This thesis examined the sensitivity of the EQ-5D-5L instrument in measuring health-related quality of life (HRQoL) among patients with persistent symptoms following COVID-19, including fatigue, memory and concentration problems, and dyspnea. Additionally, it was analyzed whether adding these symptoms to the EQ-5D-5L improved the explained variance for HRQoL. Patients from Uppsala University Hospital, Sweden, answered a survey that included questions on five dimensions of health represented by the EQ-5D-5L and an additional question on general health score called EQ-VAS. Multiple linear regression, Spearman’s rank correlation coefficient, and Least Absolute Shrinkage and Selection Operator (LASSO) were used to examine the sensitivity of the EQ-5D-5L. For the explanatory analysis, the Adjusted 𝑅2 was used to evaluate explanatory power with and without the presence of the symptoms. The results showed that the EQ-5D-5L dimensions explained a moderate proportion of the variance for fatigue and memory/concentration problems and a weak proportion for dyspnea. The explanatory analysis provided findings that fatigue significantly improved the explained variance of EQ-VAS by 5.5%, adding memory/concentration problems only improved it marginally, and adding dyspnea was non-significant. Additionally, strong to moderate correlations between fatigue and memory/concentration problems were found with multiple dimensions of the EQ-5D-5L. These findings suggest that the EQ-5D-5L instrument may be a valuable tool in assessing HRQoL in patients with persistent COVID-19 symptoms and that adding fatigue to the EQ-5D-5L could be beneficial for improving explanatory power to HRQoL in patients suffering from infectious disease. / COMBAT post-covid

The purpose of this study is to investigate physics teachers’ (TPCK) and their learners’ achievement in electricity. A purposive sample of 42 Grade 11 physics teachers and 1423 learners participated in the study. An explanatory mixed method research design was employed in the study to collect data. A survey questionnaire (PTTPCKQ), consisting of six-point Likert scale questions, was answered by participating teachers. Similarly, their learners responded to a confirmatory questionnaire (LCPTTPCKQ). The learners also responded to the Electricity Learning Confirmatory Questionnaire (LELCQ) and wrote an achievement test called Learner Electricity Achievement Test (LEAT). The data collected was analysed both quantitatively and qualitatively. Quantitatively, it was found that a positive, statistically significant relationship existed between physics teachers’ experience and their learners’ achievement [Spearman’s rho (42) = .39, p = .011] as well as physics teachers’ TPCK and their qualifications [Spearman’s rho (42) = .33, p = .003]. There was also a positive statistical relationship between physics teachers’ TPCK and learner achievement, yet this was not statistically significant. There were positive, statistically significant relationships between all the constructs of the physics teachers’ TPCK and their TPCK from the analysis of the PTTPCKQ. There were positive statistically significant relationships between all the constructs of the physics teachers’ TPCK and their TPCK, according to the analysis of the LCPTTPCKQ. Furthermore, comparing the learners’ responses on the LCTTPCKQ and their teachers’ responses on the PTTPCKQ, it was found that both learners and teachers provided similar responses for all the constructs of TPCK except TCK. Qualitative data analysis further revealed that the technologies used by these teachers were PhET Simulations, YouTube Videos, Power Point Presentations, Interactive White Boards, and Mindset Videos. Finally, between 12.9% and 5.2% of the learners reported that their teachers had neglected to teach some sections of the electricity in the curriculum. / Mathematical Sciences / Ph. D. (Mathematics, Science and Technology Education)

Reading and mathematics are two essential subjects for academic success and cognitive development. Several studies show a correlation between the reading ability and mathematical ability of pupils (Korpershoek et al., 2015; Ní Ríordáin & O’Donoghue, 2009; Reikerås, 2006; Walker et al., 2008). The didactical part of this thesis presents a study investigating a correlation between reading ability and mathematical ability among pupils in upper secondary schools in Sweden. This study collaborated with Lexplore AB to use machine learning and eye-tracking to measure reading ability. Mathematical ability was measured with Mathematics 1c grades and Stockholmsprovet, which is a diagnostic mathematics test. Although no correlation was found, there are several insights about selection and measures following the result that may improve future studies on the subject. This thesis finds that the result could have been affected by a biased selection of the participants. This thesis also suggests that the measure through machine learning and eye-tracking used in the study may not fully capture the concept of reading ability as defined in previous studies. The technological aspect of this thesis focuses on modifying and improving the model used to calculate users’ reading ability scores. As the model’s estimation tends to plateau after the fifth year of compulsory school, the study aims to maintain the same level of progression observed before this point. Previous research indicates that silent reading, being unconstrained by vocalization, is faster than reading aloud. To address this progression flattening, a grid search algorithm was employed to adjust hyperparameters and assign appropriate weight to silent and aloud reading. The findings emphasize that reading aloud should be prioritized in the weighted average and the corresponding hyperparameters adjusted accordingly. Furthermore, gathering more data for older pupils can improve the machine learning model by accounting for individual reading strategies. Introducing different word complexity factors can also enhance the model’s performance. / Läsning och matematik är två avgörande ämnen för akademisk framgång och kognitiv utveckling. Flera studier visar på ett samband mellan elevers läsförmåga och matematiska förmåga (Korpershoek et al., 2015; Ní Ríordáin & O’Donoghue, 2009; Reikerås, 2006; Walker et al., 2008). Den didaktiska delen av denna rapport presenterar en studie som undersöker sambandet mellan läsförmåga och matematisk förmåga hos elever på gymnasiet i Sverige. Studien samarbetade med Lexplore AB för att använda maskininlärning och ögonspårning för att mäta läsförmåga. Matematisk förmåga mättes genom matematikbetyg och Stockholms provet, som är ett diagnostiskt matematiktest. Trotsatt inget samband hittades uppges insikter om urvalet och åtgärder som kan förbättra framtida studier i ämnet. Rapporten konstaterar att resultatet kan ha påverkats avett sned vridet urval av deltagare. Dessutom föreslår rapporten att mätningen genom maskininlärning och ögonspårning som användes i studien kanske inte helt fångar upp begreppet läsförmåga som används i tidigare studier. Teknikdelen av denna rapport fokuserar på att modifiera och förbättra modellen som används för att beräkna användarnas läsförmågepoäng. Eftersom modellens uppskattning tenderar att avplattas efter femte året i grundskola, syftar studien till att bibehålla samma nivå av progression som observerats före denna punkt. Tidigare forskning indikerar att tyst läsning, som inte begränsas av att uttala orden, är snabbare än högläsning. För att adressera denna avplattning av progression användes en rutnätssöknings-algoritm för att justera hyperparametrar och tilldela rätt viktning åt tyst läsning. Resultaten betonar att högläsning bör prioriteras i viktade medelvärdet och att motsvarande justeringar av hyperparametrar bör implementeras. Dessutom kan insamling av mer data för äldre elever förbättra maskininlärningsmodellen genom att ta hänsyn till individuella lässtrategier. Införandet av olika faktorer för textkomplexitet kan också förbättra modellens prestanda.