The survey is based on qualitative research interviews with four active teachers from primary school. The purpose of the study is to gain knowledge of how to work with reading and writing learning in year one. The study is based on four issues that concern the teachers' views on the early work on reading and writing. The result shows that teachers have slightly shared perceptions of specific educational material, but the foundation is to have a varied reading and writing teaching. The teaching should also be fun and stimulate the students' individual needs. / Studien baseras på kvalitativa forskningsintervjuer med fyra verksamma lärare som arbetar på lågstadiet. Syftet med studien är att få kunskap om hur man kan arbeta med läs- och skrivinlärning i årskurs 1. Studien utgår från fyra frågeställningar som berör lärarnas åsikter och synsätt på det tidiga arbetet med läs- och skrivinlärning. Resultatet visar att lärarna har aningen delade uppfattningar om specifikt undervisningsmaterial men att grunden är att ha en varierad läs- och skrivinlärning. Undervisningen ska dessutom vara lustfylld och stimulera elevernas individuella behov.

Syftet med intervjustudien är att beskriva några elevers känsla av begriplighet, hanterbarhet och meningsfullhet av sin skolvardag utifrån det särskilda stöd som ges i relation till språk, - läs – och skrivutveckling. Undersökningen utgår från ett elevperspektiv med fokus på elevernas upplevelser och uppfattningar av sin skolvardag kopplat till hinder och svårigheter de möter kring skoluppgifter de får i skolan. Samtliga intervjuade elever i studien går andra året på gymnasiet och har läs- och skrivsvårigheter, samt är i behov av särskilt stöd. Vår empiri är insamlad genom kvalitativa elevintervjuer som analyserats med hjälp av tematisk analys. Vi har i vår studie en teoretisk utgångspunkt i den salutogena teorin med fokus på KASAM (Antonovsky, 1987). Studiens resultat pekar på att det finns ett samband mellan elevernas känsla av sammanhang kopplat till upplevd stress, samt att elevernas känsla av begriplighet och hanterbarhet är tätt förknippade med varandra. Våra intervjuundersökningar visar att elevernas självbild påverkar hur de ser på de hinder och svårigheter som de möter i sin skolvardag. De ämnen som särskilt pekas ut som svåra att ta sig an av eleverna, är de ämnen som har ord och begrepp som ska förstås i ett särskilt sammanhang och ämnet svenska pekades ut flest gånger av informanterna. I resultaten framkommer även att det särskilda stöd som förekommer på gymnasiet, skiljer sig från det tidigare erbjudna stödet på högstadiet. De slutsatser som med hjälp av denna kvalitativa studie kan dras, är att samtliga intervjuade elever beskriver en bild av det särskilda stödet på gymnasiet som varken tillgängligt eller utformat på rätt sätt, för att de ska kunna uppleva en känsla av sammanhang av sin skolvardag. Detta skapar i sin tur en frustration och en känsla av otillräcklighet hos eleverna, då det ofta bli de själva som får föra fram sina stödbehov och strida för att få tillgång till det stöd de har rätt till. Eleverna beskriver också att lärarna på gymnasiet inte har tillräcklig kunskap gällande stödbehovet kopplat till deras faktiska svårigheter. Ytterligare en slutsats som vi utifrån vår analys kan dra, är att samtliga elever uttrycker ett behov av stöd utanför klassrummet i en lugn miljö, vilket är i motsats till vad tidigare forskning kommit fram till. Sammanfattningsvis kan sägas att vår slutsats blir att utifrån våra intervjuanalyser konstatera att det finns ett samband mellan KASAM och hur eleverna hanterar sin skolvardag och de uppgifter de får. Att begripa vad som förväntas och på så sätt hantera sin situation tolkas utifrån vår studie som avgörande för att få till en fungerande kunskapsutveckling och ett bra mående utan stress. Att kunna skapa en skoltillvaro med meningsfullhet och begriplighet verkar vara avgörande för hur eleverna lyckas med att få till en känsla av sammanhang av sin skoltillvaro.

