Basierend auf dem Abschlussbericht der TU Chemnitz wurden die Ergebnisse der Evaluation zur ESF-finanzierten Laufzeit des Vorhabens „Inklusionsassistent“ in einer Handreichung zusammengefasst und Handlungsempfehlungen für die Praxis abgeleitet. Die Empfehlungen richten sich vor allem an die an der Maßnahme beteiligten Inklusionsassistentinnen und Inklusionsassistenten, Projektträger, Schulleitungen sowie Lehrkräfte vor Ort. Redaktionsschluss: 15.02.2022

Gemeinsamer Workshop von Universitaetsrechenzentrum und Professur "Rechnernetze und verteilte Systeme" der Fakultaet fuer Informatik der TU Chemnitz. Workshop-Thema: Mobilitaet

After the democratic election of 1994, a new and integrated education system was developed in South Africa in accordance with international trends and the stipulations of the South African Bill of Rights with regard to equality, human dignity, basic education and equal access to education. According to the inclusive education system, learners with learning and developmental barriers should be accommodated within the mainstream of education. In order for inclusive education to succeed, a network of support was developed on departmental, provincial, district and school level. At school level, the school-based support team is directly responsible for supporting learners with learning and developmental barriers, educators and parents/caregivers. The effectiveness of these school-based support teams will, eventually, determine the quality of this inclusive education approach. The question which guided this research, is: How effectively does the school-based support team fullfil its function in the teaching and learning of learners with learning and developmental barriers within the framework of inclusive education? A qualitative research design was chosen which is exploratory, descriptive and explanatory. After an initial literature study in which international and national trends in this field were investigated, five primary mainstream schools were selected in the Western Cape according to certain criteria. A pilot study was conducted in another school to refine data collection strategies. Information was then gathered in the five schools by means of structured questionnaires, individual and focus group interviews, field notes and the study of appropriate documents. In order to evaluate these teams, eleven criteria were designed to serve collectively as an evaluation instrument. The effectiveness of the school-based support teams in the five schools were subsequently assessed and placed in various categories according to a conceptual framework. It was found that the school-based support teams function relatively effectively in most areas. The composition of the teams is effective. However, the teams function ineffectively with regard to the orientation and training of their members, as well as of the teachers and parents/caregivers of learners with learning and developmental barriers / Thesis (PhD (Educational Psychology))--University of Pretoria, 2008. / Educational Psychology / unrestricted

The integration of Large Language Models (LLMs) such as GPT-4 and Gemini into healthcare, particularly for elderly care, represents a significant opportunity in the use of artificial intelligence in medical settings. This thesis investigates the capabilities of these models to understand and respond to the healthcare needs of older adults effectively. A framework was developed to evaluate their performance, consisting of specifically designed medical scenarios that simulate real-life interactions, prompting strategies to elicit responses and a comprehensive user evaluation to assess technical performance and contextual understanding.  The analysis reveals that while LLMs such as GPT-4 and Gemini exhibit high levels of technical proficiency, their contextual performance shows considerable variability, especially in personalization and handling complex, empathy-driven interactions. In simpler tasks, these models demonstrate appropriate responsiveness, but they struggle with more complex scenarios that require deep medical reasoning and personalized communication.  Despite these challenges, the research highlights the potential of LLMs to significantly enhance healthcare delivery for older adults by providing timely and relevant medical information. However, to realize a truly effective implementation, further development is necessary to improve the models’ ability to engage in meaningful dialogue and understand the nuanced needs of an aging population.  The findings underscore the necessity of actively involving older adults in the development of AI technologies, ensuring that these models are tailored to their specific needs. This includes focusing on enhancing the contextual and demographic awareness of AI systems. Future efforts should focus on enhancing these models by incorporating user feedback from the older population and applying user-centered design principles to improve accessibility and usability. Such improvements will better support the diverse needs of aging populations in healthcare settings, enhancing care delivery for both patients and doctors while maintaining the essential human touch in medical interactions. / Integrationen av stora språkmodeller (LLMs) såsom GPT-4 och Gemini inom sjukvården, särskilt inom äldrevård, representerar betydande möjligheter i användningen av artificiell intelligens i medicinska sammanhang. Denna avhandling undersöker dessa modellers förmåga att förstå och effektivt svara på äldres vårdbehov. För att utvärdera deras prestanda utvecklades ett ramverk bestående av specifikt utformade medicinska situationer som simulerar verkliga interaktioner, strategier för att framkalla relevanta svar från modellerna och en omfattande användarutvärdering för att bedöma både teknisk prestanda och kontextuell förståelse.  Analysen visar att även om LLMs såsom GPT-4 och Gemini visar på hög teknisk prestationsförmåga, är dess kontextuella förmåga mer begränsad, särskilt när det gäller personalisering och hantering av komplexa, empatidrivna interaktioner. Vid enklare uppgifter visar dessa modeller på en lämplig responsivitet, men de utmanas vid mer komplexa scenarier som kräver djup medicinsk resonemang och personlig kommunikation.  Trots dessa utmaningar belyser denna forskning potentialen hos LLMs att väsentligt förbättra vårdleveransen för äldre genom att tillhandahålla aktuell och relevant medicinsk information. Däremot krävs ytterligare utveckling för att verkligen möjliggöra en effektiv implementering, vilket inkluderar att förbättra modellernas förmåga att delta i en meningsfull dialog och förstå de nyanserade behoven hos äldre patienter.  Resultaten från denna avhandling understryker nödvändigheten av att aktivt involvera äldre individer i utvecklingen av AI-teknologier, för att säkerställa att dessa modeller är skräddarsydda för deras specifika behov. Detta inkluderar ett fokus på att förbättra den kontextuella och demografiska medvetenheten hos AI-system. Framtida insatser bör inriktas på att förbättra dessa modeller genom att integrera användarfeedback från äldre populationer och tillämpa principer för användarcentrerad design för att förbättra tillgänglighet och användbarhet. Sådana förbättringar kommer att bättre stödja de mångsidiga behoven hos äldre i vårdsammanhang, förbättra vårdleveransen för både patienter och läkare samtidigt som den väsentliga mänskliga kontakten i medicinska interaktioner bibehålls.

Gemeinsamer Workshop von Universitaetsrechenzentrum und Professur "Rechnernetze und verteilte Systeme" der Fakultaet fuer Informatik der TU Chemnitz. Workshop-Thema: Mobilitaet