11 resultados para multiple choice constructed response machine grading

em Digital Commons - Michigan Tech


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Fieldwork is supportive of students’ natural inquiry abilities. Educational research findings suggest that instructors can foster the growth of thinking skills and promote science literacy by incorporating active learning strategies (McConnel et al, 2003). Huntoon (2001) states that there is a need to determine optimal learning strategies and to document the procedure of assessing those optimal geoscience curricula. This study seeks to determine if Earth Space II, a high school geological field course, can increase students’ knowledge of selected educational objectives. This research also seeks to measure any impact Earth Space II has on students’ attitude towards science. Assessment of the Earth Space II course objectives provided data on the impact of field courses on high school students’ scientific literacy, scientific inquiry skills, and understanding of selected course objectives. Knowledge assessment was done using a multiple choice format test, the Geoscience Concept Inventory, and an open-ended format essay test. Attitude assessment occurred by utilizing a preexisting science attitude survey. Both knowledge assessments items showed a positive effect size from the pretest to the posttest. The essay exam effect size was 17 and the Geoscience Concept Inventory effect size was 0.18. A positive impact on students’ attitude toward science was observed by an increase in the overall mean Likert value from the pre-survey to the post-survey.

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This research project measured the effects of real-world content in a science classroom by determining change (deep knowledge of life science content, including ecosystems from MDE – Grade Level Content Expectations) in a subset of students (6th Grade Science) that may result from the addition of curriculum (real-world content of rearing trout in the classroom). Data showed large gains from the pre-test to post-test in students from both the experimental and control groups. The ecology unit with the implementation of real-world content [trout] was even more successful, and improved students’ deep knowledge of ecosystem content from Michigan’s Department of Education Grade Level Content Expectations. The gains by the experimental group on the constructed response section of the test, which included higher cognitive level items, were significant. Clinical interviews after the post-test confirmed increases in deep knowledge of ecosystem concepts in the experimental group, by revealing that a sample of experimental group students had a better grasp of important ecology concepts as compared to a sample of control group students.

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This report shares my efforts in developing a solid unit of instruction that has a clear focus on student outcomes. I have been a teacher for 20 years and have been writing and revising curricula for much of that time. However, most has been developed without the benefit of current research on how students learn and did not focus on what and how students are learning. My journey as a teacher has involved a lot of trial and error. My traditional method of teaching is to look at the benchmarks (now content expectations) to see what needs to be covered. My unit consists of having students read the appropriate sections in the textbook, complete work sheets, watch a video, and take some notes. I try to include at least one hands-on activity, one or more quizzes, and the traditional end-of-unit test consisting mostly of multiple choice questions I find in the textbook. I try to be engaging, make the lessons fun, and hope that at the end of the unit my students get whatever concepts I‘ve presented so that we can move on to the next topic. I want to increase students‘ understanding of science concepts and their ability to connect understanding to the real-world. However, sometimes I feel that my lessons are missing something. For a long time I have wanted to develop a unit of instruction that I know is an effective tool for the teaching and learning of science. In this report, I describe my efforts to reform my curricula using the “Understanding by Design” process. I want to see if this style of curriculum design will help me be a more effective teacher and if it will lead to an increase in student learning. My hypothesis is that this new (for me) approach to teaching will lead to increased understanding of science concepts among students because it is based on purposefully thinking about learning targets based on “big ideas” in science. For my reformed curricula I incorporate lessons from several outstanding programs I‘ve been involved with including EpiCenter (Purdue University), Incorporated Research Institutions for Seismology (IRIS), the Master of Science Program in Applied Science Education at Michigan Technological University, and the Michigan Association for Computer Users in Learning (MACUL). In this report, I present the methodology on how I developed a new unit of instruction based on the Understanding by Design process. I present several lessons and learning plans I‘ve developed for the unit that follow the 5E Learning Cycle as appendices at the end of this report. I also include the results of pilot testing of one of lessons. Although the lesson I pilot-tested was not as successful in increasing student learning outcomes as I had anticipated, the development process I followed was helpful in that it required me to focus on important concepts. Conducting the pilot test was also helpful to me because it led me to identify ways in which I could improve upon the lesson in the future.

