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    Bildstöd - en litteraturstudie : Hur kan användning av bildstöd i grunskolan påverka elevers språkinlärning i ämnet engelska?

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    Vi har observerat att forskning kring bildstöd i relation till inlärning av det engelska språket, oftast framhäver bildstödets funktion i kombination med läsförståelse och ordförståelse. Vi anser därför att det finns en brist på omfattande forskning som undersöker hur bildstöd kan påverka elevers engelska kommunikativa förmåga som helhet i grundskolan. Studiens syfte är att studera fördelar och nackdelar i att integrera bildstöd i engelskundervisning kopplat till kommunikativa färdigheter i grundskolan. Genom att studera fördelar och nackdelar kan vi identifiera bildstödets påverkan på elevers språkinlärning. Utifrån vårt arbete kan lärare finna stöd vid användning av bildstöd så att de kan använda metoden vid passande tillfällen och exkludera bildstödet vid andra. Vår ambition är att genom detta främja en meningsfull och långvarig förstärkning av elevers språkinlärning. Denna litteraturstudie är därför framskriven för att sammanställa information kring användning av bildstöd i grundskolans engelskundervisning och dess påverkan på elevers kommunikativa förmåga. Vi utgår från frågeställningen: “Hur kan användning av bildstöd i grundskolan påverka elevers språkinlärning i ämnet engelska?” med inkluderings- och exkluderingskriterier som redovisas längre fram i arbetet. Vi har utgått från tematisk analys som metod. Utifrån metoden har åtta artiklar inkluderats, analyserats och tematiserats. Genomförandet utmynnar i arbetets resultat som visar att användning av bildstöd påverkar elevers språkinlärning i ämnet engelska positivt genom flera kommunikativa moment i grundskolan. Även elevernas självsäkerhet och trygghet i genomförandet stärks samtidigt som motivation och engagemang ökar. Vårt arbete framhäver också vikten av lärares medvetenhet kring bildstödets potentiella begränsningar och behovet av en balanserad pedagogisk strategi för optimal effekt

    Barriers and enablers to the implementation of Safewards and the alignment to the i‐PARIHS framework – A qualitative systematic review

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    Inpatient mental healthcare settings should offer safe environments for patients to heal and recover and for staff to provide high-quality treatment and care. However, aggressive patient behaviour, unengaged staff approaches, and the use of restrictive practices are frequently reported. The Safewards model includes ten interventions that aim to prevent conflict and containment. The model has shown promising results but at the same time often presents challenges to successful implementation strategies. The aim of this study was to review qualitative knowledge on staff experiences of barriers and enablers to the implementation of Safewards, from the perspective of implementation science and the i-PARIHS framework. A search of the Web of Science, ASSIA, Cochrane Library, SCOPUS, Medline, Embase, PsycINFO, and CINAHL databases resulted in 10 articles. A deductive framework analysis approach was used to identify barriers and enablers and the alignment to the i-PARIHS. Data most represented by the i-PARIHS were related to the following: local-level formal and informal leadership support, innovation degree of fit with existing practice and values, and recipients' values and beliefs. This indicates that if a ward or organization wants to implement Safewards and direct limited resources to only a few implementation determinants, these three may be worth considering. Data representing levels of external health system and organizational contexts were rare. In contrast, data relating to local (ward)-level contexts was highly represented which may reflect Safewards's focus on quality improvement strategies on a local rather than organizational level. © 2023 The Authors. International Journal of Mental Health Nursing published by John Wiley & Sons Australia, Ltd.Open access funding was provided by the Karolinska Institutet.Safewards Sverig

    Meta-learning for efficient unsupervised domain adaptation

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    The standard machine learning assumption that training and test data are drawn from the same probability distribution does not hold in many real-world applications due to the inability to reproduce testing conditions at training time. Existing unsupervised domain adaption (UDA) methods address this problem by learning a domain-invariant feature space that performs well on available source domain(s) (labeled training data) and the specific target domain (unlabeled test data). In contrast, instead of simply adapting to domains, this paper aims for an approach that learns to adapt effectively to new unlabeled domains. To do so, we leverage meta-learning to optimize a neural network such that an unlabeled adaptation of its parameters to any domain would yield a good generalization on this latter. The experimental evaluation shows that the proposed approach outperforms standard approaches even when a small amount of unlabeled test data is used for adaptation, demonstrating the benefit of meta-learning prior knowledge from various domains to solve UDA problems