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2017-10-02T15:28:01Z No. of bitstreams: 2 Dissertação - Mateus Ferreira e Freitas - 2017.pdf: 4269845 bytes, checksum: e84e69d8747a21125170793812384a98 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2017-10-02T15:30:07Z (GMT) No. of bitstreams: 2 Dissertação - Mateus Ferreira e Freitas - 2017.pdf: 4269845 bytes, checksum: e84e69d8747a21125170793812384a98 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-10-02T15:30:07Z (GMT). No. of bitstreams: 2 Dissertação - Mateus Ferreira e Freitas - 2017.pdf: 4269845 bytes, checksum: e84e69d8747a21125170793812384a98 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-08-30 / Several applications process documents in different ways, aiming to filter, organize or learn with them. Nowadays, a great computational power is necessary in order to do that efficiently, due to the large and increasing number of documents. Usually, documents are independent of each other, which facilitates the use of parallelism to speed up this processing. This work explores three problems: active learning, learning to rank (L2R) and top-k search. Using the parallelism on multicore CPUs and manycore GPUs (Graphics Processing Unit), parallel algorithms were proposed and evaluated for each problem, and implemented with the OpenMP and CUDA APIs. For the active learning problem a multicore algorithm was proposed, which obtained 10.8x of speedup in the best case with 12 threads. The proposed manycore version obtained 128x of speedup over the serial version, and a solution with 4 GPUs achieved 3.5x of speedup over 1 GPU. For the L2R problem a manycore algorithm was proposed, which follows a thread-block approach using the concept of Combinadic, and uses a cache with fingerprint to speed up the processing. The best case speedups were 508x over the serial, 9x over a GPU baseline, and 4x over our solution when using 4 GPUs. When comparing with a version without combinadic, the speedup over it was 4.4x with both versions using 1 GPU and 3.9x with 4. These solutions used bitmap structures to speed up the association rules creation. In the top-k search a serial and multicore solutions were implemented from a state of the art manycore algorithm for exact searches. These implementations served as baselines for our extension of this algorithm, which includes the use of multi-GPU, group searches and an intra-block load balancing. The speedups were 2.7x over the original algorithm, 17x over the serial, 4x over the multicore, and 4x over our version when using 4 GPUs. / Diversas aplicações processam documentos de diferentes maneiras, visando filtrá-los, organizá-los ou aprender com eles. Atualmente, é necessário um grande poder computacional para que isso seja feito eficientemente, devido ao número grande e crescente de documentos. Geralmente os documentos são independentes entre si, o que facilita o uso de paralelismo para acelerar esse processamento. Este trabalho explora três problemas: aprendizado ativo, learning to rank (L2R) e busca top-k. Usando o paralelismo em CPUs multicore e GPUs (Graphics Processing Unit) manycore, algoritmos paralelos foram propostos e avaliados para cada problema, e implementados com as APIs OpenMP e CUDA. Para problema de aprendizado ativo foi proposto um algoritmo multicore, que obteve speedup de 10,8x no melhor caso com 12 threads. A versão manycore proposta obteve speedup de 128x em relação ao serial, e uma solução com 4 GPUs atingiu 3,5x de speedup sobre 1 GPU. Para o problema de L2R foi proposto um algoritmo manycore, que segue uma abordagem por bloco de threads} usando o conceito de Combinadic, e usa uma cache} com fingerprint para acelerar o processamento. Os speedups nos melhores casos foram de 508x sobre o serial, 9x sobre uma baseline em GPU, e 4x sobre nossa solução com 1 GPU ao usar 4 GPUs. Ao comparar com uma versão sem o combinadic, o speedup sobre ela foi de 4,4x com ambas versões usando 1 GPU e 3,9x usando 4. Estas soluções usaram estruturas de mapa de bits para acelerar a criação de regras de associação. Na busca top-k foram implementadas uma solução serial e uma multicore de um algoritmo manycore estado da arte para buscas exatas. Estas implementações serviram de baseline para nossa extensão desse algoritmo, que inclui o uso de multi-GPU, buscas em grupos e um balanceamento de carga intra-bloco. Os speedups obtidos foram de 2,7x sobre o algoritmo original, 17x sobre o serial, 4x sobre o multicore, e 4x sobre nossa versão ao usar 4 GPUs.

