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A systematic review and evaluation of measurement instruments assessing the needs, wellbeing, and living environments of older adults
No full textUnderstanding the built environment’s impact on older adults’ wellbeing necessitates the identification of high-quality measures that capture environmental properties, wellbeing, and needs. Literature searches were conducted to identify instruments that measure (a) objective environmental properties, (b) wellbeing, (c) needs, and (d) environmental perception, which were evaluated using the COSMIN checklist. Another literature search was conducted to explore which instruments are used in studies examining objective and perceived qualities of the environment in relation to wellbeing. Of the 54 instruments evaluated, most showed strong content or construct validity, but weak or unreported test-retest reliability. Structural validity and internal consistency tended to be satisfactory in instruments assessing wellbeing and the intersection of environment and wellbeing. Instruments evaluating needs and the perceived environment generally had poor results in our evaluation. Our review of studies assessing both perceived and objective built environments alongside wellbeing indicates a lack of consistent use of validated instruments for older adult populations. We have identified instruments in each category with mostly sufficient psychometric properties, while the rest require improvement, particularly in terms of structural validity and reliability. Environment evaluation instruments mainly focus on outdoor spaces, leaving indoor spaces underrepresented in literature
Vplivi vadbenih protiukrepov na dekondicijo skeletne mišice, izpostavljene mikrogravitaciji
No full text
Strogi pogoj variante trdnosti delnih k-faktorjev
No full textThe toughness t(G) of graph G is formalized as the minimum ratio of |S| and ω(G − S) over all vertex subsets S subject to ω(G − S) > 1. As the unique variant parameter of toughness, τ(G) is formulated as the minimum ratio of |S| and ω(G − S) − 1 traversing all the vertex subset S restricted to ω(G − S) ≥ 2. The extant contributions reveal that there is a substantial correlation between toughness and fractional factors. However, there is still a paucity of solid studies on toughness variants τ(G). This work provides several theoretical underpinnings for the tight toughness variant bound for a graph G which admits a fractional k-factor. To be specific, a graph G has a fractional k-factor if τ(G) > k for k ≥ 3 and if τ(G)>3/2 for k = 2. The sharpness of the given bounds is explained by counterexamples
Analysis of international national guidelines for the use of artificial intelligence in learning and teaching at the pre-university level
No full textV prispevku analiziramo mednarodne nacionalne smernice rabe generativne umetne inteligence (GEN-UI) v osnovnošolskem in srednješolskem izobraževanju držav Hrvaške, Španije, dveh zveznih dežel Nemčije, Norveške, Kanade in Združenih države Amerike. V prispevku smo se osredotočili na dve raziskovalni vprašanji, in sicer vlogo in pomen GEN-UI pri poučevanju učiteljev ter pomen GEN-UI pri učenju učencev. Na osnovi izvedene tematske analize smernic ugotavljamo, da nacionalni dokumenti izkazujejo ambivalenten odnos do vključevanja GEN-UI v izobraževanje. Slednja orodja na eni strani prinašajo velik potencial za izboljšano učinkovitost in kakovost poučevanja, po drugi strani pa opozarjajo na tveganja in izzive te tehnologije. Ključni predlogi analiziranih nacionalnih dokumentov se nanašajo na razmislek glede prenove obstoječih učnih načrtov z vidika vključevanja GEN-UI in doseganja višjih taksonomskih ravni znanja ter izpostavljajo potrebo po vseživljenjskem učenju učiteljev, predvsem na področju spretnosti rabe orodij UI, etičnih, pravnih in tehnično-tehnoloških vidikov UI v izobraževanju. Prispevek s pregledom ob stoječih evropskih in drugih smernic poudarja potencial za oblikovanje izhodišč nacionalnih usmeritev rabe GEN-UI v osnovnošolskem in srednješolskem izobraževanju v Sloveniji.This paper analyses international guidelines for the use of generative artificial intelligence in education (GEN-AI) in primary and secondary education across Croatia, Spain, two German regions, Norway, Canada, and the United States. The study addresses two key research questions: the role and relevance of GUI in teachers’ teaching and its significance for students’ learning. Through thematic analysis of these guidelines, we identify ambivalent perspectives on the integration of GEN-AI in education. While the documents highlight the significant potential of GEN-AI for enhancing the efficiency and quality of teaching, they also underscore the risks and challenges associated with this technology. The key proposals emphasize the need to revise existing curricula to better integrate GEN-AI, aiming to foster the achievement of higher-order cognitive skills. Additionally, they stress the importance of lifelong professional development for teachers, particularly in building competencies related to the use of AI tools and understanding the ethical, legal, and technical aspects of AI in education. By reviewing European and international guidelines, this paper underscores the potential to establish a foundational framework for national guidelines on the use of GEN-AI in primary and secondary education in Slovenia
Generativna umetna inteligenca in hrvaški izobraževalni sistem
No full textThis chapter explores the transformative potential of Generative AI (GEN-AI) in education, focusing on its integration into the Croatian educational system. It examines the historical evolution of AI, the rapid emergence of GEN-AI tools, and their implications for teaching and learning. GEN-AI’s multimodal capabilities offer opportunities to enhance creativity, problem-solving, and personalised learning. However, challenges such as overreliance, transparency, and ethical considerations require special attention. Croatia has made significant efforts in addressing these challenges through initiatives like the BrAIn project, CARNET’s AI curriculum, and the Digital Croatia Strategy 2032, which emphasise AI literacy, teacher empowerment, and equitable access. Pedagogical approaches for teaching with and about GEN-AI are discussed, emphasising active learning, ethical awareness, and the importance of maintaining human oversight. This chapter advocates for a balanced, human-centric approach to integrating GEN-AI, ensuring its use aligns with educational values of creativity and intellectual growth while addressing the evolving demands of a digital future.Poglavje raziskuje transformativni potencial generativne umetne inteligence (GUI) v izobraževanju, pri čemer se osredotoča na vključevanje te tehnologije v hrvaški izobraževalni sistem. Preučuje zgodovinski razvoj umetne inteligence (UI), hiter porast orodij GEN-U ter posledice za poučevanje in učenje. Multimodalne zmožnosti GUI ponujajo priložnosti za krepitev ustvarjalnosti, reševanje problemov in personalizirano učenje. Vendar je treba posebno pozornost nameniti tudi izzivom, kot so pretirano zanašanje na GUI, preglednost in etični vidiki. Hrvaška si je precej prizadevala za reševanje teh izzivov s pobudami, kot so projekt BrAIn, učni načrt za UI CARNET in strategija Digitalna Hrvaška 2032, ki poudarjajo opismenjevanje na področju UI, opolnomočenje učiteljev in pravičen dostop. Obravnavani so pedagoški pristopi za poučevanje z GUI in o GUI, pri čemer so poudarjeni aktivno učenje, etična ozaveščenost in pomen ohranjanja človeškega nadzora. To poglavje zagovarja uravnotežen, na človeka osredotočen pristop k vključevanju GUI, ki zagotavlja, da je njena uporaba skladna z izobraževalnimi vrednotami ustvarjalnosti in intelektualne rasti, hkrati pa obravnava spreminjajoče se zahteve digitalne prihodnosti
O enostavnih grupah, ki dopuščajo prezentacijo kot nizovne C-grupe
No full textWe prove that a simple group admits at least one string C-group representation if and only if it is not one of PSL(3, q), PSU(3, q),
PSL(4, 2^n), PSU(4, 2^n), PSU(4, 3), PSU(5, 2), A₆, A₇, M₁₁, M₂₂, M₂₃ or McL