Socio-cognitive

Socio-cognitive or sociocognitive describes integrated cognitive and social properties of systems, processes, functions, models, as well as can indicate the branch of science, engineering or technology, such as socio-cognitive research, socio-cognitive interactions. [1] This term is especially used when complex cognitive and social properties are reciprocally connected and essential for a given problem.

Socio-cognitive research is human factor and socio-organizational factor based, and assumes an integrated knowledge engineering, environment and business modeling perspective, therefore it is not social cognition which rather is a branch of psychology focused on how people process social information.

Socio-cognitive engineering (SCE) includes a set of theoretical interdisciplinary frameworks, methodologies, methods and software tools for the design of human centred technologies,[2] as well as, for the improvement of large complex human-technology systems.

Both above approaches are applicable for the identification and design of a computer-based semi-/proto-Intelligent Decision Support Systems (IDSS),[3] for the operators and managers of large socially critical systems, for high-risk tasks, such as different types of emergency and disaster management, where human errors and socio-cognitive organization vulnerability can be the cause of serious losses.[4]

See also

References

  1. C. J. Hemingway and T. G. Gough (1998), A Socio-Cognitive Theory of Information Systems, Technical Report 98.25, School of Computer Studies, University of Leeds, December 1998.
  2. M. Sharples at al.(2002), Socio-cognitive engineering: a methodology for the design of humancentred technology, European Journal of Operational Research
  3. A. M. Gadomski, et al.(2001)., Towards intelligent decision support systems for emergency managers: the IDA approach. International Journal of Risk Assessment and Management, Vol. 2, No. 3/4.
  4. A. M. Gadomski (2009), Human organisation socio-cognitive vulnerability: the TOGA meta-theory approach to the modelling methodology, International Journal of Critical Infrastructures, Vol. 5, No.1/2 pp. 120-155.

External links

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