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Week 1: The State of Human Factors

Week 1: The State of Human Factors. Week 1 Readings & Questions. Readings Smith (1987) Simon (1987) Meister (2003) Questions What is the state of our knowledge in HF? How well is HF knowledge progressing? How well is HF knowledge being applied to technological design?

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Week 1: The State of Human Factors

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  1. Week 1: The State of Human Factors

  2. Week 1 Readings & Questions • Readings • Smith (1987) • Simon (1987) • Meister (2003) • Questions • What is the state of our knowledge in HF? • How well is HF knowledge progressing? • How well is HF knowledge being applied to technological design? • What factors impede or facilitate the progress and application of HF knowledge?

  3. What is the State of Knowledge in HF? • What do we know about? • What do we not know yet?

  4. How well is HF knowledge progressing? • Smith (1987): Many early questions remain unanswered. • What is mental workload? • How much workload is enough? • What are the requirements of simulator fidelity? • When is a warning sufficient? • How do research subjects affect findings? • How is information stored in long-term memory? • Despite a vast increase in research, the field has advanced little.

  5. Smith (1987): What is hindering progress? • HF fails to advance because it fails to promote generalizable research. • HF research is driven by specific needs that reduce generalizability. • The tightly focused research study will be the sword onto which HF falls. • “Blind Empiricism” • Field is inhibited by widely accepted method of slightly modifying previous work—solving very constrained local problems.

  6. How do We Grow HF knowledge? • Smith argues that advancement can be achieved only when research is designed to be generalizable

  7. Generalizability • Can be achieved by: • Considering the more basic elements or phenomenon • Altering review and publication policies. • Putting research into a theoretical framework “It is my firm belief that a solid grasp of [psychological] theory will provide a strong base from which the specific principles of good human factors can be more readily derived.”- Christopher Wickens

  8. Communication of Research • The problem of “reinventing the wheel” • Smith advocates creating a data clearinghouse that would minimize unnecessary replication • Big multifactored problems could be broken into pieces with teams addressing each piece exchanging data • Does the internet serve this purpose?

  9. How well is HF knowledge being applied to technological design? • Simon (1977) writes “…the data being generated is seldom used and, in fact, is often useless… This situation has progressed to a point where persons outside the psychological community are reacting and rejecting what was once considered to be a time-honored ‘science.’” “…our research results are heavily overbalanced with the proliferation of pseudo-knowledge…”

  10. How well is HF knowledge being applied to technological design? • Simon (1987) writes “If the results of all human factors experiments were laid end to end, they still would not reach a conclusion.” • Admiral Hyman Rickover (1977) “[Human Factors] is about as useful as teaching your grandmother how to suck an egg.”

  11. How the discipline of HF Pays the Price • Low funding. • Poor support. • Limited labs and staff. • Ignored findings.

  12. Causes • Paradigmatic Research • Borrowed research methods. • Sanctification of borrowed research methods. • Studying too few factors in a single study.

  13. Causes (cont.) • Holding critical factors constant. • Poor designs that confound findings (e.g., latin square designs) • Thinking that basic and applied research are ends of a continuum. • What are the differences between science and engineering? • What are the differences between research and development?

  14. Causes (cont.) • Failing to isolate sources of variance. • Misinterpreting sources of variance (e.g., error variance).

  15. Simon’s Assessment • Smith’s clearinghouse is impossible. • Smith’s idea is limited by the availability of technology and the enormity of the variable space. • Perhaps in 1987 this was true…

  16. Simon’s Solution • Generality. Include all factors critical to performance. • Economy. Only test those combinations of factors that contain elements of all factors. Proceed at greater resolution only after something is found.

  17. Simon’s Solution (cont.) • Study sources of variance rather than holding them constant. • Order effects • Inter-subject variability • Learning effects • Reap the benefits of greater precision when we understand sources of variance.

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