I denna studie undersöker jag hur svenskämnet på gymnasiet lever upp till syftet som säger att eleverna i undervisningen ska få läsa andra texter än enbart skönlitterära och vars innehåll ska sättas i relation till elevernas egna intressen och erfarenheter. Texterna ska också vara en källa till självinsikt, utmana eleverna till nya tankesätt och öppna upp för nya perspektiv. Det blev därför intressant att undersöka om/hur texter av olika slag påverkar unga människors identitetsbyggande inom svenskämnet. Samtidigt visar tidigare forskning att skolan är dålig på att ta tillvara elevers medieerfarenheter i klassrummet. Syftet med studien är således att i intervjuer med nio elever undersöka hur elevernas medieerfarenheter ser ut och hur de vill att skolan ska tillvara på dessa: Hur använder eleverna medier för att uttrycka och utforska sin identitet? Hur ser eleverna på hur skolan tar tillvara deras medieerfarenheter i svenskundervisningen? Resultatet av undersökningen visar att svenskämnet i stort sett inte använder sig av texter hämtade från olika slags medieplattformar i undervisningen. De intervjuade eleverna däremot har stor kunskap om och erfarenhet från andra texter än de skönlitterära, bland annat on-linespel, bloggtexter och andra sociala medier, som de inhämtar på fritiden. I dessa forum utforskar de sin identitet. Resultatet visar att skolan sällan låter eleverna använda egna intressen i skoluppgifter. / This essay review the ways Swedish in upper secondary school carry out the tasks in the curriculum. The students ought to read other texts than fictional and the content are to be in relation to the students own interests and experiences. The texts should be a source of self-perception and challenge the students to think in new ways. That is why it became important to investigate if/how different texts affect young peoples searching for themselves within Swedish. At the same time research show that school is not taking care of the students prior encounters with media. The aim with this review is to examine nine students encounters with media and the ways they want the school to recognize these: In what ways do youth use media to express and explore their identity? What is the students opinion about the interest the Swedish take in their experiences in media? The issue of the survey shows that Swedish unfrequently use texts from different platforms of media. The students in the survey however have great knowledge about and experience from other texts than fictional - on-line games, blogs and other social media – acquired in their leisure time. In these rooms they explore their identity. The issue shows that school unfrequently let the students use their interests in instructions.

Thesis (MScEng) -- Stellenbosch University, 2014. / ENGLISH ABSTRACT: The increasing popularity of microblogging services such as Twitter means that more and more unstructured data is available for analysis. The informal language usage in these media presents a problem for traditional text mining and natural language processing tools. We develop a pre-processor to normalise this noisy text so that useful information can be extracted with standard tools. A system consisting of a tokeniser, out-of-vocabulary token identifier, correct candidate generator, and N-gram language model is proposed. We compare the performance of generative and discriminative probabilistic models for these different modules. The effect of normalising the training and testing data on the performance of a tweet sentiment classifier is investigated. A linear-chain conditional random field, which is a discriminative model, is found to work better than its generative counterpart for the tokenisation module, achieving a 0.76% character error rate compared to 1.41% for the finite state automaton. For the candidate generation module, however, the generative weighted finite state transducer works better, getting the correct clean version of a word right 36% of the time on the first guess, while the discriminatively trained hidden alignment conditional random field only achieves 6%. The use of a normaliser as a pre-processing step does not significantly affect the performance of the sentiment classifier. / AFRIKAANSE OPSOMMING: Mikro-webjoernale soos Twitter word al hoe meer gewild, en die hoeveelheid ongestruktureerde data wat beskikbaar is vir analise groei daarom soos nooit tevore nie. Die informele taalgebruik in hierdie media maak dit egter moeilik om tradisionele tegnieke en bestaande dataverwerkingsgereedskap toe te pas. ’n Stelsel wat hierdie ruiserige teks normaliseer word ontwikkel sodat bestaande pakkette gebruik kan word om die teks verder te verwerk. Die stelsel bestaan uit ’n module wat die teks in woordeenhede opdeel, ’n module wat woorde identifiseer wat gekorrigeer moet word, ’n module wat dan kandidaat korreksies voorstel, en ’n module wat ’n taalmodel toepas om die mees waarskynlike skoon teks te vind. Die verrigting van diskriminatiewe en generatiewe modelle vir ’n paar van hierdie modules word vergelyk en die invloed wat so ’n normaliseerder op die akkuraatheid van ’n sentimentklassifiseerder het word ondersoek. Ons bevind dat ’n lineêre-ketting voorwaardelike toevalsveld—’n diskriminatiewe model — beter werk as sy generatiewe eweknie vir tekssegmentering. Die voorwaardelike toevalsveld-model behaal ’n karakterfoutkoers van 0.76%, terwyl die toestandsmasjien-model 1.41% behaal. Die toestantsmasjien-model werk weer beter om kandidaat woorde te genereer as die verskuilde belyningsmodel wat ons geïmplementeer het. Die toestandsmasjien kry 36% van die tyd die regte weergawe van ’n woord met die eerste raaiskoot, terwyl die diskriminatiewe model dit slegs 6% van die tyd kan doen. Laastens het ons bevind dat die vooraf normalisering van Twitter boodskappe nie ’n beduidende effek op die akkuraatheid van ’n sentiment klassifiseerder het nie.

