The aim of this investigation was to determine whether there is a significant difference in the academic achievement of sixth grade Science students when teaching styles are matched to their learning styles. The research problem is encompassed in the following question: "Is there a relationship between matching teaching and learning styles and the academic success in Science?" A quantitative approach was undertaken, specifically, the pretest-posttest control group experimental design. The population comprised of sixth grade students selected according to a non-probability sampling method of convenience. The sample comprised of two class units randomly selected. The dependent sample t-test inferential statistic was used to analyze the data collected. The results indicated a statistically significant difference between the pretest and posttest scores of the experimental group. The conclusion reached is that matching teaching styles to learning styles improves the academic success of sixth grade learners in Science. / Educational Studies / M.Ed. (Educational Psychology)

Estudamos o problema de obtenção de estimadores/preditores ótimos para combinações lineares de respostas coletadas de uma população finita por meio de amostragem aleatória simples. Nesse contexto, estendemos o modelo misto para populações finitas proposto por Stanek, Singer & Lencina (2004, Journal of Statistical Planning and Inference) para casos em que se incluem erros de medida (endógenos e exógenos) e informação auxiliar. Admitindo que as variâncias são conhecidas, mostramos que os estimadores/preditores propostos têm erro quadrático médio menor dentro da classe dos estimadores lineares não viciados. Por meio de estudos de simulação, comparamos o desempenho desses estimadores/preditores empíricos, i.e., obtidos com a substituição das componentes de variância por estimativas, com aquele de competidores tradicionais. Também, estendemos esses modelos para análise de estudos com estrutura do tipo pré-teste/pós-teste. Também por intermédio de simulação, comparamos o desempenho dos estimadores empíricos com o desempenho do estimador obtido por meio de técnicas clássicas de análise de medidas repetidas e com o desempenho do estimador obtido via análise de covariância por meio de mínimos quadrados, concluindo que os estimadores/ preditores empíricos apresentaram um menor erro quadrático médio e menor vício. Em geral, sugerimos o emprego dos estimadores/preditores empíricos propostos para dados com distribuição assimétrica ou amostras pequenas. / We consider optimal estimation of finite population parameters with data obtained via simple random samples. In this context, we extend a finite population mixed model proposed by Stanek, Singer & Lencina (2004, Journal of Statistical Planning and Inference) by including measurement errors (endogenous or exogenous) and auxiliary information. Assuming that variance components are known, we show that the proposed estimators/predictors have the smallest mean squared error in the class of unbiased estimators. Using simulation studies, we compare the performance of the empirical estimators/predictors obtained by replacing variance components with estimates with the performance of a traditional estimator. We also extend the finite population mixed model to data obtained via pretest-posttest designs. Through simulation studies, we compare the performance of the empirical estimator of the difference in gain between groups with the performance of the usual repeated measures estimator and with the performance of the usual analysis of covariance estimator obtained via ordinary least squares. The empirical estimator has smaller mean squared error and bias than the alternative estimators under consideration. In general, we recommend the use of the proposed estimators/ predictors for either asymmetric response distributions or small samples.

Estudamos o problema de obtenção de estimadores/preditores ótimos para combinações lineares de respostas coletadas de uma população finita por meio de amostragem aleatória simples. Nesse contexto, estendemos o modelo misto para populações finitas proposto por Stanek, Singer & Lencina (2004, Journal of Statistical Planning and Inference) para casos em que se incluem erros de medida (endógenos e exógenos) e informação auxiliar. Admitindo que as variâncias são conhecidas, mostramos que os estimadores/preditores propostos têm erro quadrático médio menor dentro da classe dos estimadores lineares não viciados. Por meio de estudos de simulação, comparamos o desempenho desses estimadores/preditores empíricos, i.e., obtidos com a substituição das componentes de variância por estimativas, com aquele de competidores tradicionais. Também, estendemos esses modelos para análise de estudos com estrutura do tipo pré-teste/pós-teste. Também por intermédio de simulação, comparamos o desempenho dos estimadores empíricos com o desempenho do estimador obtido por meio de técnicas clássicas de análise de medidas repetidas e com o desempenho do estimador obtido via análise de covariância por meio de mínimos quadrados, concluindo que os estimadores/ preditores empíricos apresentaram um menor erro quadrático médio e menor vício. Em geral, sugerimos o emprego dos estimadores/preditores empíricos propostos para dados com distribuição assimétrica ou amostras pequenas. / We consider optimal estimation of finite population parameters with data obtained via simple random samples. In this context, we extend a finite population mixed model proposed by Stanek, Singer & Lencina (2004, Journal of Statistical Planning and Inference) by including measurement errors (endogenous or exogenous) and auxiliary information. Assuming that variance components are known, we show that the proposed estimators/predictors have the smallest mean squared error in the class of unbiased estimators. Using simulation studies, we compare the performance of the empirical estimators/predictors obtained by replacing variance components with estimates with the performance of a traditional estimator. We also extend the finite population mixed model to data obtained via pretest-posttest designs. Through simulation studies, we compare the performance of the empirical estimator of the difference in gain between groups with the performance of the usual repeated measures estimator and with the performance of the usual analysis of covariance estimator obtained via ordinary least squares. The empirical estimator has smaller mean squared error and bias than the alternative estimators under consideration. In general, we recommend the use of the proposed estimators/ predictors for either asymmetric response distributions or small samples.