    A Meta Systematic Review of Artificial Intelligence in Higher Education : A call for increased ethics, collaboration, and rigour

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    Although the field of Artificial Intelligence in Education (AIEd) has a substantial history as a research domain, never before has the rapid evolution of AI applications in education sparked such prominent public discourse. Given the growing AIEd literature base in higher education, it is important to ensure that the field has a solid research and conceptual grounding as AI adoption increases. This review of reviews is the first comprehensive meta review to explore the scope and nature of AIEd in higher education (AIHEd) research, by synthesising secondary research (e.g., systematic reviews), indexed in the Web of Science, Scopus, ERIC, EBSCOHost, IEEE Xplore, ScienceDirect and ACM Digital Library, or captured through snowballing in OpenAlex, ResearchGate and Google Scholar. Reviews were included if they synthesised applications of AI solely in formal higher or continuing education, were published in English between 2018 and July 2023, were journal articles or full conference papers, and if they had a method section. 66 publications were included for data extraction and synthesis in EPPI Reviewer, which were predominantly systematic reviews (66.7%), published by authors from North America (27.3%), conducted in teams (89.4%) in mostly domestic-only collaborations (71.2%). Findings show that these reviews mostly focused on AIHEd generally (47.0%) or Profiling and Prediction (28.8%) as thematic foci, however key findings indicated a predominance of the use of Adaptive Systems and Personalisation in higher education. Research gaps identified suggest a need for greater ethical, methodological, and contextual considerations within future research, alongside interdisciplinary approaches to AIHEd application. Suggestions are provided to guide future primary and secondary research. © 2024, The Author(s)

    Bilingual language development and ASD : A case-study

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    Research into bilingual language development in autistic children is a new field and the number of studies published to date are very scarce. Around the world exceptional cases are being reported to support the theory that bilingual language development in autistic children is different to that of typically developing children leaving an obvious gap in knowledge. In this essay, a case study is presented of an 11-year-old autistic native Swedish boy with an impaired speech disorder who has developed a bilingual proficiency in English with YouTube as his only source of exposure. The study showed mixed results as when the tasks were performed Swedish was the reciprocating language. However, in the interview all replies were in English, even though spoken to in Swedish, suggesting a preference for speaking English when allowed to speak freely. Furthermore, this study challenges the notion that children with impaired speech disorders would experience even slower language emergence if simultaneously exposed to an L2. These findings call for further research at a higher level than a Bachelor’s thesis.  

