8,510 research outputs found

    Exploring the Training Factors that Influence the Role of Teaching Assistants to Teach to Students With SEND in a Mainstream Classroom in England

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    With the implementation of inclusive education having become increasingly valued over the years, the training of Teaching Assistants (TAs) is now more important than ever, given that they work alongside pupils with special educational needs and disabilities (hereinafter SEND) in mainstream education classrooms. The current study explored the training factors that influence the role of TAs when it comes to teaching SEND students in mainstream classrooms in England during their one-year training period. This work aimed to increase understanding of how the training of TAs is seen to influence the development of their personal knowledge and professional skills. The study has significance for our comprehension of the connection between the TAs’ training and the quality of education in the classroom. In addition, this work investigated whether there existed a correlation between the teaching experience of TAs and their background information, such as their gender, age, grade level taught, years of teaching experience, and qualification level. A critical realist theoretical approach was adopted for this two-phased study, which involved the mixing of adaptive and grounded theories respectively. The multi-method project featured 13 case studies, each of which involved a trainee TA, his/her college tutor, and the classroom teacher who was supervising the trainee TA. The analysis was based on using semi-structured interviews, various questionnaires, and non-participant observation methods for each of these case studies during the TA’s one-year training period. The primary analysis of the research was completed by comparing the various kinds of data collected from the participants in the first and second data collection stages of each case. Further analysis involved cross-case analysis using a grounded theory approach, which made it possible to draw conclusions and put forth several core propositions. Compared with previous research, the findings of the current study reveal many implications for the training and deployment conditions of TAs, while they also challenge the prevailing approaches in many aspects, in addition to offering more diversified, enriched, and comprehensive explanations of the critical pedagogical issues

    Data-to-text generation with neural planning

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    In this thesis, we consider the task of data-to-text generation, which takes non-linguistic structures as input and produces textual output. The inputs can take the form of database tables, spreadsheets, charts, and so on. The main application of data-to-text generation is to present information in a textual format which makes it accessible to a layperson who may otherwise find it problematic to understand numerical figures. The task can also automate routine document generation jobs, thus improving human efficiency. We focus on generating long-form text, i.e., documents with multiple paragraphs. Recent approaches to data-to-text generation have adopted the very successful encoder-decoder architecture or its variants. These models generate fluent (but often imprecise) text and perform quite poorly at selecting appropriate content and ordering it coherently. This thesis focuses on overcoming these issues by integrating content planning with neural models. We hypothesize data-to-text generation will benefit from explicit planning, which manifests itself in (a) micro planning, (b) latent entity planning, and (c) macro planning. Throughout this thesis, we assume the input to our generator are tables (with records) in the sports domain. And the output are summaries describing what happened in the game (e.g., who won/lost, ..., scored, etc.). We first describe our work on integrating fine-grained or micro plans with data-to-text generation. As part of this, we generate a micro plan highlighting which records should be mentioned and in which order, and then generate the document while taking the micro plan into account. We then show how data-to-text generation can benefit from higher level latent entity planning. Here, we make use of entity-specific representations which are dynam ically updated. The text is generated conditioned on entity representations and the records corresponding to the entities by using hierarchical attention at each time step. We then combine planning with the high level organization of entities, events, and their interactions. Such coarse-grained macro plans are learnt from data and given as input to the generator. Finally, we present work on making macro plans latent while incrementally generating a document paragraph by paragraph. We infer latent plans sequentially with a structured variational model while interleaving the steps of planning and generation. Text is generated by conditioning on previous variational decisions and previously generated text. Overall our results show that planning makes data-to-text generation more interpretable, improves the factuality and coherence of the generated documents and re duces redundancy in the output document

