Search (227 results, page 2 of 12)

  • × year_i:[2020 TO 2030}
  1. Schleim, S.; Amunts, K.: Deutsche Forscher veröffentlichen ersten 3D-Atlas des menschlichen Gehirns (2020) 0.02 
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  2. Brembs, B.; Förstner, K.; Kraker, P.; Lauer, G.; Müller-Birn, C.; Schönbrodt, F.; Siems, R.: Auf einmal Laborratte (2021) 0.02 
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  3. Reynolds, R.; Aromi, J.; McGowan, C.; Paris, B.: Digital divide, critical-, and crisis-informatics perspectives on K-12 emergency remote teaching during the pandemic (2022) 0.02 
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    Abstract
    The rapid deployment of emergency remote teaching in the pandemic presents sweeping societal-level information systems phenomena worthy of scholarly inquiry. This paper reports findings from teacher interviews conducted with K-12 public school teachers, exploring how digital access and use gaps in communities reflect wider digital and social inequalities as schools fulfilled emergency remote teaching mandates, becoming swept up into e-learning technology expansion trends propelled by mandates, and unfettered corporate edtech. Results show persistence of home and school level digital affordance gaps as hindrances to pandemic pedagogy. We build upon theory of the digital divide, and crisis and critical informatics literature considering how critical approaches to the study of socio-technical systems research can inform these understandings, providing insights into how localized digital inequities contribute to broader digital inequality and social inequality, in the educative processes expected of public education in democratic societies. Our work gives voice to one highly pressured and conflicted stakeholder in these dynamics-K-12 public school teachers-and demonstrates some of the ways in which digital inequity gaps may play a further magnifying role of societal division through expanding edtech deployment in K-12 grades, if current edtech trends hold.
  4. Janssen, J.-K.: ChatGPT-Klon läuft lokal auf jedem Rechner : Alpaca/LLaMA ausprobiert (2023) 0.02 
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  5. Hartnett, K.: Sind Sprachmodelle bald die besseren Mathematiker? (2023) 0.02 
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  6. Koch, C.: Was ist Bewusstsein? (2020) 0.02 
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    Date
    17. 1.2020 22:15:11
  7. Wagner, E.: Über Impfstoffe zur digitalen Identität? (2020) 0.02 
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    Date
    4. 5.2020 17:22:40
  8. Engel, B.: Corona-Gesundheitszertifikat als Exitstrategie (2020) 0.02 
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    Date
    4. 5.2020 17:22:28
  9. Arndt, O.: Totale Telematik (2020) 0.02 
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    Date
    22. 6.2020 19:11:24
  10. Arndt, O.: Erosion der bürgerlichen Freiheiten (2020) 0.02 
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    Date
    22. 6.2020 19:16:24
  11. Baecker, D.: ¬Der Frosch, die Fliege und der Mensch : zum Tod von Humberto Maturana (2021) 0.02 
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    Date
    7. 5.2021 22:10:24
  12. Eyert, F.: Mathematische Wissenschaftskommunikation in der digitalen Gesellschaft (2023) 0.02 
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    Source
    Mitteilungen der Deutschen Mathematiker-Vereinigung. 2023, H.1, S.22-25
  13. Wüllner, J.: Obsidian - das Organisationstalent : Ideen, Notizen, Planungen, Projekte - diese App kann für Schule, Uni und Beruf hilfreich sein (2023) 0.02 
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    Date
    27. 1.2023 16:22:55
  14. Fugmann, R.: What is information? : an information veteran looks back (2022) 0.02 
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    Date
    18. 8.2022 19:22:57
  15. Zilm, G.: "Kl ist ein glorifizierter Taschenrechner" (2023) 0.02 
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    Date
    27. 1.2023 16:22:55
  16. Sokolow, A.: Es menschelt in der KI-Welt (2023) 0.02 
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    27. 1.2023 16:22:55
  17. Sokolow, A.: Chaostage bei ChatGPT (2023) 0.02 
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    Date
    27. 1.2023 16:22:55
  18. Danskin, A.; Seeman, D.; Bouchard, M.; Kammerer, K.; Kilpatrick, L.; Mumbower, K.: FAST the inside track : where we are, where do we want to be, and how do we get there? (2023) 0.01 
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  19. Meng, K.; Ba, Z.; Ma, Y.; Li, G.: ¬A network coupling approach to detecting hierarchical linkages between science and technology (2024) 0.01 
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    Abstract
    Detecting science-technology hierarchical linkages is beneficial for understanding deep interactions between science and technology (S&T). Previous studies have mainly focused on linear linkages between S&T but ignored their structural linkages. In this paper, we propose a network coupling approach to inspect hierarchical interactions of S&T by integrating their knowledge linkages and structural linkages. S&T knowledge networks are first enhanced with bidirectional encoder representation from transformers (BERT) knowledge alignment, and then their hierarchical structures are identified based on K-core decomposition. Hierarchical coupling preferences and strengths of the S&T networks over time are further calculated based on similarities of coupling nodes' degree distribution and similarities of coupling edges' weight distribution. Extensive experimental results indicate that our approach is feasible and robust in identifying the coupling hierarchy with superior performance compared to other isomorphism and dissimilarity algorithms. Our research extends the mindset of S&T linkage measurement by identifying patterns and paths of the interaction of S&T hierarchical knowledge.
  20. Zweig, K.; Luttenberger, J.: KI ist keine Magie (2020) 0.01 
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