7,097 research outputs found
Pre-service teachers’ noticing: On the way to expert target
Unlike prevailing research focusing on what pre-service teachers attend to in a lesson and how they interpret it, the study investigates the content of their comments, knowledge-based reasoning and whether it agrees with experts’ views. Study 1 determined the dimensions of quality teaching pertinent to lessons in which a new subject matter is introduced and made a noticing target. In Study 2, pre-service teachers (n = 174) at the end of their university study made a written reflection of a video lesson, which was compared against the target. Most could not discern situations important for deep work with the content in the lesson. They failed to apply their theoretical knowledge in their interpretation of the ones they mentioned. Only half of their comments included knowledge-based reasoning, and their views were mostly partially consistent or inconsistent with the experts’ ones. This highlights the need to focus on content-related important situations in a lesson and their interpretation in teacher preparation and on developing the ability to discern the dimensions of instructional quality in concrete lessons
Comparative Multiple Case Study into the Teaching of Problem-Solving Competence in Lebanese Middle Schools
This multiple case study investigates how problem-solving competence is integrated into teaching practices in private schools in Lebanon. Its purpose is to compare instructional approaches to problem-solving across three different programs: the American (Common Core State Standards and New Generation Science Standards), French (Socle Commun de Connaissances, de Compétences et de Culture), and Lebanese with a focus on middle school (grades 7, 8, and 9). The project was conducted in nine schools equally distributed among three categories based on the programs they offered: category 1 schools offered the Lebanese program, category 2 the French and Lebanese programs, and category 3 the American and Lebanese programs. Each school was treated as a separate case.
Structured observation data were collected using observation logs that focused on lesson objectives and specific cognitive problem-solving processes. The two logs were created based on a document review of the requirements for the three programs. Structured observations were followed by semi-structured interviews that were conducted to explore teachers' beliefs and understandings of problem-solving competence. The comparative analysis of within-category structured observations revealed an instruction ranging from teacher-led practices, particularly in category 1 schools, to more student-centered approaches in categories 2 and 3. The cross-category analysis showed a reliance on cognitive processes primarily promoting exploration, understanding, and demonstrating understanding, with less emphasis on planning and executing, monitoring and reflecting, thus uncovering a weakness in addressing these processes. The findings of the post-observation semi-structured interviews disclosed a range of definitions of problem-solving competence prevalent amongst teachers with clear divergences across the three school categories.
This research is unique in that it compares problem-solving teaching approaches across three different programs and explores underlying teachers' beliefs and understandings of problem-solving competence in the Lebanese context. It is hoped that this project will inform curriculum developers about future directions and much-anticipated reforms of the Lebanese program and practitioners about areas that need to be addressed to further improve the teaching of problem-solving competence
Um modelo para suporte automatizado ao reconhecimento, extração, personalização e reconstrução de gráficos estáticos
Data charts are widely used in our daily lives, being present in regular media,
such as newspapers, magazines, web pages, books, and many others. A well constructed
data chart leads to an intuitive understanding of its underlying data
and in the same way, when data charts have wrong design choices, a redesign
of these representations might be needed. However, in most cases, these
charts are shown as a static image, which means that the original data are not
usually available. Therefore, automatic methods could be applied to extract the
underlying data from the chart images to allow these changes. The task of
recognizing charts and extracting data from them is complex, largely due to the
variety of chart types and their visual characteristics.
Computer Vision techniques for image classification and object detection are
widely used for the problem of recognizing charts, but only in images without
any disturbance. Other features in real-world images that can make this task
difficult are not present in most literature works, like photo distortions, noise,
alignment, etc. Two computer vision techniques that can assist this task and
have been little explored in this context are perspective detection and
correction. These methods transform a distorted and noisy chart in a clear
chart, with its type ready for data extraction or other uses. The task of
reconstructing data is straightforward, as long the data is available the
visualization can be reconstructed, but the scenario of reconstructing it on the
same context is complex.
Using a Visualization Grammar for this scenario is a key component, as these
grammars usually have extensions for interaction, chart layers, and multiple
views without requiring extra development effort.
