This paper presents the results of a study of dyscalculia. It is a retrospective archival study implemented with a deductive approach. On the basis of established research and theory 18 analytical categories were formulated, before a deductive thematic analysis of empirical material, consisting of journal data of 17 students investigated for dyscalculia, 14 girls (82.4%) and 3 boys (17.6%). The purpose of this study was to investigate the relationship between the concepts formulated in research on dyscalculia and actual mathematical difficulties as those found in practice of students at school. All pupils had early and long-term difficulties with mathematics, while not showing any difficulties in other subjects. Most have had an unsatisfactory learning environment. All had normal intelligence but difficulty with certain cognitive, self-regulatory and linguistic features. Difficulties persisted despite numerous and protracted relief efforts at school. The study highlights that some difficulties are more prominent than others in connection with dyscalculia. This applies particularly to working memory, automation, activity control, spatial functions, certain linguistic abilities, concentration, and executive functions. Pedagogical action adaptation had been completed for most of the students but did not show to have any noticible effect. One question that requires further research would be “ why adaptation does not give the desired effect.” / I denna uppsats redovisas resultatet av en studie av dyskalkyli. Det är en retrospektiv arkivstudie med en deduktiv ansats som genomförts. Med utgångspunkt i etablerad forskning och teoribildning formulerades 18 analytiska kategorier, före en deduktiv tematisk analys, på ett empiriskt material bestående av journaldata för 17 elever utredda med avseende på dyskalkylidiagnos, 14 flickor (82,4 %) och 3 pojkar (17,6 %). Syftet med studien var att undersöka förhållandet mellan de begrepp forskningen formulerat om dyskalkyli och faktiska matematiksvårigheter så som sådana visar sig i praktiken hos elever i skolan. Samtliga elever hade tidiga och långvariga svårigheter i matematik, men vanligen inte i andra ämnen. De flesta hade haft en otillfredsställande inlärningsmiljö. Alla hade normal intelligens men svårigheter med vissa kognitiva, självreglerande och språkliga funktioner. Svårigheterna kvarstod trots många och långvariga hjälpinsatser i skolan. Studien lyfter fram att vissa svårigheter är mer framträdande än andra i samband med dyskalkyli. Det gäller framförallt arbetsminne, automatisering, aktivitetsreglering, spatiala funktioner, vissa språkliga förmågor, koncentration och exekutiva funktioner. Pedagogisk åtgärdsanpassning hade genomförts för de flesta av eleverna men verkade inte ha haft någon större effekt. Varför åtgärdsanpassning inte ger avsedd effekt är ett problem som behöver undersökas vidare.

abstract: While in recent years deep learning (DL) based approaches have been the popular approach in developing end-to-end question answering (QA) systems, such systems lack several desired properties, such as the ability to do sophisticated reasoning with knowledge, the ability to learn using less resources and interpretability. In this thesis, I explore solutions that aim to address these drawbacks. Towards this goal, I work with a specific family of reading comprehension tasks, normally referred to as the Non-Extractive Reading Comprehension (NRC), where the given passage does not contain enough information and to correctly answer sophisticated reasoning and ``additional knowledge" is required. I have organized the NRC tasks into three categories. Here I present my solutions to the first two categories and some preliminary results on the third category. Category 1 NRC tasks refer to the scenarios where the required ``additional knowledge" is missing but there exists a decent natural language parser. For these tasks, I learn the missing ``additional knowledge" with the help of the parser and a novel inductive logic programming. The learned knowledge is then used to answer new questions. Experiments on three NRC tasks show that this approach along with providing an interpretable solution achieves better or comparable accuracy to that of the state-of-the-art DL based approaches. The category 2 NRC tasks refer to the alternate scenario where the ``additional knowledge" is available but no natural language parser works well for the sentences of the target domain. To deal with these tasks, I present a novel hybrid reasoning approach which combines symbolic and natural language inference (neural reasoning) and ultimately allows symbolic modules to reason over raw text without requiring any translation. Experiments on two NRC tasks shows its effectiveness. The category 3 neither provide the ``missing knowledge" and nor a good parser. This thesis does not provide an interpretable solution for this category but some preliminary results and analysis of a pure DL based approach. Nonetheless, the thesis shows beyond the world of pure DL based approaches, there are tools that can offer interpretable solutions for challenging tasks without using much resource and possibly with better accuracy. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2019

Previous research showed that the use of laboratory materials, cooperative learning or rich mathematical problems promotes problem solving teaching and has a significant role in student learning. That is why the intention of this study was to investigate how the three concepts are used in problem solving teaching and how they can promote this type of mathematics teaching. In order to produce results for the purpose of the study, eight interviews were conducted with eight active primary school teachers to answer the following questions: 1) How do teachers describe their use of laboratory material, cooperative learning and rich mathematical problems in problem-solving teaching? 2) What opportunities and difficulties do teachers see with the use of these concepts? The results showed that the integration of laboratory material in the form of everyday materials, pedagogical materials and digital materials in problem solving teaching has a positive impact on students' problem solving skills and contributes to increased interest in mathematics teaching. It also appeared that the use of these materials enables the students to understand the abstract mathematical content in a clear way. The results of the study showed that the use of cooperative teaching is beneficial for students' development in problem solving. Through this way of working, the students' participation and activity in the classroom is strengthened and increased, which contributes to the students being able to achieve a desired result together. The results analysis clarified that the use of certain criteria for rich mathematical problems are important and necessary to be met in problem solving, while other criteria may be difficult to meet. But previous research showed that all seven criteria for rich math problems are necessary in problem solving tasks.