Socio-Cognitive Engineering


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:

  •     Creating human-centered automation is a multi-disciplinary collaborative activity
  •     Functional modules are defined and tested incrementally in an iterative refinement process
  •     Design decisions are explicitly based on claims analyses, explicating the up-downside tradeoffs
  •     Keeping and sharing the design rationale is key for progress and coherence in automation development


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, a 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:

  1.     The foundation that captures the relevant domain, human factors and technological knowledge.
  2.     The specification of the objectives, use cases, functions (requirements) and the (expected) effects (claims).
  3.     The evaluation that validates these claims and advances the foundation knowledge.