I den digitala utveckling som sker inom skolans värld använder eleverna datorn i allt större utsträckning när de producerar texter. Som en del i att skapa en vetenskaplig grund för att förstå hur digitala verktyg kan påverka textskapande är syftet med denna studie att undersöka på vilket sätt det medierande redskapet för att producera text, i detta fall tangentbord, skärm och ordbehandlingsprogram eller papper och penna, förändrar texters transitivitet och hur idéationella betydelser realiseras i de olika texttyperna. Studien ämnar även undersöka hur agentiviteten i texter förändras beroende på medierande redskap och vilka skillnader som det går att identifiera i nyttjandet av olika pronomen i agentiva processer. Tjugo texter skrivna av elever i årskurs 4 och 5 analyserades med utgångspunkt i systemisk funktionell textanalys och analysmetoderna transitivitetsanalys och ergativitetsanalys. Studiens resultat är inkonklusiva och ingen slutsats kan dras om skrivverktygens påverkan på texternas transitivitet eller agentivitet. Studien visar hur uppgiftbeskrivningar för elevers skolskrivande är mer avgörande för hur innehållet konstrueras än om de skriver för hand eller på datorn och bidrar med kunskap för vidare forskning. / In today’s developing digital era, students in school rely to an increasing extent when producing texts. As part of an effort to contribute to creating a scientific basis in regard to understanding how digital tools affects how text is constructed, this study aims to explore in which way the mediating tool for text production, in this case keyboard, screen, and word processing software versus paper and pen, changes the transitivity in texts and how ideational meaning is realised. Additionally, the study investigates how the ergativity in texts change depending on mediating tool and what differences in the use of pronouns can be identified in ergativ processes. Twenty texts written by fourth and fifth grade students are analysed based on Systemic-Functional text analysis and the analysis methods of transitivity analysis and ergativity analysis. The study’s results are inconclusive, providing no clear conclusions on the impact of writing tools on the transitivity or agency of texts. However, the study reveals that task descriptions for students' writing are more critical in shaping content than the choice between handwriting or typing, contributing valuable insights for further research.

This dissertation contains a study of the multitext manuscript Codex Holmiensis D 3 based in Material Philology and its focus on the material conditions underlying manuscripts. The aim of the investigation is to describe D 3 in order to increase understanding of its material conditions including content and circumstance of copying, as well as its use and purpose. D 3 contains 14 text works in different genres, for example romances, chronicles, and edifying works. The paper manuscript in the format of a holster book has been dated through its watermarks to around 1487/1488. It was written for the noblewoman Elin Gustavsdotter (Sture). An older manuscript, Codex Holmiensis D 4a, has previously been identified as the exemplar of D 3. These manuscripts are very similar as regards language and content. However, it is shown here that D 4a could not have been the model for D 3 in the case of the romance Flores och Blanzeflor; nor can the manuscript as a whole be a copy of D 4a. There are few traces of use in D 3, but the first work, Herr Ivan Lejonriddaren, has several concluding texts before its final closing. These concluding texts suggest that parts of the work were being read while the rest was being copied. There are also dual quire signatures in this work, implying that the quires were in disarray, possibly because they were in use when the signatures were added. The purpose of D 3 was to educate and provide examples of good and bad behaviour for the nobility. Moreover, there is an owner-epilogue which also stresses courtly ideals and can be linked to the concept of exemplary behaviour. The contents can also be ordered thematically, with first a Carolingian connection, followed by one connected with Ireland and finally one focused on the Christian community. Codicological breaks divide the manuscript into two parts, which leads to the assumption of at least two common exemplars for D 3 and D 4a. An emphasis on the materiality of the manuscript reveals it to be not so much an unwieldy collection of unrelated text witnesses as a book created for a certain person and her time. / <p>Felaktigt ISBN i den tryckta versionen: 978-91-506-2618-6</p>

Analysing handwritten texts and creating labelled data sets can facilitate novel research on languages and advanced computerized analysis of authors works. However, few handwritten works have word wise labelling or data sets associated with them. More often a transcription of the text is available, but without any exact coupling between words in the transcript and word representations in the document images. Can an algorithm be created that will take only an image of handwritten text and a corresponding transcript and return a partial alignment and data set? An algorithm is developed in this thesis that explores the use of a convolutional neural network trained on English handwritten text to be able to align some words on pages and create a data set given a handwritten page image and a transcript. This algorithm is tested on handwritten English text. The algorithm is also tested on Swedish shorthand, which was the inspiration for the development of the algorithm in this work. In testing on several pages of handwritten English text, the algorithm reaches an overall average classification of 68% of words on one page with 0% miss-classification of those words. On a sequence of pages, the algorithm reaches 84% correctly classified words on 10 pages and produces a data set of 551 correctly labelled word images. This after being shown 10 pages with an average of 70.6 words on each page, with0% miss-classification. / Analys av handskrivna texter och skapande av dataset kan främja ny forskning inom språk och avancerad datoranalys av olika författares verk. Det finns dock få handskrivna verk med information om vad varje handskrivet ord betecknar eller dataset relaterade till texten. Oftare finns en transkribering av texten, utan någon exakt koppling mellan de transkriberade orden och handskrivna ord i bilden av ett dokument. Genom att skapa en algoritm som kan ta tillvara handskrivna texter och motsvarande transkription kan potentiellt fler verk datoranalyseras. Kan en algoritm skapas som bara tar in en bild av ett handskrivet dokument och en motsvarande transkription och som returnerar en partiell placering av ord till ordbilder och ett dataset? En algoritm skapas i detta arbete som utforskar möjligheten att använda ett djupt neuralt nätverk tränat på engelsk handskriven text för att koppla ord i ett dokumentet till en transkription, och använda dessa för att skapa ett dataset. Denna algoritm är testad på engelsk handskriven text. Algoritmen testas också på svensk stenografi, vilket är inspirationen till skapandet av algoritmen. Algoritmen testades på ett antal sidor handskriven engelsk text. Där kunde algoritmen klassificera i genomsnitt 68% av orden på en handskriven sida med 0% av dessa ord felklassificerade. På en serie sidor når algoritmen en genomsnittlig klassificering av 84% klassificerade ord, och producerar ett dataset av 551 korrekt klassificerade ordbilder. Detta är efter att ha visat algoritmen 10 sidor med i snitt 70.6 ord per sida. I dessa test nåddes också en felklassificering på 0%.