Reviewing, Rethinking and Revising Homework Expectations in a Seventh Grade Math Class

In this action research study of my seventh grade mathematics class, I investigated whether de-emphasizing homework assignments as daily grades while stressing them as daily practice encouraged students to focus more on the learning rather than the daily grade. As part of this study, I also looked at how this change in homework expectations affected my daily teaching. I discovered that having students keep notes, examples, practice problems and homework assignments in a notebook helped them concentrate more on the process of getting answers and why they may of had an incorrect answer. Students were more likely to discuss with their peers how answers were found when comparing answers showed differences. When we reviewed the answers, they were more willing to ask questions about why their answer was wrong and then make corrections. As a result of this research, I plan to continue having seventh graders keep using notebooks to organize their notes, examples and assignments.

The Importance of Teaching Students How to Read to Comprehend Mathematical Language

In this action research study of my classroom of 8th and 9th grade Algebra I students, I investigated if there are any benefits for the students in my class to learn how to read, translate, use, and understand the mathematical language found daily in their math lessons. I discovered that daily use and practice of the mathematical language in both written and verbal form, by not only me but by my students as well, improved their understanding of the textbook instructions, increased their vocabulary and also increased their understanding of their math lessons. I also found that my students remembered the mathematical material better with constant use of mathematical language and terms. As a result of this research, I plan to continue stressing the use of mathematical language and vocabulary in my classroom and will try to develop new ways to help students to read, understand, and remember mathematical language they find daily in their textbooks.

Writing for Understanding in Math Class

In this action research study of my classroom of 10th grade geometry students, I investigated how students learn to communicate mathematics in a written form. The purpose of the study is to encourage students to express their mathematical thinking clearly by developing their communication skills. I discovered that although students struggled with the writing assignments, they were more comfortable with making comments, writing questions and offering suggestions through their journal rather than vocally in class. I have utilized teaching strategies for English Language Learners, but I had never asked the students if these strategies actually improved their learning. I have high expectations, and have not changed that, but I soon learned that I did not want to start the development of students’ written communication skills by having the students write a math solution. I began having my students write after teaching them to take notes and modeling it for them. Through entries in the journals, I learned how taking notes best helped them in their pursuit of mathematical knowledge. As a result of this research, I plan to use journals more in each of my classes, not just a select class. I also better understand the importance of stressing that students take notes, showing them how to do that, and the reasons notes best help English Language Learners.

Writing In Math Class? Written Communication in the Mathematics Classroom

In this action research study of my seventh grade mathematics classroom, I investigated what written communication within the mathematics classroom would look like. I increased vocabulary instruction of specific mathematical terms for my students to use in their writing. I also looked at what I would have to do differently in my teaching in order for my students to be successful in their writing. Although my students said that using writing to explain mathematics helped them to better understand the math, my research revealed that student writing did not necessarily translate to improved scores. After direct instruction and practice on math vocabulary, my students did use the vocabulary words more often in their writing; however, my students used the words more like they would in spelling sentences rather than to show what it meant and how it can be applied within their written explanation in math. In my teaching, I discovered I tried many different strategies to help my students be successful. I was very deliberate in my language and usage of vocabulary words and also in my explanations of various math concepts. As a result of this research, I plan to continue having my students use writing to communicate within the mathematics classroom. I will keep using some of the strategies I found successful. I also will be very deliberate in using vocabulary words and stress the use of vocabulary words with my students in the future.