    The developing maternal-infant relationship: a qualitative longitudinal study

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    Aim The study aimed to explore maternal perceptions and the use of knowledge relating to their infant’s mental health over time using qualitative longitudinal research. Background There has been a growing interest in infant mental health over recent years. Much of this interest is directed through the lens of infant determinism, through knowledge regarding neurological development resulting in biological determinism. Research and policy in this field are directed toward individual parenting behaviours, usually focused on the mother. Despite this, there is little attention given to maternal perspectives of infant mental health, indicating that a more innovative approach to methodology is required. Methods This study took a qualitative longitudinal approach, and interviews were undertaken with seven mothers from the third trimester of pregnancy and then throughout the first year of the infant’s life. Interviews were conducted at 34 weeks of pregnancy, and then when the infant was 6 and 12 weeks, 6, 9, and 12 months, alongside the collection of researcher field notes—a total of 41 interviews. Data were analysed by creating case profiles, memos, and summaries, and then cross-comparison of the emerging narratives. A psycho-socially informed approach was taken to the analysis of data. Findings Three interrelated themes emerged from the data: evolving maternal identity, growing a person, and creating a safe space. The theme of evolving maternal identity dominated the other themes of growing a person and creating a safe space in a way that met perceived socio-cultural requirements for mothering and childcare practices. Participants’ personal stories give voice to their perceptions of the developing maternal-infant relationship in the context of their socio-cultural setting, relationships with others, and experiences over time. Conclusions This study adds new knowledge by giving mothers a voice to express how the maternal-infant relationship develops over time. The findings demonstrate how the developing maternal-infant relationship grows in response to their mutual needs as the mother works to create and sustain identities for herself and the infant that will fit within their socio-cultural context and individual situations. Additionally, the findings illustrate the importance of temporal considerations, social networks, and intergenerational relationships to this evolving process. Recommendations for practice, policy, and education are made that reflect the unique relationship between mother and infant and the need to conceptualise this using an ecological approach

    TOWARDS AN UNDERSTANDING OF EFFORTFUL FUNDRAISING EXPERIENCES: USING INTERPRETATIVE PHENOMENOLOGICAL ANALYSIS IN FUNDRAISING RESEARCH

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    Physical-activity oriented community fundraising has experienced an exponential growth in popularity over the past 15 years. The aim of this study was to explore the value of effortful fundraising experiences, from the point of view of participants, and explore the impact that these experiences have on people’s lives. This study used an IPA approach to interview 23 individuals, recognising the role of participants as proxy (nonprofessional) fundraisers for charitable organisations, and the unique organisation donor dynamic that this creates. It also bought together relevant psychological theory related to physical activity fundraising experiences (through a narrative literature review) and used primary interview data to substantiate these. Effortful fundraising experiences are examined in detail to understand their significance to participants, and how such experiences influence their connection with a charity or cause. This was done with an idiographic focus at first, before examining convergences and divergences across the sample. This study found that effortful fundraising experiences can have a profound positive impact upon community fundraisers in both the short and the long term. Additionally, it found that these experiences can be opportunities for charitable organisations to create lasting meaningful relationships with participants, and foster mutually beneficial lifetime relationships with them. Further research is needed to test specific psychological theory in this context, including self-esteem theory, self determination theory, and the martyrdom effect (among others)

    Post-Millennial Queer Sensibility: Collaborative Authorship as Disidentification in Queer Intertextual Commodities

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    This dissertation is examining LGBTQ+ audiences and creatives collaborating in the creation of new media texts like web shows, podcasts, and video games. The study focuses on three main objects or media texts: Carmilla (web series), Welcome to Night Vale (podcast), and Undertale (video game). These texts are transmedia objects or intertextual commodities. I argue that by using queer gestures of collaborative authorship that reaches out to the audience for canonical contribution create an emerging queer production culture that disidentifies with capitalism even as it negotiates capitalistic structures. The post-millennial queer sensibility is a constellation of aesthetics, self-representation, alternative financing, and interactivity that prioritizes community, trust, and authenticity using new technologies for co-creation. Within my study, there are four key tactics or queer gestures being explored: remediation, radical ambiguity and multi-forms as queer aesthetics, audience self-representation, alternative financing like micropatronage & licensed fan-made merchandise, and interactivity as performance. The goal of this project is to better understand the changing conceptions of authorship/ownership, canon/fanon (official text/fan created extensions), and community/capitalism in queer subcultures as an indicator of the potential change in more mainstream cultural attitudes. The project takes into consideration a variety of intersecting identities including gender, race, class, and of course sexual orientation in its analysis. By examining the legal discourse around collaborative authorship, the real-life production practices, and audience-creator interactions and attitudes, this study provides insight into how media creatives work with audiences to co-create self-representative media, the motivations, and rewards for creative, audiences, and owners. This study aims to contribute towards a fuller understanding of queer production cultures and audience reception of these media texts, of which there is relatively little academic information. Specifically, the study mines for insights into the changing attitudes towards authorship, ownership, and collaboration within queer indie media projects, especially as these objects are relying on the self-representation of both audiences and creatives in the formation of the text