    From Domain Adaptation to Federated Learning

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    Data-driven methods have been gaining increasing attention; however, along with the benefits they offer, they also present several challenges, particularly concerning data availability, accessibility, and heterogeneity, the three factors that have shaped the development of this thesis. Data availability is the primary consideration when employing data-driven methodologies. Suppose we consider a system for which we aim to develop a Machine Learning (ML) model. Gathering labeled samples, particularly in the context of real-world problem-solving, consistently poses challenges. While collecting raw data may be feasible in certain situations, the process of labeling them is often difficult, leading to a shortage of labeled data. However, historical (outdated) data or labeled data may occasionally be available from different yet related systems. A feasible approach would be to leverage data from different but related sources to assist in situations in which data is scarce. The challenge with this approach is that data collected from various sources may exhibit statistical differences even if they have the same features, i.e., data heterogeneity. Data heterogeneity impacts the performance of ML models. This issue arises because conventional machine learning algorithms assume what’s known as the IID (Independently and Identically Distributed) assumption; training and test data come from the same underlying distribution and are independent and identically sampled. The IID assumption may not hold when data comes from different sources and can result in a trained model performing less effectively when used in another system or context. In such situations, Domain Adaptation (DA) is a solution. DA enhances the performance of ML models by minimizing the distribution distance between samples originating from diverse resources. Several factors come into play within the DA context, each necessitating distinct DA methods. In this thesis, we conduct an investigation and propose DA methods while considering various factors, including the number of domains involved, the quantity of data available (both labeled and unlabeled) within these domains, the task at hand (classification or regression), and the nature of statistical heterogeneity among samples from different domains, such as covariate shift or concept shift. It is crucial to emphasize that DA techniques work by assuming that we access the data from different resources. Data may be owned by different data owners, and data owners are willing to share their data. This data accessibility enables us to adapt data and optimize models accordingly. However, privacy concerns become a significant issue when addressing real-world problems, for example, where the data owners are from industry sectors. These privacy considerations necessitate the development of privacy-preserving techniques, such as Federated Learning (FL). FL is a privacy-preserving machine learning technique that enables different data owners to collaborate without sharing raw data samples. Instead, they share their ML models or model updates. Through this collaborative process, a global machine learning model is constructed, which can generalize and perform well across all participating domains. This approach addresses privacy concerns by keeping individual data localized while benefiting from collective knowledge to improve the global model. Among the most widely accepted FL methods is Federated Averaging (FedAvg). In this method, all clients connect with a central server. The server then computes the global model by aggregating the local models from each client, typically by calculating their average. Similar to DA, FL encounters issues when data from different domains exhibit statistical differences, i.e., heterogeneity, that can negatively affect the performance of the global model. A specialized branch known as Heterogeneous FL has emerged to tackle this situation. This thesis, alongside DA, considers the heterogeneous FL problem. This thesis examines FL scenarios where all clients possess labeled data. We begin by conducting experimental investigations to illustrate the impact of various types of heterogeneity on the outcomes of FL. Afterward, we perform a theoretical analysis and establish an upper bound for the risk of the global model for each client. Accordingly, we see that minimizing heterogeneity between the clients minimizes this upper bound. Building upon this insight, we develop a method aimed at minimizing this heterogeneity to personalize the global model for the clients, thereby enhancing the performance of the federated system. This thesis focuses on two practical applications that highlight the relevant challenges: Predictive Maintenance and Network Security. In predictive maintenance, the focus is on fault identification using both DA and FL. Additionally, the thesis investigates predicting the state of health of electric bus batteries using DA. Regarding network security applications, the thesis addresses network traffic classification and intrusion detection, employing DA. ©Zahra Taghiyarrenani

    Muren mellan skolan och fritidens engelska : Hur inkluderas extramural engelska i skolans engelskundervisning?

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    This study explores the integration of extramural English in school teaching of English and use among students outside the classroom. With the growing exposure to English through digital media, a new concept of "prosumer" is being created, a role that students increasingly fulfill where they are active both as consumers and producers. It is at this stage that I become more interested in this field of study and begin to think about how the school world addresses and includes students' extramural English, and how students use the English they learn at school in their spare time. Is there a link between these two types of English?  By interviewing seven teachers and twelve students from year 6 in southern Sweden, this study investigates how extramural English is used in teaching. The results show an awareness among teachers about how students learn and interact with English language learning outside of school, but a lack of concrete methods of how this knowledge is integrated in the classroom. The students report that they use their “school taught English”  mainly in social media and online games, which promote and develop their communication skills, pronunciation, spelling and vocabulary.Denna studie utforskar integrationen av extramural engelska i skolans engelskundervisning och dess användning bland elever utanför klassrummet. Med den växande exponeringen för engelska via digitala medier har det uppstått en ny roll som i litteraturen benämns som “prosumer”, en roll som eleverna uppfyller alltmer där de är aktiva både som konsumenter och producenter. I detta stadie väcks ett stort intresse hos mig och jag börjar fundera på om och i sådana fall hur skolans värld bemöter och inkluderar elevernas extramurala engelska, och om och hur eleverna i sin tur använder sig av den engelskan de lär sig i skolan på sin fritid. Finns det en länk mellan dessa två typer av engelska? Genom att intervjua sju lärare och tolv elever från årskurs 6 i södra Sverige, undersöker denna studie hur den extramurala engelskan tas tillvara i undervisningen. Resultaten visar en medvetenhet hos lärare om elevernas engelska språkinlärning utanför skolan, men en brist på konkreta metoder för hur denna kunskap integreras i klassrummet. Eleverna rapporterar att de använder sin skolengelska främst inom sociala medier och onlinespel, vilket främjar deras kommunikativa förmåga, uttal, stavning och ordförrå

    Pcapng Analyzer : Development of a Pcapng analyzer with focus on custom network packets

