Moral reasoning and ethics in educational leadership /

School leaders face difficult decisions regarding discipline matters. Often, such decisions play an important role in determining the moral tone of the school and the health of the school community. Many stakeholders are affected by the outcome of such decisions. Codes of conduct, board and school policies, and discipline meetings are often shrouded under secrecy, making the discipline process mysterious. .; In this study I examined the process of moral reasoning. I sought to determine the extent to which school leaders were aware that they were involved in a process of moral reasoning, and ftirthermore, what kind of moral reasoning they practiced. As well, I investigated the ethical grounds and foundations underlying moral reasoning. Thus, in this study I probed the awareness of the process of moral reasoning and sought to find the ethical grounding of decision making. This qualitative study featured short field research. The process involved individual interviews with three different participants: school leaders of a public. Catholic, and an independent school. It found that each school leader practiced moral reasoning to varying degrees through the discipline process. It also explored the possible democratization of moral reasoning by linking to concepts such as fairness, due process, public accountability, and greater participation in the administering of discipline. This study has implications for practice, theory, and future research. The examination of school leaders as the primary focus for discipline matters opens the door to future research that could explore differences between the school systems and possibly other parties affected by moral reasoning in discipline cases.

Violent Video Game Playing, Moral Reasoning, and Attitudes Towards Violence in Adolescents: Is There a Connection?

In this study of 109 adolescents from the eighth grade of seven public elementary schools in Ontario, the relationship among adolescents’ violent video game playing patterns, habits and attitudes, their levels of moral reasoning, and their attitudes towards violence in real life was investigated. In addition, gender differences were addressed. The mixed-methodology was employed combining qualitative and quantitative data. The research results confirmed that playing video games in general is a very popular activity among those adolescents. Significant negative relationship was found between adolescents’ amount of time playing violent video games during the day and their scores on The Sociomoral Reflection Measure. Significant difference was also found between adolescents who play violent video games and those who do not play violent video games on their scores on The Attitudes Towards Violence Scale. Boys and girls significantly differed in the amount of playing video games during the day, the reasons for playing video games, their favourite video game choices, and their favourite video game character choices. Boys and girls also significantly differed on their choices of personality traits of selected video game characters, the identification with video game characters, and their mood experiences while playing video games. The findings are put into the educational context and the context of normal development, and suggestions are given for parents, for educators, and for future violent video game research.

Age-Related Changes in Visual Spatial Working Memory Cognits: Frontal-Parietal EEG Coherence During Delay

This study explored changes in scalp electrophysiology across two Working Memory (WM) tasks and two age groups. Continuous electroencephalography (EEG) was recorded from 18 healthy adults (18-34 years) and 12 healthy adolescents (14-17) during the performance of two Oculomotor Delayed Response (ODR) WM tasks; (i.e. eye movements were the metric of motor response). Delay-period, EEG data in the alpha frequency was sampled from anterior and parietal scalp sites to achieve a general measure of frontal and parietal activity, respectively. Frontal-parietal, alpha coherence was calculated for each participant for each ODR-WM task. Coherence significantly decreased in adults moving across the two ODR tasks, whereas, coherence significantly increased in adolescents moving across the two ODR tasks. The effects of task in the adolescent and adult groups were large and medium, respectively. Within the limits of this study, the results provide empirical support that WM development during adolescence include complex, qualitative, change.

KAM: Automatic Planning and Interpretation of Numerical Experiments Using Geometrical Methods

KAM is a computer program that can automatically plan, monitor, and interpret numerical experiments with Hamiltonian systems with two degrees of freedom. The program has recently helped solve an open problem in hydrodynamics. Unlike other approaches to qualitative reasoning about physical system dynamics, KAM embodies a significant amount of knowledge about nonlinear dynamics. KAM's ability to control numerical experiments arises from the fact that it not only produces pictures for us to see, but also looks at (sic---in its mind's eye) the pictures it draws to guide its own actions. KAM is organized in three semantic levels: orbit recognition, phase space searching, and parameter space searching. Within each level spatial properties and relationships that are not explicitly represented in the initial representation are extracted by applying three operations ---(1) aggregation, (2) partition, and (3) classification--- iteratively.