    Um modelo para suporte automatizado ao reconhecimento, extração, personalização e reconstrução de gráficos estáticos

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    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

    Educating Sub-Saharan Africa:Assessing Mobile Application Use in a Higher Learning Engineering Programme

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    In the institution where I teach, insufficient laboratory equipment for engineering education pushed students to learn via mobile phones or devices. Using mobile technologies to learn and practice is not the issue, but the more important question lies in finding out where and how they use mobile tools for learning. Through the lens of Kearney et al.’s (2012) pedagogical model, using authenticity, personalisation, and collaboration as constructs, this case study adopts a mixed-method approach to investigate the mobile learning activities of students and find out their experiences of what works and what does not work. Four questions are borne out of the over-arching research question, ‘How do students studying at a University in Nigeria perceive mobile learning in electrical and electronic engineering education?’ The first three questions are answered from qualitative, interview data analysed using thematic analysis. The fourth question investigates their collaborations on two mobile social networks using social network and message analysis. The study found how students’ mobile learning relates to the real-world practice of engineering and explained ways of adapting and overcoming the mobile tools’ limitations, and the nature of the collaborations that the students adopted, naturally, when they learn in mobile social networks. It found that mobile engineering learning can be possibly located in an offline mobile zone. It also demonstrates that investigating the effectiveness of mobile learning in the mobile social environment is possible by examining users’ interactions. The study shows how mobile learning personalisation that leads to impactful engineering learning can be achieved. The study shows how to manage most interface and technical challenges associated with mobile engineering learning and provides a new guide for educators on where and how mobile learning can be harnessed. And it revealed how engineering education can be successfully implemented through mobile tools

    From wallet to mobile: exploring how mobile payments create customer value in the service experience

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    This study explores how mobile proximity payments (MPP) (e.g., Apple Pay) create customer value in the service experience compared to traditional payment methods (e.g. cash and card). The main objectives were firstly to understand how customer value manifests as an outcome in the MPP service experience, and secondly to understand how the customer activities in the process of using MPP create customer value. To achieve these objectives a conceptual framework is built upon the Grönroos-Voima Value Model (Grönroos and Voima, 2013), and uses the Theory of Consumption Value (Sheth et al., 1991) to determine the customer value constructs for MPP, which is complimented with Script theory (Abelson, 1981) to determine the value creating activities the consumer does in the process of paying with MPP. The study uses a sequential exploratory mixed methods design, wherein the first qualitative stage uses two methods, self-observations (n=200) and semi-structured interviews (n=18). The subsequent second quantitative stage uses an online survey (n=441) and Structural Equation Modelling analysis to further examine the relationships and effect between the value creating activities and customer value constructs identified in stage one. The academic contributions include the development of a model of mobile payment services value creation in the service experience, introducing the concept of in-use barriers which occur after adoption and constrains the consumers existing use of MPP, and revealing the importance of the mobile in-hand momentary condition as an antecedent state. Additionally, the customer value perspective of this thesis demonstrates an alternative to the dominant Information Technology approaches to researching mobile payments and broadens the view of technology from purely an object a user interacts with to an object that is immersed in consumers’ daily life
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