This thesis is conceived as a learning text, which deals with infinite numerical series. The thesis thematicaly results from curriculum for lectures of fourth therm's analysis for field called "Pedagogy of mathematics for secondary schools" on Pedagogical faculty by University of South Bohemia. It contains theoretical interpretation of basic concepts and theorems about infinite series, including of proofs of shown theorems, plenty of solved excersises, which show aplication of these concepts and theorems, and collection of excercises to study indipendently as well.

This diploma thesis is focused on description of methods for creating educational text and designing examples of spanish learning texts. In theoretical part I am describing The Common European Framework of Reference for Languages and its utilisation in process of creating educational texts. Beside that I am analyzing educational methods for language learning and influence of new technologies in educational process. At the end of the theoretical part I am describing main methods which are used for creating educational texts. Practical part is focused on creating certain examples of my own designed educational texts based on my conclusions from the teoretical part and my own experiences. My designed educational texts contain all of the important parts and go with my personal comments that explains my decisions. Designated educational text could be used as an example for creating another similar texts, because it contains all of the essencials.

This master thesis deals with the text analysis of cover letter in German and with identifying characteristic text structures of this text type. The theoretical part covers the main concepts of text linguistics. Based on the scientific literature are defined the basic outline for the text analysis. The practical part concerns the analysis of the corpus of 30 cover letters written by Czech candidates in compliance with the criteria for job application in supposed language German. After that, the communication context, textual theme, function and text structures significant for this text type are determined. Finally, the results are compared with the set hypotheses.

The complexity of text has a number of implications for educators in the areas of instruction and assessment. Text complexity is particularly important in formative assessments, which utilize repeated, alternate, equivalent forms to capture student growth towards a general outcome. A key assumption of such tools is that alternate forms of the assessment are of equal complexity. Consequently, there is a need to better understand what variables contribute to text complexity and how they impact student performance. This study was designed to evaluate features of text that are not typically included in readability estimates but may contribute to the text complexity: text cohesion and genre. Currently, text complexity of oral reading fluency measures is often quantified using readability estimates. It is hypothesized that a factor generally excluded from readability estimates, text cohesion&mdashthe extent to which the text functions as a cohesive, meaningful whole&mdashcontributes to text variability and variability in student performance. This research evaluated the role of a type of text cohesion (referential cohesion) in text complexity by manipulating the cohesion of passages otherwise assumed to be of equal difficulty. Genre was also considered, as research suggests that genre may impact complexity ratings of texts. Passages were strategically selecting to capture four conditions&mdash1) informational text/low cohesion, 2) informational text/high cohesion, 3) narrative text/low cohesion, and 4) narrative text/high cohesion. Data were collected on reading rate, accuracy, and passage-specific reading comprehension Results were analyzed using two-way, univariate ANOVA with dependent observations. Results indicate effects for each of the dependent variables included in the design. For rate and accuracy, results indicate significant interactions between genre and referential cohesion; scores were significantly higher for high cohesion narrative text than low cohesion narrative text and high cohesion informational text. There was a significant main effect of genre on comprehension, with students performing significantly better on the comprehension measure for narrative texts than informational texts. Altogether, these results indicate direct effects of genre and referential cohesion on student reading performance and provide evidence that text cohesion may be a meaningful component of text complexity. / 2015-10-10