The aim of this investigation was to determine whether there is a significant difference in the academic achievement of sixth grade Science students when teaching styles are matched to their learning styles. The research problem is encompassed in the following question: "Is there a relationship between matching teaching and learning styles and the academic success in Science?" A quantitative approach was undertaken, specifically, the pretest-posttest control group experimental design. The population comprised of sixth grade students selected according to a non-probability sampling method of convenience. The sample comprised of two class units randomly selected. The dependent sample t-test inferential statistic was used to analyze the data collected. The results indicated a statistically significant difference between the pretest and posttest scores of the experimental group. The conclusion reached is that matching teaching styles to learning styles improves the academic success of sixth grade learners in Science. / Educational Studies / M.Ed. (Educational Psychology)

Artificial Intelligence (AI) is a useful tool in education, with the potential to enhance teaching through the use of digital learning environments (DLEs) such as intelligent tutoring systems (ITSs). This thesis investigates the development and evaluation of an AI-assisted web-based platform for pure question-based learning (pQBL) in upper secondary school mathematics. The study aims to assess the prototype's effects compared to traditional classroom instruction and the quality of AI-generated multiple-choice questions (MCQs) using OpenAI’s GPT-4. To do this, the following research questions were formulated: (1) How can an AI-assisted platform for pQBL be designed and implemented? (2) To what extent do GPT-4 generated MCQs meet quality criteria? (3) How do learning outcomes compare between students using AI-assisted pQBL materials and those receiving traditional instruction? The study utilized principles of Question Construction and Prompt Engineering, ensuring AI-generated MCQs adhered to predefined quality standards. Human evaluation by a Teacher Quality Control panel refined and validated the generated MCQs. The effectiveness of the developed prototype was tested using a pretest/posttest design where score changes were analyzed using paired-samples t-tests. The findings indicate that generating high-quality MCQs remains a challenge. Human evaluation is essential to ensure educational efficacy, as only a fraction of the AI-generated MCQs met quality standards. User testing revealed comparable learning outcomes between the pQBL and control groups, with statistically significant results, though limitations in the pretest/posttest design may have influenced these findings. This research highlights the potential and limitations of AI in education, suggesting the need for further studies on AI-assisted tools, including exploring other language models and conducting longitudinal assessments to optimize learning outcomes. / AI utgör en viktig resurs inom utbildning och har potential att förbättra undervisningen genom digitala lärmiljöer (DLE), såsom intelligenta handledningssystem (ITS). Detta examensarbete undersöker utvecklingen och utvärderingen av en AI-stödd webbaserad plattform för rent frågebaserat lärande (pQBL) i matematik på gymnasiet. Studien syftar till att bedöma plattformens effektivitet jämfört med traditionell klassrumsundervisning och att utvärdera kvaliteten på flervalsfrågor som genereras av OpenAI:s GPT-4. För att uppnå detta formulerades följande forskningsfrågor: (1) Hur kan en AI-stödd plattform för pQBL designas och implementeras? (2) I vilken utsträckning uppfyller GPT-4- genererade flervalsfrågor fördefinierade kvalitetskriterier? (3) Hur skiljer sig inlärningsresultaten mellan elever som använder AI-stött pQBL-material och de som får traditionell klassrumsundervisning? Studien tillämpade principer för fråge- och promptkonstruktion för att säkerställa att de AI-genererade flervalsfrågorna följde fördefinierade kvalitetsstandarder. En panel av lärare genomförde mänsklig utvärdering för att förbättra och validera de genererade flervalsfrågorna. Effekten av den utvecklade prototypen testades genom en förtest/eftertest-design där poängförändringen analyserades genom parvisa t-tester. Resultaten indikerar att det finns utmaningar i att generera högkvalitativa flervalsfrågor. Mänsklig utvärdering är nödvändig för att säkerställa kvaliteten hos de AI-genererade flervalsfrågornas eftersom endast en mindre del av dem uppfyllde kvalitetskraven. Användartester visade jämförbara inlärningsresultat mellan pQBL-gruppen och kontrollgruppen med statistiskt signifikanta resultat även om begränsningar i förtest/eftertest-designen kan ha påverkat dessa resultat. Denna forskning belyser AI:s potential och begränsningar inom utbildning och föreslår behovet av ytterligare studier kring AI-drivna verktyg, inklusive undersökning av andra språkmodeller och genomförande av longitudinella studier för att optimera inlärningsresultaten.