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This dissertation serves as a call to geoscientists to share responsibility with K-12 educators for increasing Earth science literacy. When partnerships are created among K-12 educators and geoscientists, the synergy created can promote Earth science literacy in students, teachers, and the broader community. The research described here resulted in development of tools that can support effective professional development for teachers. One tool is used during the planning stages to structure a professional development program, another set of tools supports measurement of the effectiveness of a development program, and the third tool supports sustainability of professional development programs. The Michigan Teacher Excellence Program (MiTEP), a Math/Science Partnership project funded by the National Science Foundation, served as the test bed for developing and testing these tools. The first tool, the planning tool, is the Earth Science Literacy Principles (ESLP). The ESLP served as a planning tool for the two-week summer field courses as part of the MiTEP program. The ESLP, published in 2009, clearly describe what an Earth science literate person should know. The ESLP consists of nine big ideas and their supporting fundamental concepts. Using the ESLP for planning a professional development program assisted both instructors and teacher-participants focus on important concepts throughout the professional development activity. The measurement tools were developed to measure change in teachers’ Earth science content-area knowledge and perceptions related to teaching and learning that result from participating in a professional development program. The first measurement tool, the Earth System Concept Inventory (ESCI), directly measures content-area knowledge through a succession of multiple-choice questions that are aligned with the content of the professional development experience. The second measurement, an exit survey, collects qualitative data from teachers regarding their impression of the professional development. Both the ESCI and the exit survey were tested for validity and reliability. Lesson study is discussed here as a strategy for sustaining professional development in a school or a district after the end of a professional development activity. Lesson study, as described here, was offered as a formal course. Teachers engaged in lesson study worked collaboratively to design and test lessons that improve the teachers’ classroom practices. Data regarding the impact of the lesson study activity were acquired through surveys, written documents, and group interviews. The data are interpreted to indicate that the lesson study process improved teacher quality and classroom practices. In the case described here, the lesson study process was adopted by the teachers’ district and currently serves as part of the district’s work in Professional Learning Communities, resulting in ongoing professional development throughout the district.

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Important food crops like rice are constantly exposed to various stresses that can have devastating effect on their survival and productivity. Being sessile, these highly evolved organisms have developed elaborate molecular machineries to sense a mixture of stress signals and elicit a precise response to minimize the damage. However, recent discoveries revealed that the interplay of these stress regulatory and signaling molecules is highly complex and remains largely unknown. In this work, we conducted large scale analysis of differential gene expression using advanced computational methods to dissect regulation of stress response which is at the heart of all molecular changes leading to the observed phenotypic susceptibility. One of the most important stress conditions in terms of loss of productivity is drought. We performed genomic and proteomic analysis of epigenetic and miRNA mechanisms in regulation of drought responsive genes in rice and found subsets of genes with striking properties. Overexpressed genesets included higher number of epigenetic marks, miRNA targets and transcription factors which regulate drought tolerance. On the other hand, underexpressed genesets were poor in above features but were rich in number of metabolic genes with multiple co-expression partners contributing majorly towards drought resistance. Identification and characterization of the patterns exhibited by differentially expressed genes hold key to uncover the synergistic and antagonistic components of the cross talk between stress response mechanisms. We performed meta-analysis on drought and bacterial stresses in rice and Arabidopsis, and identified hundreds of shared genes. We found high level of conservation of gene expression between these stresses. Weighted co-expression network analysis detected two tight clusters of genes made up of master transcription factors and signaling genes showing strikingly opposite expression status. To comprehensively identify the shared stress responsive genes between multiple abiotic and biotic stresses in rice, we performed meta-analyses of microarray studies from seven different abiotic and six biotic stresses separately and found more than thirteen hundred shared stress responsive genes. Various machine learning techniques utilizing these genes classified the stresses into two major classes' namely abiotic and biotic stresses and multiple classes of individual stresses with high accuracy and identified the top genes showing distinct patterns of expression. Functional enrichment and co-expression network analysis revealed the different roles of plant hormones, transcription factors in conserved and non-conserved genesets in regulation of stress response.

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Large parts of the world are subjected to one or more natural hazards, such as earthquakes, tsunamis, landslides, tropical storms (hurricanes, cyclones and typhoons), costal inundation and flooding. Virtually the entire world is at risk of man-made hazards. In recent decades, rapid population growth and economic development in hazard-prone areas have greatly increased the potential of multiple hazards to cause damage and destruction of buildings, bridges, power plants, and other infrastructure; thus posing a grave danger to the community and disruption of economic and societal activities. Although an individual hazard is significant in many parts of the United States (U.S.), in certain areas more than one hazard may pose a threat to the constructed environment. In such areas, structural design and construction practices should address multiple hazards in an integrated manner to achieve structural performance that is consistent with owner expectations and general societal objectives. The growing interest and importance of multiple-hazard engineering has been recognized recently. This has spurred the evolution of multiple-hazard risk-assessment frameworks and development of design approaches which have paved way for future research towards sustainable construction of new and improved structures and retrofitting of the existing structures. This report provides a review of literature and the current state of practice for assessment, design and mitigation of the impact of multiple hazards on structural infrastructure. It also presents an overview of future research needs related to multiple-hazard performance of constructed facilities.