In view of the new compulsory assessment support and the added learning requirements in the curriculum, the aim of this study is to investigate how teachers work with teaching reading and writing in grade 1 in relation to the method used in the school. The study uses interviews as a method to answer the questions. The result shows that both schools use a combination of methods in the teaching of reading and writing. The teachers who took part in the study are favourably inclined to the new assessment support and hope that more follow-ups of the pupils’ results can mean that resources are provided earlier for those who need it. The teachers have differing opinions about changes in teaching taking place in connection with changes or additions to the curriculum. The crucial factor appears to be how great the changes are or what the additions concern, and how they relate to existing methods.

Syftet med studien är att undersöka hur lärare använder sig av högläsning i undervisning för att främja elevernas läsförmåga och hur detta syns i elevernas aktiviteter. Teorin som studien bygger på är det sociokulturella perspektivet med ursprung i Lev Vygotskijs teorier om lärande, utveckling och språk. I studien har fem lärare som arbetar i årskurserna F–3 blivit intervjuade med en semistrukturerad intervju. Lärarna har även blivit observerade under en av sina högläsningslektioner för att se hur de använder sig av högläsning för att utveckla elevernas läsförmåga. Resultatet visar att lärarna försöker använda sig av högläsning dagligen i sin undervisning då de anser att den ger väldigt mycket. Lärarna anser att högläsningen utvecklar elevernas ordförråd, läsförståelse, läslust och koncentrationsförmåga. Utifrån observationerna, tidigare forskning och lärarnas intervjuer visar resultatet även att lärarna använder sig av olika arbetssätt och metoder för att eleverna ska få möjlighet att utveckla sin läsförmåga. / The purpose of this study is to examine some teachers' view of the effect of read-alouds on the development of pupils' reading skills, as well as the opportunities the pupils get to develop their reading skills in teacher practices of reading aloud. The study is based on the sociocultural perspective originating in Lev Vygotsky theories on learning, development and language. In this study, five teachers working in preschool and grades 1–3 have been interviewed using qualitative interviews. Teachers have also been observed during one of their read-aloud lessons in order to see how they use reading aloud to develop pupils' reading skills. The results show that the teachers try to read aloud daily in their teaching because they find it has great advantages. The teachers believe that reading aloud develops pupils' vocabulary, reading comprehension, love of reading and concentration. Based on previous research, observation and teacher interviews, the results also show that teachers use approaches to and methods for giving their pupils opportunity to develop their reading skills.

Siekimas užtikrinti geresnį mokinių mokymąsi tapo pagrindiniu Lietuvos švietimo sistemos iššukiu. Mokėjimo mokytis kompetencija apima mokymosi kaip vertingo ir visą gyvenimą trunkančio proceso sampratą, mokėjimą kelti ir įgyvendinti mokymosi tikslus bei būti atsakingu už savo mokymosi rezultatus. Vis dažniau yra vartojama kompetencijos samprata švietimo kontekste, pateikiamos įvairios šios sąvokos interpretacijos Lietuvos ir užsienio mokslininkų. Tyrimo tikslas: Atskleisti mokymosi mokytis kompetencijos ugdymo vadybinus aspektus pagrindinėje mokykloje. Tyrimo uždaviniai: 1.Atlikti mokslinės literatūros analizę apie mokėjimo mokytis kompetenciją, išryškinant konstruktyvistinį jos pobūdį. 2. Atskleisti mokytojų požiūrį į metodologines ir metodines mokėjimo mokytis kompetencijos ugdymo prielaidas.3.Ištirti mokyklos vadovų požiūrį į planavimo vaidmenį ugdant mokinių mokėjimo mokytis kompetencijas. 