Systems factorial technology (SFT) is a theory-driven set of methodologies oriented toward identification of basic mechanisms, such as parallel versus serial processing, of perception and cognition. Studies employing SFT in visual search with small display sizes have repeatedly shown decisive evidence for parallel processing. The first strong evidence for serial processing was recently found in short-term memory search, using targetdistractor (T-D) similarity as a key experimental variable (Townsend & Fifić, 2004). One of the major goals of the present study was to employ T-D similarity in visual search to learn whether this mode of manipulating processing speed would affect the parallel versus serial issue in that domain. The result was a surprising and regular departure from ordinary parallel or serial processing. The most plausible account at present relies on the notion of positively interacting parallel channels. Perception & Psychophysics 2008, 70 (4), 583-603 doi: 10.3758/PP.70.4.583 M. Fifić, mfific@indiana.edu 584 FIFIĆ, TOWNSEND, AND EIDELS ity of the items in order to explore its effect on architecture. Would the experimental evidence again provide uniform support for parallel processing? How would our simple extensions of the popular three-stage models fare? As will be seen, the results deviated radically from earlier findings.
Factorial Technology Tests of Parallel Versus Serial SystemsSFT is a theory-driven experimental methodology that unveils a taxonomy of four critical characteristics of the cognitive system under study: architecture (serial vs. parallel), stopping rule (exhaustive vs. minimum time), workload capacity (limited, unlimited, or super), and channel independence. The first three are directly tested by our RT methodology. Independence can only be indirectly assessed, although channel dependencies can affect capacity (e.g., Townsend & Wenger, 2004b). To directly test for independence, the investigator needs the accuracy-based analyses afforded by general recognition theory (e.g., Ashby & Townsend, 1986). Architecture and stopping rule are the primary characteristics targeted in this study, but we will see that capacity and, possibly, channel dependencies may be implicated in the interpretations.It is important to observe that all of our assessment procedures are distribution and parameter free. Most experimentation pursues tests of qualitative predictions (e.g., Group A is faster than Group B) of verbally founded predictions. More rigorous modeling typically tests mathematical models that are based on specific probability functions (normal, Gaussian, gamma, etc.) by estimating the parameters that provide a "best" fit to the data and then, sometimes, determining whether the fit is statistically significant or not. If it is, the model is said to be supported by the data; if not, the model is said to be falsified. In the SFT approach, powerful qualitative predictions are made that, if wrong, can falsify huge classes of models-for instance, the set of all mathematical functions that ...