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Designing a Transformative Epistemology of the Problematic: A Perspective for Transdisciplinary Sustainability Research
Social Epistemology ( IF 1.625 ) Pub Date : 2020-02-02 , DOI: 10.1080/02691728.2019.1706119
Esther Meyer 1 , Daniela Peukert 1
Affiliation  

ABSTRACT This paper elaborates on the question of how to design an epistemological foundation for problem-oriented, collaborative forms of research, such as transdisciplinary sustainability research. It picks up approaches of twentieth-century European philosophy to the concept of the problematic and design research. The problematic is explained as a historical epistemological effort. Design research shows parallels to the epistemological thinking of the problematic by contributing to a differentiation and historicity of knowledge and knowledge production itself. Designing is constituted by a nexus of conceptual thinking and creative making, and so designs are drafts themselves. We interweave the thinking of the problematic with the practice of designing in order to open an epistemological perspective in and for transdisciplinary sustainability research. We call this a ‘thinking practice of problematic designing,’ which describes an epistemological tool as well as a transformative process. Problematic designing is characterized by always being in the making – its designs can grow beyond their conditions of production. By opening up manifold dimensions of transformation, this epistemological approach is oriented towards complexity, enabling the generation of sound and future-relevant knowledge.

中文翻译:

设计问题的变革性认识论:跨学科可持续性研究的视角

摘要 本文详细阐述了如何为以问题为导向的合作研究形式(例如跨学科可持续性研究)设计认识论基础的问题。它采用了 20 世纪欧洲哲学对问题和设计研究的概念的方法。这个问题被解释为历史认识论的努力。设计研究通过促进知识和知识生产本身的差异化和历史性,显示出与问题认识论思维的相似之处。设计是由概念思维和创意制作的纽带构成的,因此设计本身就是草稿。我们将问题的思考与设计实践交织在一起,以便为跨学科可持续性研究打开认识论视角。我们称其为“问题设计的思维实践”,它描述了一种认识论工具以及一个变革过程。有问题的设计的特点是总是在制作中——它的设计可以超出生产条件。通过打开转换的多种维度,这种认识论方法面向复杂性,能够生成可靠的和未来相关的知识。有问题的设计的特点是总是在制作中——它的设计可以超出生产条件。通过打开转换的多种维度,这种认识论方法面向复杂性,能够生成可靠的和未来相关的知识。有问题的设计的特点是总是在制作中——它的设计可以超出生产条件。通过打开转换的多种维度,这种认识论方法面向复杂性,能够生成可靠的和未来相关的知识。
更新日期:2020-02-02
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