A presente tese tem por objetivo investigar os efeitos do uso do minerador de textos Sobek no processo de leitura e compreensão textual de estudantes. Este minerador de textos é capaz de extrair informações relevantes de textos e representá-las de forma gráfica. Esta tese está apoiada nas teorias de aprendizagem significativa, de uso de mapas conceituais para representação de conhecimento e em pesquisas que apontam que representações gráficas de palavras auxiliam na leitura de textos e na sua decodificação. De acordo com a pesquisa de David Ausubel, a aprendizagem significativa ocorre através da assimilação de novos conceitos e ideias e associação destas ao conhecimento que a pessoa já possui. Através da utilização de um minerador de textos com representação gráfica de informações, busca-se apresentar aos estudantes uma representação visual de textos. Esta representação se assemelha a de um mapa conceitual, de forma a auxiliar no processo de compreensão e assimilação de informações pelos estudantes. Nesta representação, ligações entre termos considerados relevantes pelo minerador auxiliam no entendimento destes termos e simbolizam relações presentes no texto, fato esse que pode auxiliar os estudantes a compreenderem melhor o texto e relacionarem novas informações àquelas que já possuem Nesta tese, foi realizado um estudo para auxiliar estudantes nas atividades relacionadas ao letramento. A pesquisa se caracteriza como mista (qualitativa e quantitativa). A coleta de dados se deu a partir da aplicação de questionários com professores e alunos, além de avaliações com o objetivo de verificar contribuições do uso da ferramenta a partir de seu uso do ponto de vista do letramento. Como resultado, encontramos que estudantes que utilizaram o Sobek obtiveram um número mais elevado de respostas corretas nas atividades de interpretação de textos. Em média, os alunos acertaram 66% das questões quando utilizando o minerador de textos Sobek, contra apenas 47% das questões que eram respondidas sem o apoio do minerador. Outro resultado apresentado é o alto grau de satisfação de alunos e professores quanto à tecnologia e seu uso em sala de aula. Além destes resultados, obtivemos uma avaliação acerca da capacidade do minerador de textos de extrair termos considerados relevantes ao texto. / This thesis aimed to investigate the effects of using Sobek Text Miner to improve literacy. Sobek is a tool capable of extracting relevant information from texts and representing them in a graphical way. The thesis is supported by meaningful learning theory, conceptual maps theory and several research theories which indicate that graphical representation of words may improve reading capability and word decoding. According to David Ausubel, meaningful learning occurs through the assimilation of new concepts and ideas and association of those to what the person already knows. Using text mining with graphical representation of information, we seek to provide students with a graphical representation of a text. This text representation is similar to a concept map, helping students assimilate and comprehend that information. In Sobek’s representation, the relationship between terms considered relevant to text comprehension may assist students to better understand the meaning of each term and demonstrate relationships that are presented in the text, improving context comprehension. Furthermore, the relationship between terms may help information assimilation, once it relates the new information with previous known information This project conducted a study using Sobek text miner in classroom to support student’s literacy. In order to assess the tool’s possible benefits in reading and comprehension activities, we designed a series of classroom activities. To evaluate those activities, qualitative and quantitative approaches were used. The study was conducted in two primary schools, with students from 5th grade and 8th grade. Interviews were also made with the teachers and students, inquiring them about the tool's and main functions and its ability to help students from a literacy point of view. The study shows that students answered more correct question when using Sobek than when no support technology was used. Also, both students and teachers approved the software and agreed that it does improve student’s text comprehension. It also describes an evaluation of Sobek's capability to extract terms considered relevant for text comprehension.

abstract: Text Classification is a rapidly evolving area of Data Mining while Requirements Engineering is a less-explored area of Software Engineering which deals the process of defining, documenting and maintaining a software system's requirements. When researchers decided to blend these two streams in, there was research on automating the process of classification of software requirements statements into categories easily comprehensible for developers for faster development and delivery, which till now was mostly done manually by software engineers - indeed a tedious job. However, most of the research was focused on classification of Non-functional requirements pertaining to intangible features such as security, reliability, quality and so on. It is indeed a challenging task to automatically classify functional requirements, those pertaining to how the system will function, especially those belonging to different and large enterprise systems. This requires exploitation of text mining capabilities. This thesis aims to investigate results of text classification applied on functional software requirements by creating a framework in R and making use of algorithms and techniques like k-nearest neighbors, support vector machine, and many others like boosting, bagging, maximum entropy, neural networks and random forests in an ensemble approach. The study was conducted by collecting and visualizing relevant enterprise data manually classified previously and subsequently used for training the model. Key components for training included frequency of terms in the documents and the level of cleanliness of data. The model was applied on test data and validated for analysis, by studying and comparing parameters like precision, recall and accuracy. / Dissertation/Thesis / Masters Thesis Engineering 2016