Spatial patterns of gluten protein and polymer distribution in wheat grain

The starchy endosperm is the major storage tissue in the mature wheat grain and exhibits quantitative and qualitative gradients in composition, with the outermost cell layers being rich in protein, mainly gliadins, and the inner cells being low in protein but enriched in high-molecular-weight (HMW) subunits of glutenin. We have used sequential pearling to produce flour fractions enriched in particular cell layers to determine the protein gradients in four different cultivars grown at two nitrogen levels. The results show that the steepness of the protein gradient is determined by both genetic and nutritional factors, with three high-protein breadmaking cultivars being more responsive to the N treatment than a low-protein cultivar suitable for livestock feed. Nitrogen also affected the relative abundances of the three main classes of wheat prolamins: the sulfur-poor ω-gliadins showed the greatest response to nitrogen and increased evenly across the grain; the HMW subunits also increased in response to nitrogen but proportionally more in the outer layers of the starchy endosperm than near the core, while the sulfur-rich prolamins showed the opposite trend.

On Aspects of Mathematical Reasoning : Affect and Gender

This thesis explores two aspects of mathematical reasoning: affect and gender. I started by looking at the reasoning of upper secondary students when solving tasks. This work revealed that when not guided by an interviewer, algorithmic reasoning, based on memorising algorithms which may or may not be appropriate for the task, was predominant in the students reasoning. Given this lack of mathematical grounding in students reasoning I looked in a second study at what grounds they had for different strategy choices and conclusions. This qualitative study suggested that beliefs about safety, expectation and motivation were important in the central decisions made during task solving.  But are reasoning and beliefs gendered? The third study explored upper secondary school teachers conceptions about gender and students mathematical reasoning. In this study I found that upper secondary school teachers attributed gender symbols including insecurity, use of standard methods and imitative reasoning to girls and symbols such as multiple strategies especially on the calculator, guessing and chance-taking were assigned to boys. In the fourth and final study I found that students, both male and female, shared their teachers view of rather traditional feminities and masculinities. Remarkably however, this result did not repeat itself when students were asked to reflect on their own behaviour: there were some discrepancies between the traits the students ascribed as gender different and the traits they ascribed to themselves. Taken together the thesis suggests that, contrary to conceptions, girls and boys share many of the same core beliefs about mathematics, but much work is still needed if we should create learning environments that provide better opportunities for students to develop beliefs that guide them towards well-grounded mathematical reasoning. 

Does spatial visualization ability improve after studying technical drawing?

Two studies were carried out to analyze whether learning technical drawing improves a person's ability for spatial visualization. Visualization and inductive reasoning tests were applied at the beginning and end of a course in technical drawing in samples of first year engineering students. In both studies it was observed that a moderate percentage of students improved their Visualization test execution. The improvement was similar in men and women. There was no improvement on the inductive reasoning test. The results support the conclusion that the spatial visualization ability can be improved with training.

The spatial dynamics of native and introduced blowflies (Dipt., Calliphoridae)

The spatial dynamics of three blowfly species was investigated using a spatially extended model of density-dependent population growth and the results indicate an overall stabilizing effect. Introduction of diffusive dispersal induced a quantitative effect of damping variation in population size on the route to a one-fixed point equilibrium in the native species, Cochliomyia macellaria. On the other hand, diffusive dispersal caused qualitative shifts in the dynamics of two invading species, Chrysomya megacephala and Chrysomya putoria. In both species diffusive dispersal can produce a qualitative shift from a two-point limit cycle to a one fixed-point dynamics. Quantitatively, dispersal also has the effect of damping oscillations in population size in the invading species.

Chlorophyll a spatial inference using artificial neural network from multispectral images and in situ measurements

Considering the importance of monitoring the water quality parameters, remote sensing is a practicable alternative to limnological variables detection, which interacts with electromagnetic radiation, called optically active components (OAC). Among these, the phytoplankton pigment chlorophyll a is the most representative pigment of photosynthetic activity in all classes of algae. In this sense, this work aims to develop a method of spatial inference of chlorophyll a concentration using Artificial Neural Networks (ANN). To achieve this purpose, a multispectral image and fluorometric measurements were used as input data. The multispectral image was processed and the net training and validation dataset were carefully chosen. From this, the neural net architecture and its parameters were defined to model the variable of interest. In the end of training phase, the trained network was applied to the image and a qualitative analysis was done. Thus, it was noticed that the integration of fluorometric and multispectral data provided good results in the chlorophyll a inference, when combined in a structure of artificial neural networks.