This work presents a model for automated support for custom recognition, and
reconstruction of charts in images. The model automatically performs the
process steps, such as reverse engineering, turning a static chart back into its
data table for later reconstruction, while allowing the user to make modifications
in case of uncertainties. This work also features a model-based architecture
along with prototypes for various use cases. Validation is performed step by
step, with methods inspired by the literature. This work features three use
cases providing proof of concept and validation of the model.
The first use case features usage of chart recognition methods focused on
documents in the real-world, the second use case focus on vocalization of
charts, using a visualization grammar to reconstruct a chart in audio format,
and the third use case presents an Augmented Reality application that
recognizes and reconstructs charts in the same context (a piece of paper)
overlaying the new chart and interaction widgets. The results showed that with
slight changes, chart recognition and reconstruction methods are now ready for
real-world charts, when taking time, accuracy and precision into consideration.Os gráficos de dados são amplamente utilizados na nossa vida diária, estando
presentes nos meios de comunicação regulares, tais como jornais, revistas,
páginas web, livros, e muitos outros. Um gráfico bem construído leva a uma
compreensão intuitiva dos seus dados inerentes e da mesma forma, quando
os gráficos de dados têm escolhas de conceção erradas, poderá ser
necessário um redesenho destas representações. Contudo, na maioria dos
casos, estes gráficos são mostrados como uma imagem estática, o que
significa que os dados originais não estão normalmente disponíveis. Portanto,
poderiam ser aplicados métodos automáticos para extrair os dados inerentes
das imagens dos gráficos, a fim de permitir estas alterações. A tarefa de
reconhecer os gráficos e extrair dados dos mesmos é complexa, em grande
parte devido à variedade de tipos de gráficos e às suas características visuais.
As técnicas de Visão Computacional para classificação de imagens e deteção
de objetos são amplamente utilizadas para o problema de reconhecimento de
gráficos, mas apenas em imagens sem qualquer ruído. Outras características
das imagens do mundo real que podem dificultar esta tarefa não estão
presentes na maioria das obras literárias, como distorções fotográficas, ruído,
alinhamento, etc. Duas técnicas de visão computacional que podem ajudar
nesta tarefa e que têm sido pouco exploradas neste contexto são a deteção e
correção da perspetiva. Estes métodos transformam um gráfico distorcido e
ruidoso em um gráfico limpo, com o seu tipo pronto para extração de dados
ou outras utilizações. A tarefa de reconstrução de dados é simples, desde que
os dados estejam disponíveis a visualização pode ser reconstruída, mas o
cenário de reconstrução no mesmo contexto é complexo.
A utilização de uma Gramática de Visualização para este cenário é um
componente chave, uma vez que estas gramáticas têm normalmente
extensões para interação, camadas de gráficos, e visões múltiplas sem exigir
um esforço extra de desenvolvimento.
Este trabalho apresenta um modelo de suporte automatizado para o
reconhecimento personalizado, e reconstrução de gráficos em imagens
estáticas. O modelo executa automaticamente as etapas do processo, tais
como engenharia inversa, transformando um gráfico estático novamente na
sua tabela de dados para posterior reconstrução, ao mesmo tempo que
permite ao utilizador fazer modificações em caso de incertezas. Este trabalho
também apresenta uma arquitetura baseada em modelos, juntamente com
protótipos para vários casos de utilização. A validação é efetuada passo a
passo, com métodos inspirados na literatura. Este trabalho apresenta três
casos de uso, fornecendo prova de conceito e validação do modelo.
