Automatic category search and its transfer.

Abstract

Experiments examined practice and transfer effects in consistently mapped (CM) and variably mapped (VM) semantic search. Experiment 1a examined improvements in reaction time in detecting words from a category as a function of the number of exemplars (4-12) in the category. All CM conditions showed improvement, but there was no significant effect of the number of exemplars. Experiment 1b examined the extent to which training on a subset of exemplars transferred to untrained members of the category. Results showed substantial positive transfer (60%-92%) to untrained exemplars from the trained category. The transfer was better if there were more exemplars in the training set. Experiment 2a showed practice reduced resource sensitivity in CM category search but did not benefit VM category search. Experiment 2b showed that under high workload, untrained exemplars of the trained CM category were detected when first presented to exhibit substantial positive transfer (70%). We conclude that many of the practice effects observed for CM category search take place at either the category level or the category feature level. We suggest that practice results in context activation of the category node or category features. This context activation hypothesis is evaluated with respect to major phenomena relating to automatic and controlled processing.

Automatic Information Processing and High Performance Skills

“…The data appear to support and extend the context activation hypothesis proposed by Schneider and Fisk (1984) as an important locus of CM training. The context activation framework assumes that consistent exposure to the training context is a critical factor leading to performance improvement.…”

“…Fisk and Rogers (1988) found that, in the absence of traditional consistency, context can play an important role in facilitating performance. In addition, the Fisk and Rogers data supported the suggestion that context can also be important for completely consistent tasks (e.g., see Schneider and Fisk, 1984).…”

“…Several previous experiments (e.g., Hale and Eggemeier, 1990;Hassoun and Eggemeier, 1988;Schneider and Fisk, 1984) have demonstrated transfer of automatic processing to untrained exemplars of trained categories within semantic category search paradigms. These results suggest that similar transfer might also be obtained within rule-based alphanumeric search tasks of the type found in C 2 systems.…”

“…This type of rule-based search task is conceptually similar to a semantic category search task that has demonstrated characteristics of automatic processing with extensive practice in a number of previous experiments (e.g., Fisk et al, 1990Fisk et al, , 1992Fisk and Schneider, 1983;Hale and Eggemeier, 1990;Hassoun and Eggemeier, 1988;Schneider and Fisk, 1984). In both tasks, a general category or rule defines the characteristics or boundaries of the search set, and in both cases, successful performance requires that single items be classified as exemplars or non-exemplars of the category or rule.…”

Automaticity: A Theoretical and Conceptual Analysis.

“…Moreover, even if retrieval is required to set the stored algorithm in place, the computation of the algorithm may fall beyond the boundaries of retrieval (at least according to those theorists who argue for a qualitative distinction between memory retrieval and algorithm computation). 5 Support for algorithm-based automaticity has come mainly from skill development studies in which the benefits of practice with consistent algorithms transferred to data that were never encountered during practice (Carlson & Lundy, 1992;Kramer, Strayer, & Buckley, 1990;Schneider & Fisk, 1984;Smith & Lerner, 1986). These benefits were evident in increased speed and efficiency.…”