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Autonomous system applications are typically limited by the power supply operational lifetime when battery replacement is difficult or costly. A trade-off between battery size and battery life is usually calculated to determine the device capability and lifespan. As a result, energy harvesting research has gained importance as society searches for alternative energy sources for power generation. For instance, energy harvesting has been a proven alternative for powering solar-based calculators and self-winding wristwatches. Thus, the use of energy harvesting technology can make it possible to assist or replace batteries for portable, wearable, or surgically-implantable autonomous systems. Applications such as cardiac pacemakers or electrical stimulation applications can benefit from this approach since the number of surgeries for battery replacement can be reduced or eliminated. Research on energy scavenging from body motion has been investigated to evaluate the feasibility of powering wearable or implantable systems. Energy from walking has been previously extracted using generators placed on shoes, backpacks, and knee braces while producing power levels ranging from milliwatts to watts. The research presented in this paper examines the available power from walking and running at several body locations. The ankle, knee, hip, chest, wrist, elbow, upper arm, side of the head, and back of the head were the chosen target localizations. Joints were preferred since they experience the most drastic acceleration changes. For this, a motor-driven treadmill test was performed on 11 healthy individuals at several walking (1-4 mph) and running (2-5 mph) speeds. The treadmill test provided the acceleration magnitudes from the listed body locations. Power can be estimated from the treadmill evaluation since it is proportional to the acceleration and frequency of occurrence. Available power output from walking was determined to be greater than 1mW/cm³ for most body locations while being over 10mW/cm³ at the foot and ankle locations. Available power from running was found to be almost 10 times higher than that from walking. Most energy harvester topologies use linear generator approaches that are well suited to fixed-frequency vibrations with sub-millimeter amplitude oscillations. In contrast, body motion is characterized with a wide frequency spectrum and larger amplitudes. A generator prototype based on self-winding wristwatches is deemed to be appropriate for harvesting body motion since it is not limited to operate at fixed-frequencies or restricted displacements. Electromagnetic generation is typically favored because of its slightly higher power output per unit volume. Then, a nonharmonic oscillating rotational energy scavenger prototype is proposed to harness body motion. The electromagnetic generator follows the approach from small wind turbine designs that overcome the lack of a gearbox by using a larger number of coil and magnets arrangements. The device presented here is composed of a rotor with multiple-pole permanent magnets having an eccentric weight and a stator composed of stacked planar coils. The rotor oscillations induce a voltage on the planar coil due to the eccentric mass unbalance produced by body motion. A meso-scale prototype device was then built and evaluated for energy generation. The meso-scale casing and rotor were constructed on PMMA with the help of a CNC mill machine. Commercially available discrete magnets were encased in a 25mm rotor. Commercial copper-coated polyimide film was employed to manufacture the planar coils using MEMS fabrication processes. Jewel bearings were used to finalize the arrangement. The prototypes were also tested at the listed body locations. A meso-scale generator with a 2-layer coil was capable to extract up to 234 µW of power at the ankle while walking at 3mph with a 2cm³ prototype for a power density of 117 µW/cm³. This dissertation presents the analysis of available power from walking and running at different speeds and the development of an unobtrusive miniature energy harvesting generator for body motion. Power generation indicates the possibility of powering devices by extracting energy from body motion.