Teaching of the Integrated Management of Childhood Illness strategy in undergraduate nursing programs

Objective: To describe and analyze the teaching of the Integrated Management of hildhood Illness (IMCI) strategy on Brazilian undergraduate nursing programs. Method: Integrating an international multicentric study, a cross-sectional online survey was conducted between May and October 2010 with 571 undergraduate nursing programs in Brazil Results: Responses were received from 142 programs, 75% private and 25% public. 64% of them included the IMCI strategy in the theoretical content, and 50% of the programs included IMCI as part of the students’ practical experience. The locations most used for practical teaching were primary health care units. The ‘treatment’ module was taught by the fewest number of programs, and few programs had access to the IMCI instructional manuals. All programs used exams for evaluation, and private institutions were more likely to include class participation as part of the evaluation. Teaching staff in public institutions were more likely to have received training in teaching IMCI. Conclusion: In spite of the relevance of the IMCI strategy in care of the child, its content is not addressed in all undergraduate programs in Brazil, and many programs do not have access to the IMCI teaching manuals and have not provide training in IMCI to their teaching staff.

Heterogeneous multicore systems for signal processing

This thesis explores the capabilities of heterogeneous multi-core systems, based on multiple Graphics Processing Units (GPUs) in a standard desktop framework. Multi-GPU accelerated desk side computers are an appealing alternative to other high performance computing (HPC) systems: being composed of commodity hardware components fabricated in large quantities, their price-performance ratio is unparalleled in the world of high performance computing. Essentially bringing “supercomputing to the masses”, this opens up new possibilities for application fields where investing in HPC resources had been considered unfeasible before. One of these is the field of bioelectrical imaging, a class of medical imaging technologies that occupy a low-cost niche next to million-dollar systems like functional Magnetic Resonance Imaging (fMRI). In the scope of this work, several computational challenges encountered in bioelectrical imaging are tackled with this new kind of computing resource, striving to help these methods approach their true potential. Specifically, the following main contributions were made: Firstly, a novel dual-GPU implementation of parallel triangular matrix inversion (TMI) is presented, addressing an crucial kernel in computation of multi-mesh head models of encephalographic (EEG) source localization. This includes not only a highly efficient implementation of the routine itself achieving excellent speedups versus an optimized CPU implementation, but also a novel GPU-friendly compressed storage scheme for triangular matrices. Secondly, a scalable multi-GPU solver for non-hermitian linear systems was implemented. It is integrated into a simulation environment for electrical impedance tomography (EIT) that requires frequent solution of complex systems with millions of unknowns, a task that this solution can perform within seconds. In terms of computational throughput, it outperforms not only an highly optimized multi-CPU reference, but related GPU-based work as well. Finally, a GPU-accelerated graphical EEG real-time source localization software was implemented. Thanks to acceleration, it can meet real-time requirements in unpreceeded anatomical detail running more complex localization algorithms. Additionally, a novel implementation to extract anatomical priors from static Magnetic Resonance (MR) scansions has been included.

MODELING FUNCTIONAL DATA WITH SPATIALLY HETEROGENEOUS SHAPE CHARACTERISTICS

We propose a novel class of models for functional data exhibiting skewness or other shape characteristics that vary with spatial or temporal location. We use copulas so that the marginal distributions and the dependence structure can be modeled independently. Dependence is modeled with a Gaussian or t-copula, so that there is an underlying latent Gaussian process. We model the marginal distributions using the skew t family. The mean, variance, and shape parameters are modeled nonparametrically as functions of location. A computationally tractable inferential framework for estimating heterogeneous asymmetric or heavy-tailed marginal distributions is introduced. This framework provides a new set of tools for increasingly complex data collected in medical and public health studies. Our methods were motivated by and are illustrated with a state-of-the-art study of neuronal tracts in multiple sclerosis patients and healthy controls. Using the tools we have developed, we were able to find those locations along the tract most affected by the disease. However, our methods are general and highly relevant to many functional data sets. In addition to the application to one-dimensional tract profiles illustrated here, higher-dimensional extensions of the methodology could have direct applications to other biological data including functional and structural MRI.

