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Auflistung nach Autor:in "Kraft, Angelie"

1 - 5 von 5
  • Konferenzbeitrag
    Community and Training in NFDI4DS
    (INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Lorenz, Anna-Lena; Christoforaki, Maria; Hennig, Christine; Kraft, Angelie; von Maltzan, Stephanie; Schimmler, Sonja
    Key to NFDI4DS’s success is an active and vibrant community as establishing a common data culture and practice relies on the community’s participation and acceptance. We address this challenge by leveraging the network of NFDI4DS partners to raise awareness for topics around FAIR data and establish international standards. By identifying requirements, we improve our services and develop new strategies for building and finding user communities.
  • Zeitschriftenartikel
    Multimodal Algebra Learning: From Math Manipulatives to Tangible User Interfaces
    (i-com: Vol. 17, No. 3, 2018) Reinschlüssel, Anke; Alexandrovsky, Dmitry; Döring, Tanja; Kraft, Angelie; Braukmüller, Maike; Janßen, Thomas; Reid, David; Vallejo, Estela; Bikner-Ahsbahs, Angelika; Malaka, Rainer
    While manipulatives have played an important role in children’s mathematics development for decades, employing tangible objects together with digital systems in the classroom has been rarely explored yet. In a transdisciplinary research project with computer scientists, mathematics educators and a textbook publisher, we investigate the potentials of using tangible user interfaces for algebra learning and develop as well as evaluate a scalable system for different use cases. In this paper, we present design implications for tangible user interfaces for algebra learning that were derived from a comprehensive field study in a grade 9 classroom and an expert study with textbook authors, who also are teachers. Furthermore, we present and discuss the resulting system design.
  • Konferenzbeitrag
    NFDI4DS Infrastructure and Services
    (INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Schimmler, Sonja; Wentzel, Bianca; Bleier, Arnim; Dietze, Stefan; Karmakar, Saurav; Mutschke, Peter; Kraft, Angelie; Taffa, Tilahun A.; Usbeck, Ricardo; Boukhers, Zeyd; Auer, Sören; Castro, Leyla J.; Ackermann, Marcel R.; Neumuth, Thomas; Schneider, Daniel; Abedjan, Ziawasch; Latif, Atif; Limani, Fidan; Abu Ahmad, Raia; Rehm, Georg; Attar Khorasani, Sima; Lieber, Matthias
    NFDI4DataScience (NFDI4DS) is a consortium founded to support researchers in all stages of the research data lifecycle in order to conduct their research in line with the FAIR principles. The infrastructure developed targets researchers from a wide range of disciplines working in the field of data science and artificial intelligence. NFDI4DS contributes to systematically understanding the needs and challenges of researchers in various disciplines regarding data science and artificial intelligence, keeping in mind ethical, legal and social aspects. The identified needs will be addressed by support structures such as educational videos and challenges. Transparency, reproducibility and FAIRness will be improved by integrating existing and newly developed services into the NFDI4DS infrastructure, and by systematically adding all digital objects (articles, data, machine learning models, workflows, scripts/code, etc.) to the NFDI4DS research knowledge graph. This paper presents the goals of NFDI4DS, and gives an overview on what the consortium is going to contribute to the data science and artificial intelligence communities. It focuses on existing and newly developed services and their integration.
  • Zeitschriftenartikel
  • Zeitschriftenartikel
    Unpacking Large Language Models: Grundlagen, Perspektiven und Herausforderungen
    (Vol. 48, Large Language Models, 2024) Kraft, Angelie
    Obwohl es statistische Sprachmodelle bereits seit den 1980ern gibt, konnte erst ChatGPT, welches im Winter 2022 veröffentlicht wurde, das Interesse der breiten Gesellschaft für diese Technologie wecken. Große Sprachmodelle oder auf Englisch Large Language Models (abgekürzt LLMs) lassen sich auf verschiedene Weise charakterisieren.