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    I ett modernt industrisammanhang spelar kommunikation mellan inbyggda komponenter en viktig roll. Svetsmaskins företaget ESAB (Elektriska Svetsar AB) producerar och utvecklar svetsmaskiner med ett flertal olika inbyggda komponenter som kommunicerar sinsemellan för att konfigurera operationen för svetsning. Inom ramen för projektet på ESAB analyseras nätverkspaketen som skickas inom svetsmaskiner och som hämtas ut med hjälp av Wireshark. Nätverkspaketen används för systemkommunikations analys och hämtas ut i Pcapng-filformatet. Pcapng-filernagranskats manuellt med hjälp av Wireshark och deras skräddarsydda plugin, vilket kräver att varje paket inspekteras för att identifiera innehåll och potentiella felmeddelanden. Pcapng Analysatorn är ett program för att automatisera denna process och framhäva enbart de meddelanden och data som är av relevans för företaget. Denna rapport fokuserar på tekniker för manipulering och hantering av Pcapng-filer, samt metoder för extrahering av felmeddelanden från specialanpassade Pcapng-filer. Projektet representerar ett viktigt steg mot att effektivisera analysen av Pcapng-filer och att förse ESAB med en mer automatiserad och produktiv lösning för dataanalys inom sina verksamheter.In a modern industrial context, communication between embedded components plays a crucial role. The welding machine company ESAB (Electric Welders AB) produces and develops welding machines with various embedded components that communicate with each other to configure the welding operation. Within the framework of the project at ESAB, network packets sent within welding machines are analysed and retrieved using Wireshark. These network packets are used for system communication analysis and extracted in Pcapng file format. The Pcapng files have been manually reviewed using Wireshark and a custom-built plugin, requiring each packet to be inspected to identify content and potential error messages. The Pcapng Analyzer is a program designed to automate this process and highlight only the messages and data relevant to the company. This report focuses on techniques for manipulating and managing Pcapng files, as well as methods for extracting error messages from customized Pcapng files. The project represents a significant step towards streamlining the analysis of Pcapng files and providing ESAB with a more automated and productive solution for data analysis in its operations

    Inkludering av spelelement i matematikundervisning : Effekter och strategier

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    I skolan har den traditionella metoden för undervisning länge dominerat i klassrummen. Däremot har barns intresse för spel öppnat dörren för ett spelbaserat lärande, inte minst inom matematikämnet. Fler och fler pedagogiska spel skapas och möjligheterna att implementera spel eller spelelement i undervisningen är många. Denna litteraturstudie syftar till att undersöka vad forskning säger om hur det spelbaserade lärandet påverkar elevers lärande och spelupplevelse, samt hur lärare kan planera sin undervisning med spel eller spelelement. För att utforska detta har åtta vetenskapliga artiklar noggrant utvalts och en litteraturstudie genomförts med hjälp av en tematisk analys. Analysen framställde att den spelbaserade undervisningen påverkar elevers lärande och prestationer positivt. Resultatet visar vidare att eleverna upplever spel i undervisningen som både spännande och engagerande, samt att lärare uttrycker en övervägande positiv inställning gentemot de granskade metoderna för spelbaserat lärande

    Abstrakta begrepp i NO-salen : En trestegsmodell för ökad begreppsförståelse i naturorienterande ämnen

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    Swedish students in grades 4 and 8 have maintained a consistent performance in natural science based on the TIMSS assessments conducted in 2019 and 2015. However, results from the Swedish School Inspectorate suggest a low level of interest among students in the subject of natural science. Students have expressed difficulty in understanding natural science subjects due to teachers frequently discussing abstract phenomena that are challenging to observe or visualize clearly. Despite memorizing information to meet subject objectives, pupils often lack a deeper comprehension of these scientific phenomena, resulting in a diminished interest in the subject. This litterary overwiev aims to address the question: What factors and methods are conducive to enhancing middle school pupils' conceptual understanding in natural science subjects? Eight diverse studies focused on students' conceptual understanding, or lack thereof, in natural science were analyzed. The outcomes highlighted three themes with a positive impact on pupils' conceptual understanding: the nature of the subject matter, teacher-related factors, and aspects of instructional content such as teaching methods. This study identifies methods and pedagogical choices that educators can utilize to improve pupils' conceptual understanding in a three step solution. Further discussion explores potential discrepancies between the new Swedish curriculum and such instructional approaches, questioning the coexistence of pupils' interest and knowledge in elementary science education

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