O primeiro caso de uso apresenta a utilização de métodos de reconhecimento
de gráficos focando em documentos no mundo real, o segundo caso de uso
centra-se na vocalização de gráficos, utilizando uma gramática de visualização
para reconstruir um gráfico em formato áudio, e o terceiro caso de uso
apresenta uma aplicação de Realidade Aumentada que reconhece e reconstrói
gráficos no mesmo contexto (um pedaço de papel) sobrepondo os novos
gráficos e widgets de interação. Os resultados mostraram que com pequenas
alterações, os métodos de reconhecimento e reconstrução dos gráficos estão
agora prontos para os gráficos do mundo real, tendo em consideração o
tempo, a acurácia e a precisão.Programa Doutoral em Engenharia Informátic
Fatores críticos de sucesso na gestão do conhecimento: um estudo de caso baseado na implementação de uma academia do conhecimento
Nowadays, knowledge is considered a key resource for organizations, crucial for obtaining long-term sustainable competitive. In line with this principle, many organizations are making efforts toward the implementation of knowledge management (KM) initiatives, recognizing that their competitive foundation lies in the effective way to capture, retain, store and share knowledge. Thus, this research aims to understand how organizations can implement KM initiatives, with a comprehensive study to identify critical success factors, and based on a practical project to implement a knowledge academy in a multinational organization. In order to achieve this objective, the adopted methodology in this research first went through a systematic literature review in order to identify the critical success factors with most influence on the implementation of KM practices. Then, based on the results found with this theoretical approach, it was possible to identify and analyse, in a practical context within a multinational company, the critical factors that contributed the most to the success of a knowledge academy implementation, a project in which the author of this study was involved. The results found suggest that factors related to the organization and people, such as the definition of a clear strategy, the definition of performance measures to evaluate and monitor the strategy, the involvement of top management, or even the organizational culture itself, represent some of the factors that have the most influence on the successful implementation of KM initiatives. With this research, it is expected to contribute from a theoretical perspective to the KM area through the compilation, categorization and classification of a set of critical success factors reported in the literature and subsequently analyzed and validated in a practical context. From a practical perspective, it is expected that these results can contribute as a consultative tool to support the preparation of strategies in this area by organizations wishing to implement KM initiatives.Atualmente o conhecimento é considerado um recurso chave para as organizações, crucial na obtenção de competitividade sustentável a longo prazo. Alinhado com este princípio, muitas organizações estão a fazer esforços no sentido de implementarem iniciativas de gestão do conhecimento (GC), reconhecendo que a sua base competitiva reside na forma eficaz de captar, reter, armazenar e partilhar conhecimento. Desta forma, o presente trabalho tem por objetivo compreender como as organizações podem implementar iniciativas de GC, elencando num estudo exaustivo de identificação de fatores críticos de sucesso, e tendo por base um projeto prático de implementação de uma academia de conhecimento numa organização multinacional. Por forma a alcançar tal objetivo, a metodologia adotada neste trabalho compreendeu, em primeiro lugar, uma revisão sistemática da literatura, de forma a identificar os fatores críticos de sucesso que mais influência têm na implementação de práticas de GC. Seguidamente, e tendo por base os resultados encontrados com esta abordagem teórica, foi possível identificar e analisar, num contexto prático no âmbito de uma empresa multinacional, os fatores críticos que mais contribuíram para o sucesso da implementação de uma academia de conhecimento, projeto onde a autora deste trabalho esteve envolvida. Os resultados encontrados sugerem que fatores relacionados com a organização e com as pessoas, tais como, a definição de uma estratégia clara, a definição de medidas de performance para avaliar e acompanhar a estratégia, o envolvimento da gestão de topo, ou mesmo a própria cultura organizacional, representam alguns dos fatores que mais influência têm na implementação bemsucedida de práticas e iniciativas de GC. Espera-se, assim, com este estudo, contribuir numa perspetiva teórica para a área da GC através da compilação, categorização e classificação de um conjunto de fatores críticos de sucesso reportados na literatura e, posteriormente, analisados e validados num contexto prático. Numa perspetiva prática, espera-se que estes resultados possam contribuir com uma ferramenta consultiva de apoio à preparação de estratégias nesta área, por parte das organizações que pretendam implementar iniciativas de GC.Mestrado em Engenharia e Gestão Industria