4.Atskleisti mokytojų ir mokyklos vadovų požiūrį į mokėjimo mokytis kompetencijos ugdymą . Tyrimo metodai: Mokslinės literatūros ir švietimo dokumentų analizė; Ankėtinė mokytojų ir vadovų apklausa; Interviu su mokyklos vadovu; Statistinė empirinių duomenų analizė. Tyrimo imtis. 162 respondentai: 60 vadovų ir 102 Vilniaus miesto pagrindinių mokyklų mokytojai. Išvados: 1.Teorinės mokslinės literatūros įžvalgos parodė, kad šiuolaikinėje didaktikoje, vis labiau įsigalint konstruktivystinei paradigmai, keičiasi požiūris į... [toliau žr. visą tekstą] / Striving for better learning for all pupils and doing it in the most effective and efficient way has become a priority for Lithuania’s educational system. The learning to learn competence is considered to be the most important and valuable concept in today‘s education. The present school headmaster, managers and all the teachers are facing high demands in today‘s education for they are responsible for the crucial aspects improving students’ competence of learning abilities to learn i. e planning, organizing, staffing, leading, and controlling the whole domain. The Aim: To investigate the managerial aspects of learning to learn competence at secondary school. Objectives: 1. To analyze the learning to learn competence in scientific literature, highlightning its constructivist features .2. To investigate teachers' methodical and methodological attitudes to the development of learning to learn competence 3. To investigate the school principals‘ attitude to planning as one of the aspects to develop students‘ learning to learn competence. 4. To reveal teachers‘ and school principals‘ approach to learning to learn competence educational assumptions. Methods used: The analysis of science literature and the survey of standard acts; questionnairing teachers and school principals‘ , statistic analysis of empiric data. Sampling:162 respondents (102 teachers and 60 school principals) from schools in Vilnius... [to full text]

Thesis advisor: Patrick J. McQuillan / Most would agree that pupil learning is a fundamental purpose of schooling. Differences arise, however, when conceptualizing what form that learning should take and how it should be assessed. In recent years, there has been increased pressure to improve pupil achievement through educational reform initiatives intended to ensure that all pupils meet high academic standards through strict accountability measures. This dissertation seeks to understand how teacher candidates/beginning teachers, working in this era of accountability, focus on pupil learning over time. An interpretive qualitative approach was employed to complete cross-case analyses on 55 interviews conducted with five participants over a 3-year period. Based on a sociocultural framework, and drawing on constructivist assessment theories and prior research on learning to teach, this dissertation argues that the end objective of improving pupil learning led teachers to enhance their teaching practice by holding high expectations for pupil learning, building personal relationships with pupils, maintaining strong classroom management strategies, and utilizing formative assessment practices. However, engaging in these practices was often a result of a complex process of negotiation between aspects of the school context that functioned as obstacles and the teachers' moral sensibilities Overall, contrary to claims made by stage theory, the beginning teachers in this study demonstrated that focusing on pupil learning was possible with perseverance, commitment to social justice, development of an inquiry stance and an understanding that learning to teach is a life-long process that involves continuous reflection and professional development. / Thesis (PhD) — Boston College, 2009. / Submitted to: Boston College. Lynch School of Education. / Discipline: Teacher Education, Special Education, Curriculum and Instruction.