Distinguishing phenotypes of childhood wheeze and cough using latent class analysis

Airway disease in childhood comprises a heterogeneous group of disorders. Attempts to distinguish different phenotypes have generally considered few disease dimensions. The present study examines phenotypes of childhood wheeze and chronic cough, by fitting a statistical model to data representing multiple disease dimensions. From a population-based, longitudinal cohort study of 1,650 preschool children, 319 with parent-reported wheeze or chronic cough were included. Phenotypes were identified by latent class analysis using data on symptoms, skin-prick tests, lung function and airway responsiveness from two preschool surveys. These phenotypes were then compared with respect to outcome at school age. The model distinguished three phenotypes of wheeze and two phenotypes of chronic cough. Subsequent wheeze, chronic cough and inhaler use at school age differed clearly between the five phenotypes. The wheeze phenotypes shared features with previously described entities and partly reconciled discrepancies between existing sets of phenotype labels. This novel, multidimensional approach has the potential to identify clinically relevant phenotypes, not only in paediatric disorders but also in adult obstructive airway diseases, where phenotype definition is an equally important issue.

Modeling mechanical response of heterogeneous materials

Heterogeneous materials are ubiquitous in nature and as synthetic materials. These materials provide unique combination of desirable mechanical properties emerging from its heterogeneities at different length scales. Future structural and technological applications will require the development of advanced light weight materials with superior strength and toughness. Cost effective design of the advanced high performance synthetic materials by tailoring their microstructure is the challenge facing the materials design community. Prior knowledge of structure-property relationships for these materials is imperative for optimal design. Thus, understanding such relationships for heterogeneous materials is of primary interest. Furthermore, computational burden is becoming critical concern in several areas of heterogeneous materials design. Therefore, computationally efficient and accurate predictive tools are highly essential. In the present study, we mainly focus on mechanical behavior of soft cellular materials and tough biological material such as mussel byssus thread. Cellular materials exhibit microstructural heterogeneity by interconnected network of same material phase. However, mussel byssus thread comprises of two distinct material phases. A robust numerical framework is developed to investigate the micromechanisms behind the macroscopic response of both of these materials. Using this framework, effect of microstuctural parameters has been addressed on the stress state of cellular specimens during split Hopkinson pressure bar test. A voronoi tessellation based algorithm has been developed to simulate the cellular microstructure. Micromechanisms (microinertia, microbuckling and microbending) governing macroscopic behavior of cellular solids are investigated thoroughly with respect to various microstructural and loading parameters. To understand the origin of high toughness of mussel byssus thread, a Genetic Algorithm (GA) based optimization framework has been developed. It is found that two different material phases (collagens) of mussel byssus thread are optimally distributed along the thread. These applications demonstrate that the presence of heterogeneity in the system demands high computational resources for simulation and modeling. Thus, Higher Dimensional Model Representation (HDMR) based surrogate modeling concept has been proposed to reduce computational complexity. The applicability of such methodology has been demonstrated in failure envelope construction and in multiscale finite element techniques. It is observed that surrogate based model can capture the behavior of complex material systems with sufficient accuracy. The computational algorithms presented in this thesis will further pave the way for accurate prediction of macroscopic deformation behavior of various class of advanced materials from their measurable microstructural features at a reasonable computational cost.

Ctp1 and the MRN-complex are required for endonucleolytic Rec12 removal with release of a single class of oligonucleotides in fission yeast

DNA double-strand breaks (DSBs) are formed during meiosis by the action of the topoisomerase-like Spo11/Rec12 protein, which remains covalently bound to the 5' ends of the broken DNA. Spo11/Rec12 removal is required for resection and initiation of strand invasion for DSB repair. It was previously shown that budding yeast Spo11, the homolog of fission yeast Rec12, is removed from DNA by endonucleolytic cleavage. The release of two Spo11 bound oligonucleotide classes, heterogeneous in length, led to the conjecture of asymmetric cleavage. In fission yeast, we found only one class of oligonucleotides bound to Rec12 ranging in length from 17 to 27 nucleotides. Ctp1, Rad50, and the nuclease activity of Rad32, the fission yeast homolog of Mre11, are required for endonucleolytic Rec12 removal. Further, we detected no Rec12 removal in a rad50S mutant. However, strains with additional loss of components localizing to the linear elements, Hop1 or Mek1, showed some Rec12 removal, a restoration depending on Ctp1 and Rad32 nuclease activity. But, deletion of hop1 or mek1 did not suppress the phenotypes of ctp1Delta and the nuclease dead mutant (rad32-D65N). We discuss what consequences for subsequent repair a single class of Rec12-oligonucleotides may have during meiotic recombination in fission yeast in comparison to two classes of Spo11-oligonucleotides in budding yeast. Furthermore, we hypothesize on the participation of Hop1 and Mek1 in Rec12 removal.