Quantitative and qualitative dynamics of exotic and native blowflies ( Diptera: Calliphoridae) with migrations among municipalities

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The influence of landscape on the spatial and temporal distribution of stream macroalgal communities of two types of subtropical biomes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Correlations of trace elements in breast human tissues: Evaluation of spatial distribution using μ-XRF

The aim of this work is to investigate microscopic correlations between trace elements in breast human tissues. A synchrotron X-ray fluorescence microprobe system (μ-XRF) was used to obtain two-dimensional distribution of trace element Ca, Fe, Cu and Zn in normal (6 samples) and malignant (14 samples) breast tissues. The experiment was performed in X-ray Fluorescence beam line at Laboratório Nacional de Luz Síncrotron (LNLS), Campinas, Brazil. The white microbeam was generated with a fine conical capillary with a 20 μm output diameter. The samples were supported on a XYZ table. An optical microscope with motorized zoom was used for sample positioning and choice the area to be scanned. Automatic two-dimensional scans were programmed and performed with steps of 30 μm in each direction (x, y) on the selected area. The fluorescence signals were recorded using a Si(Li) detector, positioned at 90 degrees with respect to the incident beam, with a collection time of 10 s per point. The elemental maps obtained from each sample were overlap to observe correlation between trace elements. Qualitative results showed that the pairs of elements Ca-Zn and Fe-Cu could to be correlated in malignant breast tissues. Quantitative results, achieved by Spearman correlation tests, indicate that there is a spatial correlation between these pairs of elements (p < 0.001) suggesting the importance of these elements in metabolic processes associated with the development of the tumor.

Generalizing the dynamic field theory of spatial cognition across real and developmental time scales

Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.

Effect of mixing, particle interaction, and spatial dimension on the glass transition

In this thesis, the influence of composition changes on the glass transition behavior of binary liquids in two and three spatial dimensions (2D/3D) is studied in the framework of mode-coupling theory (MCT).The well-established MCT equations are generalized to isotropic and homogeneous multicomponent liquids in arbitrary spatial dimensions. Furthermore, a new method is introduced which allows a fast and precise determination of special properties of glass transition lines. The new equations are then applied to the following model systems: binary mixtures of hard disks/spheres in 2D/3D, binary mixtures of dipolar point particles in 2D, and binary mixtures of dipolar hard disks in 2D. Some general features of the glass transition lines are also discussed. The direct comparison of the binary hard disk/sphere models in 2D/3D shows similar qualitative behavior. Particularly, for binary mixtures of hard disks in 2D the same four so-called mixing effects are identified as have been found before by Götze and Voigtmann for binary hard spheres in 3D [Phys. Rev. E 67, 021502 (2003)]. For instance, depending on the size disparity, adding a second component to a one-component liquid may lead to a stabilization of either the liquid or the glassy state. The MCT results for the 2D system are on a qualitative level in agreement with available computer simulation data. Furthermore, the glass transition diagram found for binary hard disks in 2D strongly resembles the corresponding random close packing diagram. Concerning dipolar systems, it is demonstrated that the experimental system of König et al. [Eur. Phys. J. E 18, 287 (2005)] is well described by binary point dipoles in 2D through a comparison between the experimental partial structure factors and those from computer simulations. For such mixtures of point particles it is demonstrated that MCT predicts always a plasticization effect, i.e. a stabilization of the liquid state due to mixing, in contrast to binary hard disks in 2D or binary hard spheres in 3D. It is demonstrated that the predicted plasticization effect is in qualitative agreement with experimental results. Finally, a glass transition diagram for binary mixtures of dipolar hard disks in 2D is calculated. These results demonstrate that at higher packing fractions there is a competition between the mixing effects occurring for binary hard disks in 2D and those for binary point dipoles in 2D.

Studies of spatial clustering of inertial particles in turbulence

We present studies of the spatial clustering of inertial particles embedded in turbulent flow. A major part of the thesis is experimental, involving the technique of Phase Doppler Interferometry (PDI). The thesis also includes significant amount of simulation studies and some theoretical considerations. We describe the details of PDI and explain why it is suitable for study of particle clustering in turbulent flow with a strong mean velocity. We introduce the concept of the radial distribution function (RDF) as our chosen way of quantifying inertial particle clustering and present some original works on foundational and practical considerations related to it. These include methods of treating finite sampling size, interpretation of the magnitude of RDF and the possibility of isolating RDF signature of inertial clustering from that of large scale mixing. In experimental work, we used the PDI to observe clustering of water droplets in a turbulent wind tunnel. From that we present, in the form of a published paper, evidence of dynamical similarity (Stokes number similarity) of inertial particle clustering together with other results in qualitative agreement with available theoretical prediction and simulation results. We next show detailed quantitative comparisons of results from our experiments, direct-numerical-simulation (DNS) and theory. Very promising agreement was found for like-sized particles (mono-disperse). Theory is found to be incorrect regarding clustering of different-sized particles and we propose a empirical correction based on the DNS and experimental results. Besides this, we also discovered a few interesting characteristics of inertial clustering. Firstly, through observations, we found an intriguing possibility for modeling the RDF arising from inertial clustering that has only one (sensitive) parameter. We also found that clustering becomes saturated at high Reynolds number.