of changes that have been completed. For these reasons, the major value of socio-technical systems theory appears to be its considerable usefulness as a way of thinking about work systems and their redesign. In its present form, it has only limited use in generating new understanding through quantitative

.). Within the theoret-ical framework of human information processing, we discuss different types of processes underlying verbalization and present a model of how subjects, in re-sponse to an instruction to think aloud, verbalize information that they are attending to in short-term memory (STM). Verbalizing

its omnipresence across the social sciences and humanities, nowhere is there a general statement of framing theory that shows exactly how frames become embedded within and make themselves manifest in a text, or how framing influences thinking. Analysis of this concept suggests how the discipline

, not only in AI, but also in ordinary life, to help people improve their own human intelligence without the assistance of computers. 1

This paper explores the ergonomic implications of the affirmative answer

. Distributed cognition provides a radical reorientation of how to think about designing and supporting human-computer interaction. As a theory it is specifically tailored to understanding interactions among people and technologies. In this article we propose distributed cognition as a new foundation for human

Human creative thinking is analyzed, in particular through the principle of multiple knowledge. It is claimed that current digital computers, however fast, cannot achieve true human-level intelligence, and that the Church-Turing thesis might be inadequate to encapsulate top human thinking

additional and distinct forms of interference. These conclusions challenge widely accepted ideas about attentional resources and probe reaction time methodologies. They also suggest new ways of thinking about continuous dual-task performance, effects of extraneous stimulation (e.g.. stop signals

The mere possibility of Artificial Intelligence (AI) – of machines that can think and act as intelligently as humans – can generate strong emotions. While some enthusiasts are excited by the thought that one day machines may become more intelligent than people, many of its critics view such a

Much of humankind's remarkable mental aptitude can be attributed to analogical ability – the ability to perceive and use relational similarity. In this chapter, we present an overview of analogy and describe its component processes, including structural alignment and inference projection, evaluation, schema abstraction and re-representation. We discuss how these component processes lead to learning and the generation of new knowledge, and review evidence that suggests that greater use of analogy during learning can improve relational retrieval and transfer.