E-Learning, E-Teaching und E-Assessment in der Hochschullehre

Wie lässt sich die Qualität des Lernens, Lehrens und Prüfens durch den Einsatz neuer Medien steigern? Übertragen auf die Komponenten und Bausteine des E-Education-Prozesses heißt das: - Mit welchen digitalen Materialien und Komponenten ist eine effiziente computergestützte Inhaltserschließung möglich? - Mit welcher Organisationsform der Lehre kann ein maximaler Qualitätsgewinn für die traditionelle Präsenzlehre erzielt werden? - Wie lassen sich traditionelle Prüfungsformen durch digitale Medien bereichern und mit technischer Hilfe auswerten? - Wie müssen digitale Inhalte beschaffen sein, um einen Mehrwert für den Lehr- und Lernprozess, möglicherweise in Selbstlernszenarien, zu erzielen? - Wie muss eine Lernplattformaufgebaut sein, um E-Education in ihrer gesamten Breite zu unterstützen und eine hohe Akzeptanz zu erreichen? Die Autoren sind Hauptakteure des Marburger „Linguistik Engineering Teams“, das in sich das gesamte Know-How für die Entwicklung und Nutzung verschiedener Lehr- und Lernszenarien vereinigt: von der Konzeption über die Programmierung bis hin zur Nutzung in allen denkbaren Varianten. Ihr Buch ist ein Leitfaden, der aufzeigt, wie mit einem komplexen E-Education-System nicht nur Qualitäts-, sondern auch Kapazitätsgewinne sowie erhebliche Aufwandsreduktionen erreicht werden können.

Bringing the Community into the Classroom: Teaching Immunizations Skills via a Community-based Project

Introduction or Statement of Problem Health care profession educators are challenged in their efforts to bring clinical experiences into the class room and to introduce students to community settings early in their didactic training. An immunization program directed at improving childhood immunization rates can introduce students to the community, to students of other disciplines and reinforce the knowledge and skills needed for immunization interventions. Successful interventions increase community demand for immunizations, improve access to services, and educate providers about immunization services and disease. Interventions serve to mold attitudes among health care professionals that foster commitment to universal immunization coverage and low disease rates. [See PDF for complete abstract]

Improving Chat in an Online Graduate Class

Introduction: Foundations of Health Information Sciences I is the first class many students take to introduce them to the field of health informatics. It is completely online, and uses optional weekly text-only chats to provide real time interaction between faculty and students. Chat sessions were very disorganized and difficult to follow, both real time and on the transcript. Research suggests that the disorganization contributes to cognitive load. [See PDF for complete abstract]

The Social Geography of Education: Neighborhood, Class Composition, and the Educational Achievement of Elementary School Students in Zurich, Switzerland

Despite an impressive amount of research and policy intervention no robust pattern of neighborhood effects on educational attainment has previously been identified. Adequate theoretical modeling and the sensitivity of the results to the method of the study are the major challenges in this area of research. This paper elaborates the social mechanisms of neighborhood effects and applies various methodological approaches to test them. Using data from Switzerland, the research reported here has detected heterogeneous effects of neighborhood on elementary school students’ educational achievement in Zurich. Although modest in comparison with the effects of classroom composition, these effects appear to be mediated primarily through social integration into a local peer network and are differentiated according to students’ gender and their social origin.