How Designers Use Design Principles: Design Behaviors and Application Modes

Kruse, Leona Chandra; Purao, Sandeep; Seidel, Stefan

doi:10.17705/1jais.00759

Cited by 9 publications

(4 citation statements)

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“…Hence, recent research has already developed first design principles for domain-dependent EIS development (e.g., Landwehr et al 2022). To extend this sparse research, we position our research as a broad design theory for EIS development (Chandra Kruse et al 2022), that distinguishes itself from recent research:…”

Section: Discussionmentioning

confidence: 99%

A nascent design theory for explainable intelligent systems

et al. 2022

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Due to computational advances in the past decades, so-called intelligent systems can learn from increasingly complex data, analyze situations, and support users in their decision-making to address them. However, in practice, the complexity of these intelligent systems renders the user hardly able to comprehend the inherent decision logic of the underlying machine learning model. As a result, the adoption of this technology, especially for high-stake scenarios, is hampered. In this context, explainable artificial intelligence offers numerous starting points for making the inherent logic explainable to people. While research manifests the necessity for incorporating explainable artificial intelligence into intelligent systems, there is still a lack of knowledge about how to socio-technically design these systems to address acceptance barriers among different user groups. In response, we have derived and evaluated a nascent design theory for explainable intelligent systems based on a structured literature review, two qualitative expert studies, a real-world use case application, and quantitative research. Our design theory includes design requirements, design principles, and design features covering the topics of global explainability, local explainability, personalized interface design, as well as psychological/emotional factors.

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Section: Discussionmentioning

confidence: 99%

A nascent design theory for explainable intelligent systems

et al. 2022

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“…Design principles can be used by design professionals to apply prescriptive knowledge in their design activities (Chandra- Kruse et al, 2022). In doing so, prescriptive information is interpreted and put to use, creating further, more specific design knowledge.…”

Section: Methodsmentioning

confidence: 99%

Smart Participation Design: Prescriptive Knowledge for Bottom-Up Participation

Stanke¹,

Siemon²,

Robra-Bissantz³

2022

CAIS

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This is a PDF file of an unedited manuscript that has been accepted for publication in the Communications of the Association for Information Systems. We are providing this early version of the manuscript to allow for expedited dissemination to interested readers. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered, which could affect the content. All legal disclaimers that apply to the Communications of the Association for Information Systems pertain.

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“…Most of the projects start by first defining the problem space and codifying the problem design knowledge. In the codification of design knowledge, the DSR papers in our analysis tend to follow a structured text-based approach (57 papers), for instance, by drawing on the notion of design principles (Chandra Kruse et al, 2022) or design theories (Gregor & Jones, 2007) or visualization (37 papers) through graphics and screenshots of the developed artifacts. Some of the papers also combine both.…”

Section: Review Of Extant Literaturementioning

confidence: 99%

Sharing Design Knowledge Through Codification in Interdisciplinary DSR Collaborations

Dickhaut,

Janson,

Hevner

et al. 2023

Proceedings of the Annual Hawaii International Conference on System Sciences

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The goals of design science research (DSR) projects are to generate novel and useful artifacts and to produce rigorous and generalizable design knowledge. Often, DSR projects are conducted in collaborative, interdisciplinary project teams. Different disciplinary approaches to codifying design knowledge result in challenging project interactions.To study this situation, we analyze design knowledge codification in interdisciplinary teams over time. We gain insights from a survey of recent DSR papers that have been published in the AIS Senior Scholars' Basket. We then present a detailed case study of a longitudinal project that brought to light issues of sharing design knowledge across disciplinary borders. Drawing from the survey and case study, we provide actionable guidance on how to effectively codify and share design knowledge to support researchers and practitioners to build useful artifacts and to make interdisciplinary design knowledge contributions reusable and applicable.

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How Designers Use Design Principles: Design Behaviors and Application Modes

Cited by 9 publications

References 0 publications

A nascent design theory for explainable intelligent systems

A nascent design theory for explainable intelligent systems

Smart Participation Design: Prescriptive Knowledge for Bottom-Up Participation

Sharing Design Knowledge Through Codification in Interdisciplinary DSR Collaborations

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