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Item statistics derived from three-option versions of multiple-choice questions are usually as robust as four- or five-option versions: implications for exam design.
Different versions of multiple-choice exams were administered to an undergraduate class in human physiology as part of normal testing in the classroom. The goal was to evaluate whether the number of options (possible answers) per question influenced the effectiveness of this assessment. Three exams (each with three versions) were given to each of two sections during an academic quarter. All versions were equally long, with 30 questions: 10 questions with 3 options, 10 questions with 4, and 10 questions with 5 (always one correct answer plus distractors). Each question appeared in all three versions of an exam, with a different number of options in each version (three, four, or five). Discrimination (point biserial and upper-lower discrimination indexes) and difficulty were evaluated for each question. There was a small increase in difficulty (a lower average score on a question) when more options were provided. The upper-lower discrimination index indicated a small improvement in assessment of student learning with more options, although the point biserial did not. The total length of a question (number of words) was associated with a small increase in discrimination and difficulty, independent of the number of options. Quantitative questions were more likely to show an increase in discrimination with more options than nonquantitative questions, but this effect was very small. Therefore, for these testing conditions, there appears to be little advantage in providing more than three options per multiple-choice question, and there are disadvantages, such as needing more time for an exam
Globalization and land-use transitions in Latin America
Current socioeconomic drivers of land-use change associated with globalization are producing two contrasting land-use trends in Latin America. Increasing global food demand (particularly in Southeast Asia) accelerates deforestation in areas suitable for modern agriculture (e.g., soybean), severely threatening ecosystems, such as Amazonian rain forests, dry forests, and subtropical grasslands. Additionally, in the coming decades, demand for biofuels may become an emerging threat. In contrast, high yields in modern agricultural systems and rural–urban migration coupled with remittances promote the abandonment of marginal agricultural lands, thus favoring ecosystem recovery on mountains, deserts, and areas of poor soils, while improving human well-being. The potential switch from production in traditional extensive grazing areas to intensive modern agriculture provides opportunities to significantly increase food production while sparing land for nature conservation. This combination of emerging threats and opportunities requires changes in the way the conservation of Latin American ecosystems is approached. Land-use efficiency should be analyzed beyond the local-based paradigm that drives most conservation programs, and focus on large geographic scales involving long-distance fluxes of products, information, and people in order to maximize both agricultural production and the conservation of environmental services.Fil: Grau, Hector Ricardo. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - Tucumán; ArgentinaFil: Mitchell, Aide. Universidad de Puerto Rico; Puerto Ric
Annual Report of the Iowa Citizen's Aide/Ombudsman, 2011
Annual report for the Iowa Citizen's Aide/Ombudsman Office
Executive Order, August 31, 1935
Appointment of an Aide on the Military Staff of the Commander-in-Chief, Iowa National Guar
DoPAMINE: Double-sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling
We propose DoPAMINE, a new neural network based multiplicative noise
despeckling algorithm. Our algorithm is inspired by Neural AIDE (N-AIDE), which
is a recently proposed neural adaptive image denoiser. While the original
N-AIDE was designed for the additive noise case, we show that the same
framework, i.e., adaptively learning a network for pixel-wise affine denoisers
by minimizing an unbiased estimate of MSE, can be applied to the multiplicative
noise case as well. Moreover, we derive a double-sided masked CNN architecture
which can control the variance of the activation values in each layer and
converge fast to high denoising performance during supervised training. In the
experimental results, we show our DoPAMINE possesses high adaptivity via
fine-tuning the network parameters based on the given noisy image and achieves
significantly better despeckling results compared to SAR-DRN, a
state-of-the-art CNN-based algorithm.Comment: AAAI 2019 Camera Ready Versio
Executive Order, August 16, 1933
Appointment made of an Aide to the Military Staff of the Commander-in-Chief, Iowa National Guar
Lanthanide Soil Chemistry and Its Importance in Understanding Soil Pathways: Mobility, Plant Uptake, and Soil Health
The lanthanide elements or rare earth elements (REEs) are an active soil science research area, given their usage as micro-fertilizers, documented cases of environmental impact attributed to industry/mining, and their ability to identify lithologic discontinuities and reveal active soil processes. To fully understand REEs requires an understanding of their chemical reactivity, both for the individual elements and their behavior as a group of elements. The elements of the lanthanide series, including La and Y, may have subtle to very perceptible chemical differences that when viewed collectively reveal information that gives emphasis to soil processes that clarify soil behavior or soil genesis. This chapter concentrates on lanthanide soil chemistry and shows how the soil chemistry of REEs may support soil science investigations
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