Heart failure is a growing public health problem associated with significant morbidity and mortality. Family support positively affects outcomes for the person with heart failure while also leading to caregiver burden. Registered nurses have a key role in supporting and meeting the needs of family caregivers. The overall aim was to explore the situation and needs of family caregivers to a person with heart failure, and explore requisites and ways of supporting and involving family caregivers in heart failure nursing care. Two interview studies, one web survey study and one intervention study were conducted between 2012 and 2017. A total of 22 family caregivers, eight persons with heart failure and 331 registered nurses participated in the studies. Family caregivers' daily life was characterized by worry, uncertainty and relational incongruence but salutogenic behaviours restored new strength and motivation to care. Family caregivers experienced that their caregiving was taken for granted by health care professionals. Family caregivers expressed a need for a permanent health care contact and more involvement in the planning and implementation of their near one’s health care together with health care professionals. Registered nurses acknowledged family caregivers’ burden, lack of knowledge and relational incongruence. A registered nurse was suggested as a permanent health care contact to improve continuity and security. Registered nurses neither acknowledged family caregivers as a resource nor their need for involvement. Registered nurses working in primary health care centres, in nurse-led heart failure clinics, with district nurse specialization, with education in cardiac nursing care held the most supportive attitudes toward family involvement in heart failure nursing care. Family health conversations via telephone in nurse-led heart failure clinics were found to successfully support and involve families. The conversations enhanced nurse-family relationship and relations within the family. They also provided registered nurses with new, relevant knowledge and understanding about the family as a whole. Family health conversations via telephone were feasible to both families and registered nurses, although fewer and shorter conversations were preferred by registered nurses. This thesis highlights the divergence between family caregivers’ experiences and needs, and registered nurses’ perceptions about family caregivers’ situation and attitudes toward the importance of family involvement. It adds to the knowledge on the importance to acknowledge family caregivers as a resource and to support and involve them in heart failure nursing care. One feasible and successful way is to conduct Family health conversations via telephone in nurse-led heart failure clinics.

<p dir="ltr">Infographics are increasingly used as visual communication tools for conveying health information to diverse audiences. However, research is lacking on how specific infographic design factors influence learning outcomes. This study aimed to determine the comparative effectiveness of automatically advanced (Group A) versus manually advanced (Group B) infographics for promoting breast cancer awareness and knowledge. A mixed-methods quasi-experimental pretest-posttest design was utilized. The sample comprised 42 participants for analysis. Of these, the majority, 41 persons self-reported as female, with one participant indicating their gender as 'other.' Participant ages ranged from 25 to 55 years (M = 40.5, SD = 7.62). Most participants were well-educated, with graduate degrees or other advanced education beyond a bachelor's degree. Participants were randomly assigned to either the automatically advanced infographic group (Group A) or the manually advanced infographic group (Group B). Results indicated that Group B had significantly higher scores on the knowledge post-test compared to Group A, suggesting improved recall and comprehension of key information. There were no significant differences in cognitive load ratings or viewing duration between the groups. Qualitative feedback from participants suggested that Group B's manually advanced infographic facilitated better self-pacing and absorption of content. While the study's findings provide preliminary evidence supporting the efficacy of manually advanced infographics in learning complex health information, limitations are acknowledged. The research contributes to the design of patient education materials and underscores the necessity for further investigations across varied populations and health topics to understand the impact of infographic design more comprehensively on learning and behavior.</p>