2,111 research outputs found

    Mars Mysteries: Landform Pictograms

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    Graphic organizers are a way for teachers to accommodate students with disabilities such as poor memory or emotional disorders. This technique allows organization of thoughts and visual representation of relationships between ideas and facts. Indeed, poor memory affects students’ reflection and retention of information while emotional disorders can cause a lack of focus in the classroom. Accommodations for students with these disabilities is important because students with emotional disorders may experience social isolation, which in turn may negatively affect their levels of academic achievement. Twenty high-achieving doctoral students participated in a teaching experience designed to introduce gifted students with learning disabilities to using de Bono thinking skills to mediate the possible negative effects of the disabilities through an arts-integrated project focused on some of the mysteries of the planet Mars. The results of this practical lesson showed that the students used their previous experiences in most cases to interpret the different photographs presented. Graphic organizers helped them organize their thought processes and the learning experience. Instruction needs to be woven tightly with the use of interactive materials and graphic organizers

    Promoting Interdisciplinary Practice: An Interview With Steven R. Forness

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    As part of an ongoing oral history project, a conversation was held with Dr. Stephen Forness on the past, present, and possible future of the field of providing services to children with emotional-behavioral disorders. Dr. Forness stresses the increasing importance of providing an interdisciplinary approach to meeting these needs

    Model evidence links (MELs) and the impact of critical thinking on open ended responses

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    The purpose of this dissertation, which was conducted in a rural school district that is equidistant from three major urban areas in central Iowa, and employed an action research methodology, was to examine the relationship between graphic organizer use and critical thinking. A multitude of studies have provided evidence that graphic organizers aid in the recall and understanding of basic facts in the lower grade levels; however, little research exists that supports a connection between graphic organizer use and the ability of students to recall information used on open-ended critical thinking assessments or the ability to create what Bickel and Lombardi (2016) call “causal connections” with content material. This study examined a research-based method that can deliver consistent results in growing students’ understanding of social studies content, while allowing students to interrogate content and demonstrate knowledge of critical thinking skills through an open-ended written response. This dissertation was based on an action research methodology in which the researcher conducted the dissertation within his secondary social studies classroom. The students who participated in this study were members of two different courses, divided into two sections of each course according to their class schedule determined by the high school counselor. Students were engaged in instruction using research based instructional methods, in coordination with the three, twenty minute blocks per week of direct MEL instruction. Students were measured on growth in critical thinking skills on open-ended critical thinking writing prompts. The growth of students measured using a rubric, allowed for isolation of specific critical thinking skills that were specifically targeted with MEL usage and instruction. These results suggest that MELs are an effective tool for promoting critical thinking and potentially other higher levels of learning. The positive impact of MELs, may be found in multiple subject areas including social studies. Implications for incorporating the use of MELs into classroom instruction are discussed, as well as broader theoretical implications for critical thinking that involves cognitive models and evidence

    A Serious Gaming Approach For Serious Stakeholder Participation

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    Serious games are a category of games which are designed for a specific purpose other than for pure entertainment. It is not a new concept but serious games using real data, coupled with real time modelling and combining model results with social and economic factors opens up a new paradigm for active stakeholder participation. DHI and UNEP-DHI Centre initiated a project called Aqua Republica where a virtual world is developed which allows participants to develop a river basin and visualise the consequences of their decisions. The aim of this project is to raise awareness of the interconnectivity of water and educate on integrated water resources management. Aqua Republica combines a game layer with a water allocation model, MIKE BASIN, to create an interactive, realistic virtual environment where players play the role of a catchment manager of an undeveloped river catchment. Their main objective is to develop the river catchment to be as prosperous as it can be. To achieve that, they will need to generate a good economy in the catchment to provide the funds needed for development, have a steady food supply for their population and enough energy and water for the catchment. Through these actions by the player, a meaningful play is established to engage players and to educate them about the complex relationships between developmental actions in a river basin and the natural environment as well as their consequences. The game layer also consists of a reward system to encourage learning. People can play and replay the game, get rewarded from performing the right principles and penalised from failures in the game. This abstract will explain the concept of the game and how it has been used in a stakeholder participation environment

    Survival and Selection of Migrating Salmon from Capture-Recapture Models with Individual Traits