Den här studien är en kritisk innehållsanalys gjord på tre läromedel för årskurs 6 i svenskämnet där genrepedagogik är en utgångspunkt. Syftet med studien är att analysera aktiviteter i varje läromedel. Det här för att synliggöra vilka möjligheter de erbjuder elever till att bli självständiga skribenter och därmed utveckla deras skrivförmåga. Studien utgår ifrån det sociokulturella perspektivet samt teorier om explicit skrivundervisning. Två texttyper i läromedlen, narrativ och argumenterande, har analyserats utifrån cirkelmodellen samt ytterligare bidragande aspekter som kan öka elevers skrivförmåga. Resultatet av analysen visar att samtliga läromedel erbjuder vissa möjligheter vid utvecklandet av elevers skrivförmåga. Samtliga läromedel kan kompletteras med ytterligare aktiviteter och material för att de ska bidra med goda förutsättningar för att utveckla elever till självständiga skribenter. Studiens slutsatser visar att lärarens kompetens om genrepedagogik och cirkelmodellen är en viktig aspekt. Det är därmed läraren som har den viktigaste rollen vid skapandet av meningsfulla undervisningstillfällen där innehållet i läromedlet kan vara en komponent att utgå ifrån.

A presente tese tem por objetivo investigar os efeitos do uso do minerador de textos Sobek no processo de leitura e compreensão textual de estudantes. Este minerador de textos é capaz de extrair informações relevantes de textos e representá-las de forma gráfica. Esta tese está apoiada nas teorias de aprendizagem significativa, de uso de mapas conceituais para representação de conhecimento e em pesquisas que apontam que representações gráficas de palavras auxiliam na leitura de textos e na sua decodificação. De acordo com a pesquisa de David Ausubel, a aprendizagem significativa ocorre através da assimilação de novos conceitos e ideias e associação destas ao conhecimento que a pessoa já possui. Através da utilização de um minerador de textos com representação gráfica de informações, busca-se apresentar aos estudantes uma representação visual de textos. Esta representação se assemelha a de um mapa conceitual, de forma a auxiliar no processo de compreensão e assimilação de informações pelos estudantes. Nesta representação, ligações entre termos considerados relevantes pelo minerador auxiliam no entendimento destes termos e simbolizam relações presentes no texto, fato esse que pode auxiliar os estudantes a compreenderem melhor o texto e relacionarem novas informações àquelas que já possuem Nesta tese, foi realizado um estudo para auxiliar estudantes nas atividades relacionadas ao letramento. A pesquisa se caracteriza como mista (qualitativa e quantitativa). A coleta de dados se deu a partir da aplicação de questionários com professores e alunos, além de avaliações com o objetivo de verificar contribuições do uso da ferramenta a partir de seu uso do ponto de vista do letramento. Como resultado, encontramos que estudantes que utilizaram o Sobek obtiveram um número mais elevado de respostas corretas nas atividades de interpretação de textos. Em média, os alunos acertaram 66% das questões quando utilizando o minerador de textos Sobek, contra apenas 47% das questões que eram respondidas sem o apoio do minerador. Outro resultado apresentado é o alto grau de satisfação de alunos e professores quanto à tecnologia e seu uso em sala de aula. Além destes resultados, obtivemos uma avaliação acerca da capacidade do minerador de textos de extrair termos considerados relevantes ao texto. / This thesis aimed to investigate the effects of using Sobek Text Miner to improve literacy. Sobek is a tool capable of extracting relevant information from texts and representing them in a graphical way. The thesis is supported by meaningful learning theory, conceptual maps theory and several research theories which indicate that graphical representation of words may improve reading capability and word decoding. According to David Ausubel, meaningful learning occurs through the assimilation of new concepts and ideas and association of those to what the person already knows. Using text mining with graphical representation of information, we seek to provide students with a graphical representation of a text. This text representation is similar to a concept map, helping students assimilate and comprehend that information. In Sobek’s representation, the relationship between terms considered relevant to text comprehension may assist students to better understand the meaning of each term and demonstrate relationships that are presented in the text, improving context comprehension. Furthermore, the relationship between terms may help information assimilation, once it relates the new information with previous known information This project conducted a study using Sobek text miner in classroom to support student’s literacy. In order to assess the tool’s possible benefits in reading and comprehension activities, we designed a series of classroom activities. To evaluate those activities, qualitative and quantitative approaches were used. The study was conducted in two primary schools, with students from 5th grade and 8th grade. Interviews were also made with the teachers and students, inquiring them about the tool's and main functions and its ability to help students from a literacy point of view. The study shows that students answered more correct question when using Sobek than when no support technology was used. Also, both students and teachers approved the software and agreed that it does improve student’s text comprehension. It also describes an evaluation of Sobek's capability to extract terms considered relevant for text comprehension.