Este trabalho avalia o desempenho do uso de árvores de decisão como função de ordenação para documentos e pessoas em ambientes empresariais. Para tanto, identificouse atributos relevantes das entidades a serem recuperadas a partir da análise de: (i) dinâmica de produção e consumo de informações em um ambiente empresarial; (ii) algoritmos existentes na literatura para a recuperação de documentos e pessoas; e (iii) conceitos utilizados em funções de ordenação para domínios genéricos. Montou-se um ambiente de avaliação, utilizando a coleção de referência CERC, para avaliar a aplicabilidade do algoritmo C4.5 na obtenção de funções de ordenação para o domínio empresarial. O uso do algoritmo C4.5 para a construção de funções de ordenação mostrou-se parcialmente efetivo. Para a tarefa de recuperação de documentos não trouxe resultados bons. Porém, constatou-se que é possível controlar a forma de construção da função de ordenação a fim de otimizar a precisão nas primeiras posições do ranking ou otimizar a média das precisões (MAP). Para a tarefa de recuperação de pessoas o algoritmo C4.5 obteve uma árvore de decisão que consegue resultados melhores que todas as outras funções de ordenação avaliadas. OMAP obtido pela árvore de decisão foi 0, 83, enquanto que a média do MAP das outras funções de ordenação foi de 0, 74. Percebeu-se que a árvore de decisão utilizada para representar a função de ordenação contribui para a compreensão da composição dos diversos atributos utilizados na caracterização dos documentos e pessoas. A partir da análise da árvore de decisão utilizada como função de ordenação para pessoas foi possível entender que uma pessoa é considerada especialista em algum tópico se ela aparecer em muitos documentos, aparecer muitas vezes nos documentos e os documentos onde aparece têm uma relevância alta para a consulta. / This work evaluates the performance of using decision trees as ranking functions for documents and people in enterprises. It was identified relevant attributes of the entities to be retrieved from the analysis of: (i) the production and consumption of information behavior in an enterprise, (ii) algorithms for documents and people retrieval at literature, and (iii) the concepts used in ranking functions for generic domains. It was set up an evaluation environment, using the CERC collection, to evaluate the applicability of the C4.5 algorithm to obtain a ranking function for the enterprise domain. The use of C4.5 algorithm for the construction of ranking function was proved to be partially effective. In the case of documents retrieval the C4.5 has not found good results. However, it was found that is possible to control the way of building the ranking function in order to optimize the precision in the first positions of the ranking or optimize the mean average precision (MAP). For the task of people retrieval the C4.5 algorithm developed a ranking function that obtain better results than all other ranking functions assessed. The value of MAP obtained by decision tree was 0, 83, while the average MAP of other ranking functions was 0, 74. The decision tree used to represent the ranking function contributes to understanding the attributes composition used in the characterization of documents and people. Through the analysis of the decision tree used as ranking function for people, we could realise that a person is considered expert in any topic if he/she appear in many documents, appear many times in same documents and documents where he/she appears have a high relevance to the query.

We study the problem of embedding high-dimensional visual data into low-dimensional vector representations. This is an important component in many computer vision applications involving nearest neighbor retrieval, as embedding techniques not only perform dimensionality reduction, but can also capture task-specific semantic similarities. In this thesis, we use deep neural networks to learn vector embeddings, and develop a gradient-based optimization framework that is capable of optimizing ranking-based retrieval performance metrics, such as the widely used Average Precision (AP) and Normalized Discounted Cumulative Gain (NDCG). Our framework is applied in three applications. First, we study Supervised Hashing, which is concerned with learning compact binary vector embeddings for fast retrieval, and propose two novel solutions. The first solution optimizes Mutual Information as a surrogate ranking objective, while the other directly optimizes AP and NDCG, based on the discovery of their closed-form expressions for discrete Hamming distances. These optimization problems are NP-hard, therefore we derive their continuous relaxations to enable gradient-based optimization with neural networks. Our solutions establish the state-of-the-art on several image retrieval benchmarks. Next, we learn deep neural networks to extract Local Feature Descriptors from image patches. Local features are used universally in low-level computer vision tasks that involve sparse feature matching, such as image registration and 3D reconstruction, and their matching is a nearest neighbor retrieval problem. We leverage our AP optimization technique to learn both binary and real-valued descriptors for local image patches. Compared to competing approaches, our solution eliminates complex heuristics, and performs more accurately in the tasks of patch verification, patch retrieval, and image matching. Lastly, we tackle Deep Metric Learning, the general problem of learning real-valued vector embeddings using deep neural networks. We propose a learning to rank solution through optimizing a novel quantization-based approximation of AP. For downstream tasks such as retrieval and clustering, we demonstrate promising results on standard benchmarks, especially in the few-shot learning scenario, where the number of labeled examples per class is limited.

