A study of teachers\u27 perceptions about staff development factors and their classroom implementation of reform-based science instruction

The purpose of this study was two-fold: (1) to determine whether or not there were significant differences in implementation levels of reform-based science instructional strategies by teachers who participated in an established staff development program, Project LIFE and those who did not, and (2) to distinguish specific program factors that may have impacted the level of implementation of reform-based instructional classroom practices. The instrument used, the Survey of Reform-Based Science Teaching Strategies (SRBSTS ), was developed by the researcher and had reliability of .912 as measured by Cronbach Alpha. An independent samples t-test analysis was used to compare the implementation levels of a random sample (n = 40) of Project LIFE teachers and a control group of non-Project LIFE teachers (n = 34). The random sample (n = 40) was drawn from the experimental group (n = 148) which included former teacher participants (from seven different summer programs and follow-up years, 1992–1998) who responded to the mail-in survey. All respondents reported on Likert-type scale inventories about their estimated percentage of time spent on reform and non-reform-based science instructional practices. Additionally the experimental group responded to 40 Likert-type scale items about their perceptions of five staff development program components. A stepwise multiple regression analysis between the dependent variable, levels of implementation, and the independent variables, five program components, determined that positive levels of implementation could be predicted ( p = .05) by only one program component, the participant\u27s favorable perception of the program\u27s core values (i.e. belief that reform methodologies offer the best way to help students learn science). Perceptions about the initial training experience, program follow-up, program support, and school/district support showed no significant correlation. The study concluded that the Project LIFE teachers showed significantly higher positive levels of reform-based instructional practices, and that their positive perceptions about the value of the staff development program objectives is the single-most important factor influencing post-training practices. These findings are important in enhancing national science reform goals because they contribute to an understanding of which factors in staff development programs for practicing teachers most contribute to transfer of training

3D Feature Extraction for Unstructured Grids

Visualization techniques provide tools that help scientists identify observed phenomena in scientific simulation. To be useful, these tools must allow the user to extract regions, classify and visualize them, abstract them for simplified representations, and track their evolution. Object Segmentation provides a technique to extract and quantify regions of interest within these massive datasets. This article explores basic algorithms to extract coherent amorphous regions from two-dimensional and three-dimensional scalar unstructured grids. The techniques are applied to datasets from Computational Fluid Dynamics and those from Finite Element Analysis

Applied computational geometry: Towards robust solutions of basic problems

AbstractGeometric computations, like all numerical procedures, are extremely prone to roundoff error. However, virtually none of the numerical analysis literature directly applies to geometric calculations. Even for line intersection, the most basic geometric operation, there is no robust and efficient algorithm. Compounding the difficulties, many geometric algorithms perform iterations of calculations reusing previously computed data. In this paper, we explore some of the main issues in geometric computations and the methods that have been proposed to handle roundoff errors. In particular, we focus on one method and apply it to a general iterative intersection problem. Our initial results seem promising and will hopefully lead to robust solutions for more complex problems of applied computational geometry

Ray Casting Architectures for Volume Visualization

Real-time visualization of large volume datasets demands high performance computation, pushing the storage, processing, and data communication requirements to the limits of current technology. General purpose parallel processors have been used to visualize moderate size datasets at interactive frame rates; however, the cost and size of these supercomputers inhibits the widespread use for real-time visualization. This paper surveys several special purpose architectures that seek to render volumes at interactive rates. These specialized visualization accelerators have cost, performance, and size advantages over parallel processors. All architectures implement ray casting using parallel and pipelined hardware. We introduce a new metric that normalizes performance to compare these architectures. The architectures included in this survey are VOGUE, VIRIM, Array Based Ray Casting, EM-Cube, and VIZARD II. We also discuss future applications of special purpose accelerators.Engineering and Applied Science

A Bounded Measure for Estimating the Benefit of Visualization: Case Studies and Empirical Evaluation

Many visual representations, such as volume-rendered images and metro maps, feature a noticeable amount of information loss. At a glance, there seem to be numerous opportunities for viewers to misinterpret the data being visualized, hence undermining the benefits of these visual representations. In practice, there is little doubt that these visual representations are useful. The recently-proposed information-theoretic measure for analyzing the cost-benefit ratio of visualization processes can explain such usefulness experienced in practice, and postulate that the viewers' knowledge can reduce the potential distortion (e.g., misinterpretation) due to information loss. This suggests that viewers' knowledge can be estimated by comparing the potential distortion without any knowledge and the actual distortion with some knowledge. In this paper, we describe several case studies for collecting instances that can (i) support the evaluation of several candidate measures for estimating the potential distortion distortion in visualization, and (ii) demonstrate their applicability in practical scenarios. Because the theoretical discourse on choosing an appropriate bounded measure for estimating the potential distortion is yet conclusive, it is the real world data about visualization further informs the selection of a bounded measure, providing practical evidence to aid a theoretical conclusion. Meanwhile, once we can measure the potential distortion in a bounded manner, we can interpret the numerical values characterizing the benefit of visualization more intuitively.Comment: Following the SciVis 2020 reviewers' request for more explanation and clarification, the origianl article, "A Bounded Measure for Estimating the Benefit of Visualization, arxiv:2002.05282", has been split into two articles, on "Theoretical Discourse and Conceptual Evaluation" and "Case Studies and Empirical Evaluation" respectively. This is the second articl

Drexel University

We present a 3D matching framework based on a many-to-many matching algorithm that works with skeletal representations of 3D volumetric objects. We demonstrate the performance of this approach on a large database of 3D objects containing more than 1000 exemplars. The method is especially suited to matching objects with distinct part structure and is invariant to part articulation. Skeletal matching has an intuitive quality that helps in defining the search and visualizing the results. In particular, the matching algorithm produces a direct correspondence between two skeletons and their parts, which can be used for registration and juxtaposition. 1

Prescription and Other Medication Use in Pregnancy

OBJECTIVE: To characterize prescription and other medication use in a geographically and ethnically diverse cohort of women in their first pregnancy. METHODS: In a prospective, longitudinal cohort study of nulliparous women followed through pregnancy from the first trimester, medication use was chronicled longitudinally throughout pregnancy. Structured questions and aids were used to capture all medications taken as well as reasons they were taken. Total counts of all medications taken including number in each category and class were captured. Additionally, reasons the medications were taken were recorded. Trends in medications taken across pregnancy and in the first trimester were determined. RESULTS: Of the 9,546 study participants, 9,272 (97.1%) women took at least one medication during pregnancy with 9,139 (95.7%) taking a medication in the first trimester. Polypharmacy, defined as taking at least five medications, occurred in 2,915 (30.5%) women. Excluding vitamins, supplements, and vaccines, 73.4% of women took a medication during pregnancy with 55.1% taking one in the first trimester. The categories of drugs taken in pregnancy and in the first trimester include the following: gastrointestinal or antiemetic agents (34.3%, 19.5%), antibiotics (25.5%, 12.6%), and analgesics (23.7%, 15.6%, which includes 3.6%; 1.4% taking an opioid pain medication). CONCLUSION: In this geographically and ethnically diverse cohort of nulliparous pregnant women, medication use was nearly universal and polypharmacy was common