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The goal of this research is to provide a framework for vibro-acoustical analysis and design of a multiple-layer constrained damping structure. The existing research on damping and viscoelastic damping mechanism is limited to the following four mainstream approaches: modeling techniques of damping treatments/materials; control through the electrical-mechanical effect using the piezoelectric layer; optimization by adjusting the parameters of the structure to meet the design requirements; and identification of the damping material’s properties through the response of the structure. This research proposes a systematic design methodology for the multiple-layer constrained damping beam giving consideration to vibro-acoustics. A modeling technique to study the vibro-acoustics of multiple-layered viscoelastic laminated beams using the Biot damping model is presented using a hybrid numerical model. The boundary element method (BEM) is used to model the acoustical cavity whereas the Finite Element Method (FEM) is the basis for vibration analysis of the multiple-layered beam structure. Through the proposed procedure, the analysis can easily be extended to other complex geometry with arbitrary boundary conditions. The nonlinear behavior of viscoelastic damping materials is represented by the Biot damping model taking into account the effects of frequency, temperature and different damping materials for individual layers. A curve-fitting procedure used to obtain the Biot constants for different damping materials for each temperature is explained. The results from structural vibration analysis for selected beams agree with published closed-form results and results for the radiated noise for a sample beam structure obtained using a commercial BEM software is compared with the acoustical results of the same beam with using the Biot damping model. The extension of the Biot damping model is demonstrated to study MDOF (Multiple Degrees of Freedom) dynamics equations of a discrete system in order to introduce different types of viscoelastic damping materials. The mechanical properties of viscoelastic damping materials such as shear modulus and loss factor change with respect to different ambient temperatures and frequencies. The application of multiple-layer treatment increases the damping characteristic of the structure significantly and thus helps to attenuate the vibration and noise for a broad range of frequency and temperature. The main contributions of this dissertation include the following three major tasks: 1) Study of the viscoelastic damping mechanism and the dynamics equation of a multilayer damped system incorporating the Biot damping model. 2) Building the Finite Element Method (FEM) model of the multiple-layer constrained viscoelastic damping beam and conducting the vibration analysis. 3) Extending the vibration problem to the Boundary Element Method (BEM) based acoustical problem and comparing the results with commercial simulation software.

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Red pine (Pinus resinosa Ait.) plantations have been established in Michigan with expectations of mixed final product goals: pulpwood, boltwood and possibly sawlogs. The effects of alternative treatments on tree and stand attributes were examined in: the Atlantic Mine trial, thinned in spring 2006 with three alternatives: (1) every fifth row removal plus crown thinning, (2) every third row removal plus crown thinning and (3) every third row removal plus thinning from below; the Crane Lake trial, thinned in fall 2004 with two alternatives: (1) every third row removal and (2) every third row removal plus thinning from above; the Middle Branch East trial, thinned in fall 2004 with two alternatives: (1) every third row removal plus one in three remaining trees and (2) every third row removal plus one in five remaining trees. All trials included control plots where no thinning was applied. The trials were established in the field as a randomized complete block experiments, in which individual trees were measured in 3-4 fixed-area plots located within each treatment unit. Growth responses of diameter at breast height, height, live crown length, stand basal area and stand volume were examined along with their increments. The Tukey multiple comparison test was used to detect significant differences between treatments in their effect on tree growth response. The results showed that diameter increment increased with increasing thinning intensity and was significantly larger in thinned plots compared to unthinned. Treatments did not substantially affect average tree height increment. Stand basal area increment was significantly larger in the control plot only the year after the harvest. Volume increment was significantly larger in controls, but did not differ considerably among remaining treatments. However, the ratio of volume increment to standing volume was significantly smaller in unthinned plots compared to thinned. Since thinning treatments in all trials hardly ever differed significantly in their effect on stand growth response, mainly due to the relatively short time of the evaluation, heavier thinnings should be favored due to higher volume increment rates and shorter time needed to reach desirable diameters. Nevertheless, economic evaluation based on obtained results will be conducted in the future in order to make final decisions about the most profitable treatment.

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Understanding how a living cell behaves has become a very important topic in today’s research field. Hence, different sensors and testing devices have been designed to test the mechanical properties of these living cells. This thesis presents a method of micro-fabricating a bio-MEMS based force sensor which is used to measure the force response of living cells. Initially, the basic concepts of MEMS have been discussed and the different micro-fabrication techniques used to manufacture various MEMS devices have been described. There have been many MEMS based devices manufactured and employed for testing many nano-materials and bio-materials. Each of the MEMS based devices described in this thesis use a novel concept of testing the specimens. The different specimens tested are nano-tubes, nano-wires, thin film membranes and biological living cells. Hence, these different devices used for material testing and cell mechanics have been explained. The micro-fabrication techniques used to fabricate this force sensor has been described and the experiments preformed to successfully characterize each step in the fabrication have been explained. The fabrication of this force sensor is based on the facilities available at Michigan Technological University. There are some interesting and uncommon concepts in MEMS which have been observed during this fabrication. These concepts in MEMS which have been observed are shown in multiple SEM images.

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The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.