A Cross-cultural Comparative Study of Dark Triad and Five-Factor Personality Models in Relation to Prejudice and Aggression
When examining socially malevolent outcomes in the form of prejudice and aggression, previous research on the Dark Triad and five-factor personality models has failed to consider potential cross-cultural differences. A deeper understanding of cross-cultural variations is necessary because these factors represent important social problems and risks. Prior investigation has so far only established preliminary relationships between the Dark Triad and the Big Five model and these outlined associations influence prejudice and aggression. Accordingly, this thesis consisted of two phases. The first examined interrelationships between Dark Triad traits (psychopathy, narcissism, and Machiavellianism) and Big Five personality dimensions (extraversion, neuroticism, agreeableness, openness, conscientiousness) in UK and Russian samples. The second used the results from the initial phase to inform the baseline of a predictive model, which was extended. Both phases used cross-sectional designs, correlation-based methods of analysis (e.g., confirmatory factor analysis, structural equation modelling with mediation, path analysis and invariance analysis), and large samples, comprising a range of backgrounds and ages. The analysis identified the strongest and weakest relationships between personality traits and prejudice and aggression. This research made an original contribution to existing literature by identifying novel relationships
Graphical scaffolding for the learning of data wrangling APIs
In order for students across the sciences to avail themselves of modern data streams, they must first know how to wrangle data: how to reshape ill-organised, tabular data into another format, and how to do this programmatically, in languages such as Python and R. Despite the cross-departmental demand and the ubiquity of data wrangling in analytical workflows, the research on how to optimise the instruction of it has been minimal. Although data wrangling as a programming domain presents distinctive challenges - characterised by on-the-fly syntax lookup and code example integration - it also presents opportunities. One such opportunity is how tabular data structures are easily visualised. To leverage the inherent visualisability of data wrangling, this dissertation evaluates three types of graphics that could be employed as scaffolding for novices: subgoal graphics, thumbnail graphics, and parameter graphics. Using a specially built e-learning platform, this dissertation documents a multi-institutional, randomised, and controlled experiment that investigates the pedagogical effects of these. Our results indicate that the graphics are well-received, that subgoal graphics boost the completion rate, and that thumbnail graphics improve navigability within a command menu. We also obtained several non-significant results, and indications that parameter graphics are counter-productive. We will discuss these findings in the context of general scaffolding dilemmas, and how they fit into a wider research programme on data wrangling instruction
Novel strategies for the modulation and investigation of memories in the hippocampus
Disruptions of the memory systems in the brain are linked to the manifestation of many neuropsychiatric diseases such as Alzheimer’s disease, depression, and post-traumatic stress disorder. The limited efficacy of current treatments necessities the development of more effective therapies. Neuromodulation has proven effective in a variety of neurological diseases and could be an attractive solution for memory disorders. However, the application of neuromodulation requires a more detailed understanding of the network dynamics associated with memory formation and recall. In this work, we applied a combination of optical and computational tools in the development of a novel strategy for the modulation of memories, and have expanded its application for interrogation of the hippocampal circuitry underlying memory processing in mice.
First, we developed a closed-loop optogenetic stimulation platform to activate neurons implicated in memory processing (engram neurons) with a high temporal resolution. We applied this platform to modulate the activity of engram neurons and assess memory processing with respect to synchronous network activity. The results of our investigation support the proposal that encoding new information and recalling stored memories occur during distinct epochs of hippocampal network-wide oscillations.
Having established the high efficacy of the modulation of engram neurons’ activity in a closed-loop fashion, we sought to combine it with two-photon imaging to enable high spatial resolution interrogation of hippocampal circuitry. We developed a behavioral apparatus for head-fixed engram modulation and the assessment of memory recall in immobile animals. Moreover, through the optimization of dual color two-photon imaging, we improved the ability to monitor activity of neurons in the subfields of the hippocampus with cellular specificity. The platform created here will be applied to investigate the effects of engram reactivation on downstream projections targets with high spatial and cell subtype specificity.
