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Auflistung nach Autor:in "Linke, Diane"

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  • Zeitschriftenartikel
    Collaborative Speculations on Future Themes for Participatory Design in Germany
    (i-com: Vol. 21, No. 2, 2022) Mucha, Henrik; Correia de Barros, Ana; Benjamin, Jesse Josua; Benzmüller, Christoph; Bischof, Andreas; Buchmüller, Sandra; de Carvalho, Alexandra; Dhungel, Anna-Katharina; Draude, Claude; Fleck, Marc-Julian; Jarke, Juliane; Klein, Stefanie; Kortekaas, Caroline; Kurze, Albrecht; Linke, Diane; Maas, Franzisca; Marsden, Nicola; Melo, Ricardo; Michel, Susanne; Müller-Birn, Claudia; Pröbster, Monika; Rießenberger, Katja Antonia; Schäfer, Mirko Tobias; Sörries, Peter; Stilke, Julia; Volkmann, Torben; Weibert, Anne; Weinhold, Wilhelm; Wolf, Sara; Zorn, Isabel; Heidt, Michael; Berger, Arne
    Participatory Design means recognizing that those who will be affected by a future technology should have an active say in its creation. Yet, despite continuous interest in involving people as future users and consumers into designing novel and innovative future technology, participatory approaches in technology design remain relatively underdeveloped in the German HCI community. This article brings together the diversity of voices, domains, perspectives, approaches, and methods that collectively shape Participatory Design in Germany. In the following, we (1) outline our understanding of participatory practice and how it is different from mere user involvement; (2) reflect current issues of participatory and fair technology design within the German Participatory Design community; and (3) discuss tensions relevant to the field, that we expect to arise in the future, and which we derived from our 2021 workshop through a speculative method. We contribute an introduction and an overview of current themes and a speculative outlook on future issues of Participatory Design in Germany. It is meant to inform, provoke, inspire and, ultimately, invite participation within the wider Computer Science community.
  • Konferenzbeitrag
    Identifying Characteristics of Reflection Triggers in Data Science Ethics Education
    (Proceedings of Mensch und Computer 2024, 2024) Linke, Diane; Müller-Birn, Claudia
    Ethics education in data science aims to teach aspiring data scientists a critical reflective data science practice. However, university courses must bridge the gap between theoretic knowledge of ethics and ethical practice. Towards this, our research aims to understand how we can promote a critical reflective practice through reflection. We, therefore, investigate how data science students start reflecting and what constitutes reflection-triggering contexts in data science education. For this, we introduce a reflective essay assignment and propose a reflection-sensitive inductive content analysis to analyze it. Our findings based on seven student reflective essays suggest that important reflection trigger characteristics in data science ethics education include students’ expectations, a new insight, motivators for reflection related to expectations, teaching formats, and emotions. Our reflection-sensitive analysis is suitable for explorative analysis and creates transparency about existing sensitizing concepts.