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11.1 | 1 | === **Principles** === |
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11.1 | 3 | The development of interactive, human-centered automation should be built on theory and empirical research. To support the research & development processes systematically, a Socio-Cognitive Engineering (SCE) method was constructed for building, maintaining and re-using design knowledge based on the following principles: |
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11.1 | 5 | * Creating human-centered automation is a multi-disciplinary collaborative activity |
6 | * Functional modules are defined and tested incrementally in an iterative refinement process | ||
7 | * Design decisions are explicitly based on claims analyses, explicating the up-downside tradeoffs | ||
8 | * Keeping and sharing the design rationale is key for progress and coherence in automation development | ||
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11.1 | 11 | === **Origin** === |
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11.1 | 13 | In an international project, the European Space Agency asked to establish a sound requirements baseline for a "Mission Execution Crew Assistant" (MECA) for future manned deep space missions (e.g. to Mars). As a concise method was lacking for the research & development of the envisioned human-automation system, the first version of the SCE methodology was constructed and applied. This methodology combines approaches from user-centered design, cognitive engineering and requirements analyses to establish a coherent "self-explaining" requirements baseline consisting of: |
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11.1 | 15 | 1. The **foundation** that captures the relevant domain, human factors and technological knowledge. |
16 | 1. The **specification **of the objectives, use cases, functions (requirements) and the (expected) effects (//claims//). | ||
17 | 1. The **evaluation **validates these //claims// and advances the foundation knowledge. | ||
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11.1 | 20 | The SCE activities that provide these outcomes can be performed in parallel. At "some time" they will be integrated into an evaluation (i.e., a prototype or simulation). For this we distinguish development **cycles**. Each development cycle provides a next version of a prototype. **Milestones** are specified for the SCE outcomes that need to be finished for such an evaluation (//note~:// a demonstration can be viewed as a very minimal evaluation). |
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22 | For agile R&D, SCE defines the **Minimal Viable Product (MVP)** as a coherent and concise set of (interim) SCE outcomes, i.e. a coherent set of milestones that lead to the envisioned prototype or simulation. | ||
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9.1 | 24 | WiSCE is the successor to the Socio-Cognitive Engineering Tool (SCET) that was hosted on Atlassian Confluence. WiSCE provides **design rationale** templates and **links** design concepts to each other (see the [[SCE Guide>>url:https://confluence.ewi.tudelft.nl/display/SG]]). The top menu of WiSCE shows the SCE components (i.e., the "boxes" of the Figure: Foundation, Specification and Evaluation), the "meta-models" (i.e., Ontology and Design Patterns, and reference items. General information about the Socio-Cognitive Engineering methodology can be found at [[http:~~/~~/scetool.ewi.tudelft.nl/;>>url:https://confluence.ewi.tudelft.nl/pages/removepage.action?pageId=59539816]] an example application is provided by Neerincx et al. [[^^~[1~] ^^>>url:https://confluence.ewi.tudelft.nl/display/SE/SCE+Example+Home#cite-summary-1-1]]([[https:~~/~~/doi.org/10.3389/frobt.2019.00118>>url:https://doi.org/10.3389/frobt.2019.00118]]). |
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26 | === References === | ||
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29 | |1.|[[1 >>url:https://confluence.ewi.tudelft.nl/display/SE/SCE+Example+Home#cite-1-1]]((( | ||
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7.1 | 30 | Neerincx, M.A. //et al.// (2019). “Socio-Cognitive Engineering of a Robotic Partner for Child’s Diabetes Self-Management,” //Frontiers in Robotics and AI//, vol. 6, [[https:~~/~~/doi.org/10.3389/frobt.2019.00118>>url:https://doi.org/10.3389/frobt.2019.00118]]. |
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4.1 | 31 | ))) |