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    Capture–recapture studies are powerful tools for studying animal population dynamics, providing information on population abundance, survival rates, population growth rates, and selection for phenotypic traits. In these studies, the probability of observing a tagged individual reflects both the probability of the individual surviving to the time of recapture and the probability of recapturing an animal, given that it is alive. If both of these probabilities are related to the same phenotypic trait, it can be difficult to distinguish effects on survival probabilities from effects on recapture probabilities. However, when animals are individually tagged and have multiple opportunities for recapture, we can properly partition observed trait-related variability into survival and recapture components. We present an overview of capture–recapture models that incorporate individual variability and develop methods to incorporate results from these models into estimates of population survival and selection for phenotypic traits. We conducted a series of simulations to understand the performance of these estimators and to assess the consequences of ignoring individual variability when it exists. In addition, we analyzed a large data set of .153 000 juvenile chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) of known length that were PIT-tagged during their seaward migration. Both our simulations and the case study indicated that the ability to precisely estimate selection for phenotypic traits was greatly compromised when differential recapture probabilities were ignored. Estimates of population survival, however, were far more robust. In the chinook salmon and steelhead study, we consistently found that smaller fish had a greater probability of recapture. We also uncovered length-related survival relationships in over half of the release group/river segment combinations that we observed, but we found both positive and negative relationships between length and survival probability. These results have important implications for the management of salmonid populations

    Using machine learning to study the kinematics of cold gas in galaxies

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    Next generation interferometers, such as the Square Kilometre Array, are set to obtain vast quantities of information about the kinematics of cold gas in galaxies. Given the volume of data produced by such facilities astronomers will need fast, reliable, tools to informatively filter and classify incoming data in real time. In this paper, we use machine learning techniques with a hydrodynamical simulation training set to predict the kinematic behaviour of cold gas in galaxies and test these models on both simulated and real interferometric data. Using the power of a convolutional autoencoder we embed kinematic features, unattainable by the human eye or standard tools, into a 3D space and discriminate between disturbed and regularly rotating cold gas structures. Our simple binary classifier predicts the circularity of noiseless, simulated, galaxies with a recall of 85% and performs as expected on observational CO and H i velocity maps, with a heuristic accuracy of 95%. The model output exhibits predictable behaviour when varying the level of noise added to the input data and we are able to explain the roles of all dimensions of our mapped space. Our models also allow fast predictions of input galaxies’ position angles with a 1σ uncertainty range of ±17° to ±23° (for galaxies with inclinations of 82.5° to 32.5°, respectively), which may be useful for initial parametrization in kinematic modelling samplers. Machine learning models, such as the one outlined in this paper, may be adapted for SKA science usage in the near future

    National Institutes of Health Stroke Scale (NIHSS) scoring inconsistencies between neurologists and emergency room nurses

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    BACKGROUND: Little is known about the consistency of initial NIHSS scores between neurologists and RNs in clinical practice. METHODS: A cohort study of patients with a code stroke was conducted at an urban academic Primary Stroke Center in the Midwest between January 1, 2018, and December 31, 2019 to determine consistency in National Institutes of Health Stroke Scale Scores (NIHSS) between neurologists and registered nurses (RNs). RESULTS: Among the 438 patients included in this study 65.3% (n = 286) of neurologist-RN NIHSS scoring pairs had congruent scores. One-in-three, (34.7%, n = 152) of neurologist-RN NIHSS scoring pairs had a clinically meaningful scoring difference of two points or greater. Higher NIHSS (p ≀ 0.01) and aphasia (p ≀ 0.01) were each associated with incongruent scoring between neurologist and emergency room RN pairs. CONCLUSIONS: One-in-three initial NIHSS assessed by both a neurologist and RN had a clinically meaningful score difference between providers. More severe stroke, as indicated by a higher NIHSS was associated with scoring inconsistency between neurologist-RN pairs. Subjective scoring measures, especially those involving a patient having aphasia, was associated with greater score incongruency. Score differences may be attributed to differences in NIHSS training requirements between neurologists and RNs

    The Morphological Butcher-Oemler effect in the SDSS Cut&Enhance Galaxy Cluster Catalog

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    We investigate the evolution of the fractions of late type cluster galaxies as a function of redshift, using one of the largest, most uniform cluster samples available. The sample consists of 514 clusters of galaxies in the range 0.02<z<0.3 from the Sloan Digital Sky Survey Cut & Enhance galaxy cluster catalog. This catalog was created using a single automated cluster finding algorithm on uniform data from a single telescope, with accurate CCD photometry, thus, minimizing selection biases. We use four independent methods to analyze the evolution of the late type galaxy fraction. Specifically, we select late type galaxies based on: restframe g-r color, u-r color, galaxy profile fitting and concentration index. The first criterion corresponds to the one used in the classical Butcher-Oemler analyses. The last three criteria are more sensitive to the morphological type of the galaxies. In all four cases, we find an increase in the fraction of late type galaxies with increasing redshift, significant at the 99.9% level. The results confirm that cluster galaxies do change colors with redshift (the Butcher-Oemler effect) and, in addition, they change their morphology to later-type toward higher redshift -- indicating a morphological equivalent of the Butcher-Oemler effect. We also find a tendency of richer clusters to have lower fractions of late type galaxies. The trend is consistent with a ram pressure stripping model, where richer clusters have more effective ram pressure due to their higher temperature.Comment: 44 pages, 15 figures, accepted for PAS