Following these lines of investigations will enhance our understanding of memory modulation and could lead to novel neuromodulation treatments for neurological disorders associated with memory malfunctioning
Automaticity and executive abilities in developmental dyslexia: A theoretical review
Cognitive difficulties are well documented in developmental dyslexia but they present a challenge to dyslexia theory. In this paper, the Model of the Control of Action is proposed as a theoretical explanation of how and why deficits in both automaticity and executive abilities are apparent in the cognitive profiles of dyslexia and how these deficits might relate to literacy difficulties. This theoretical perspective is used to consider evidence from different cognitive domains. The neuroanatomical underpinnings of automaticity and executive abilities are then discussed in relation to the understanding of dyslexia. Links between reading, writing, and executive function are considered. The reviewed evidence suggests dyslexia theory should consider an interaction between procedural learned behaviour (automaticity) and higher-order (executive) abilities. The capacity to handle environmental interference, develop and engage adaptive strategies accordingly, and plan actions all require interactions between the cerebellum and the prefrontal cortex (PFC). Difficulties in these areas might explain both impairments in the cumulative development of literacy skills in childhood and general task management in everyday life in adulthood. It is suggested that improved measures are required to assess this cerebellar-PFC interaction and to allow early identification of future literacy difficulties, allowing implementation of timely interventions and reasonable adjustments
The Efficacy of Response to Intervention on Academic Outcomes at the Secondary School Level in a New England School District
Educational policies and practices have had a long-standing emphasis of conducting incoming literacy screenings to determine who is at risk for school failure. Response to intervention (RTI) is an intervention program designed to deliver educational resources to students who fall below what is deemed an acceptable level of proficiency as viewed through the early screening process. The goal of the program is to provide early mitigation in order to catch students up to their peers, and to limit misidentification into special education. Studies have evaluated the success of the program in grades K-3 and shown mixed success. However, there was no evidence found with respect to the long-term academic outcomes for students who participated in the program. The overarching question in this study asks: what impact does Response to Intervention (RTI) have on the academic placement of students at the secondary level? Specifically, does RTI promote academic mobility or produce no or little effect on a student’s academic placement at the secondary level? The study used a retrospective-longitudinal design to investigate the relationship between RTI participation in the primary grades and academic outcomes at the secondary level using the indicators of English track level placement, average track level placement, and weighted GPA. This quantitative study used multiple regression analysis, logistic regression, and chi-square hypothesis testing to compare the student outcomes from three schools in the same district, two of which used RTI and one that did not. The results showed that RTI students had no significant difference in English track level placement, average track level placement, and weighted GPA compared to the non-RTI students; students in RTI who were from low SES families and in special education were more likely to be in lower-level tracks, and low-SES students were over placed in both groups, but more significantly in the non-RTI group. The study also addressed the overlap between race, poverty, and special education disproportion as viewed through the conceptual framework of eugenics, cultural capital, and deficit perspectives. The outcomes of this study provide necessary research as to the effectiveness of RTI in relationship to student academic outcomes at the secondary level; the association between early intervention and long-term academic success; and a glimpse at how lower-resourced communities may be affected by the intervention. Recommendations are to conduct a larger and more comprehensive study at the national level; include cultural course work in teacher education programs that lead to culturally sustaining pedagogies; and conduct a comprehensive qualitative analysis of student perspectives
"Alien and Critical": The Modernist Satiric Practices of Djuna Barnes, Wyndham Lewis, and Virginia Woolf
This dissertation offers an extended analysis of the modernist satiric practices of authors Djuna Barnes, Wyndham Lewis, and Virginia Woolf in a selection of works spanning different genres published between 1913 and 1954. With these authors works as evidence, I suggest that satire undergoes a significant shift in the first half of the twentieth century as it departs from its premodern roots as a fixed genre or mode, instead becoming a diffuse element that intermittently shapes formal aspects and produces complex critiques. This shift partly results from new formulations of genderfrom altered understandings of masculinity and femininity to the emergence of what we now refer to as queer, nonbinary, and trans identitiesand the way in which what I call the instrumentality of satire enables a range of satiric attacks across different subject positions and a volatile political spectrum. Through a highly comparative approach, I draw upon formalist, feminist, and sociological theories to trace the different networks in which the texts of focus and their authors are embedded (networks of readers, artistic movements, political transformations, marketplaces, and discourses of gender and sexuality) to understand more thoroughly the satire that emerges from these texts. Each chapter pairs discrete investigations of works by each individual author, guided by an overarching topic (Chapter 1 explores networks of satire, Chapter 2 examines satiric method and the novel, and Chapter 3 considers satiric forms of life writing), and ends with a shorter section that compares the three authors works within a specific thematic framework (Chapter 1 with respect to the notion of authority, Chapter 2 through party scenes, and Chapter 3 concerning the portrait genre). My research reveals that the modernist satiric exchanges within these networks can be analyzed as, on the one hand, manifestations of the selected periods political dynamics and, on the other hand, cultural productions that altered how gender was discursively constructed within specific social environments of that period. In brief, the study illustrates how gender and its performance, aesthetics, and rhetoric become central to the production and function of satire in modernist art and literature
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