Knowledge generation between design, data and theory

A. Brase
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Abstract

Design-based research (DBR) is a diversified research genre: The combination of two worlds – that of research and that of education – and the different backgrounds and intentions of those involved entail different emphases, epistemological ideas, ideas on valuable outcomes and normative claims. This becomes visible in very different kinds of reasoning: No uniform structure of argumentation can be discerned, and so far, a differentiation into clear DBR types has not been convincingly achieved. This is a challenge for the orientation of DBR novices, the quality review of DBR studies, and the legitimation of DBR in the field of educational research. This article provides an empirical contribution to the discussion on argumentation: In a literature review, DBR studies are examined regarding their outcomes, the rationales authors use to justify their outcomes and indications for specific challenges in DBR reasoning. The analysis confirms for the sample that preliminary, prescriptive theory is most common alongside diverse practical outcomes. Authors often justify them with emphasis on variation, iteration, cooperation, and data triangulation. Different (standard) orientations, multi-level reasoning, and sub-studies present challenges for authors and readers, going back to the complexity of DBR projects. To justify their results in a comprehensible way, authors are confronted with the task to actively select an argumentation strategy.
设计、数据和理论之间的知识生成
基于设计的研究(DBR)是一种多样化的研究流派:研究和教育这两个世界的结合,以及参与者的不同背景和意图,导致了不同的侧重点、认识论观点、有价值的成果观点和规范性主张。这一点在截然不同的推理中显而易见:没有统一的论证结构可言,而且迄今为止,尚未令人信服地将 DBR 类型明确区分开来。这对 DBR 新手的定位、DBR 研究的质量审查以及 DBR 在教育研究领域的合法化都是一个挑战。本文为有关论证的讨论提供了经验性的贡献:在文献综述中,对 DBR 研究的结果、作者用来证明其结果的理由以及 DBR 推理中的具体挑战进行了研究。分析表明,在样本中,初步的、规范性的理论与多样化的实践成果最为常见。作者通常通过强调变异、迭代、合作和数据三角测量来证明其合理性。不同的(标准)方向、多层次的推理和子研究给作者和读者带来了挑战,这与 DBR 项目的复杂性有关。为了以易于理解的方式证明其结果的合理性,作者面临着积极选择论证策略的任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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