Submitted by Roberto Fonseca (rcf2@icomp.ufam.edu.br) on 2018-11-18T00:36:14Z No. of bitstreams: 2 rcidadef-final-dissertacao-mestrado.pdf: 998750 bytes, checksum: 1738deb5326e881be7192f444ccedb86 (MD5) 315 ATA de Defesa - Roberto Cidade (Assinada).pdf: 531920 bytes, checksum: 51157459356b7ee8be9be278b4579378 (MD5) / Approved for entry into archive by Secretaria PPGI (secretariappgi@icomp.ufam.edu.br) on 2018-11-19T17:31:42Z (GMT) No. of bitstreams: 2 rcidadef-final-dissertacao-mestrado.pdf: 998750 bytes, checksum: 1738deb5326e881be7192f444ccedb86 (MD5) 315 ATA de Defesa - Roberto Cidade (Assinada).pdf: 531920 bytes, checksum: 51157459356b7ee8be9be278b4579378 (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2018-11-19T19:46:24Z (GMT) No. of bitstreams: 2 rcidadef-final-dissertacao-mestrado.pdf: 998750 bytes, checksum: 1738deb5326e881be7192f444ccedb86 (MD5) 315 ATA de Defesa - Roberto Cidade (Assinada).pdf: 531920 bytes, checksum: 51157459356b7ee8be9be278b4579378 (MD5) / Made available in DSpace on 2018-11-19T19:46:24Z (GMT). No. of bitstreams: 2 rcidadef-final-dissertacao-mestrado.pdf: 998750 bytes, checksum: 1738deb5326e881be7192f444ccedb86 (MD5) 315 ATA de Defesa - Roberto Cidade (Assinada).pdf: 531920 bytes, checksum: 51157459356b7ee8be9be278b4579378 (MD5) Previous issue date: 2018-08-28 / Machine learning (ML) based ranking functions generating methods have been broadly used on web search systems, such as the utilized by Google and Bing. Nonetheless, such methods have not been employed or studied in other contexts. It is the case, to cite an example, of electronic commerce (e-commerce), on which the user interaction with virtual stores produces data as: when an user landed on a page for the first time, queries submitted, products clicked and what she bought. In this work, we propose to leverage ML to learn ranking functions for the e-commerce context. We studied alternatives to estimate the relevance of a result for a given query and deployed experiments using data mined from e-commerce shops. We ran experiments in setups we denominated offline, where a dataset was created the traditional way by separating it in three subsets of training, validation and test, as well as in setups we denominated online, where distinct versions of the system were deployed to shops facing users in a real purchase situation. We present in the study our conclusions regarding the performed experiments. / Métodos que geram funções de ordenação de resultados baseadas em aprendizagem de máquina têm sido amplamente utilizados em sistemas de busca para a web, como as utilizadas em motores de busca como o Google e Bing. No entanto, esses recursos não têm sido muito empregados ou estudados em outros contextos. É o caso, por exemplo, do comércio eletrônico, no qual, a interação de usuários com lojas virtuais produz dados como: quando um usuário acessou a página de uma loja pela primeira vez, que consultas realizou, quais produtos clicou, e o que comprou. Neste trabalho, propomos a utilização de métodos de aprendizagem de máquina para aprender funções de ordenação de resultados no contexto de comércio eletrônico. Estudamos formas alternativas de estimar a relevância de um resultado para uma dada consulta e realizamos experimentos utilizando dados extraídos de lojas de comércio eletrônico. Realizamos experimentos tanto com ambientes que denominamos offline, onde uma base de dados é montada com a abordagem tradicional de separa-la em treino, validação e teste, quanto em ambientes que denominamos online, onde pusemos versões distintas dos sistemas para funcionar em lojas com usuários em situações reais de compra. Apresentamos no estudo nossas conclusões a respeito dos experimentos realizados. / Formulário longo, com várias fases e páginas.