powerful.Comment: 9 pages, Latex, to appear in Phys. Rev. Let