Working memory resources are needed for processing and maintenance of information during cognitive tasks. Many models have been developed to capture the effects of limited working memory resources on performance. However, most of these models do not account for the finding that different individuals show different sensitivities to working memory demands, and none of the models predicts individual subjects' patterns of performance. We propose a computational model that accounts for differences in working memory capacity in terms of a quantity called (...) source activation, which is used to maintain goal‐relevant information in an available state. We apply this model to capture the working memory effects of individual subjects at a fine level of detail across two experiments. This, we argue, strengthens the interpretation of source activation as working memory capacity. (shrink)

Working memory resources are needed for processing and maintenance of information during cognitive tasks. Many models have been developed to capture the effects of limited working memory resources on performance. However, most of these models do not account for the finding that different individuals show different sensitivities to working memory demands, and none of the models predicts individual subjects' patterns of performance. We propose a computational model that accounts for differences in working memory capacity in terms of a quantity called (...) source activation, which is used to maintain goal‐relevant information in an available state. We apply this model to capture the working memory effects of individual subjects at a fine level of detail across two experiments. This, we argue, strengthens the interpretation of source activation as working memory capacity. (shrink)

In Koriat's paper ''The Feeling of Knowing: Some Metatheoretical Implications for Consciousness and Control,'' he asserts that the feeling of knowing straddles the implicit and explicit, and that these conscious feelings enter into a conscious control process that is necessary for controlled behavior. This assertion allows him to make many speculations on the nature of consciousness itself. We agree that feelings of knowing are produced through a monitoring of one's knowledge, and that this monitoring can affect the control of behavior (...) such as whether or not to search memory for an answer. Further, we believe that monitoring of performance with a strategy can also affect cognition control and strategy selection; however, we also believe that frequently this monitoring and control occurs without conscious awareness. Feeling of knowing has received an inordinate amount of attention because it lies behind the highly recognizable tip-of-the-tongue phenomenon that represents one of the rare cases of conscious monitoring. There are other feelings of knowing which are much more common and are not accompanied by conscious awareness. These are evident in the early selection of a strategy for answering a problem. In our view, the research on feeling of knowing will not resolve the question of whether consciousness is merely epiphenomenal. (shrink)

As a theory of skill acquisition, the instance theory of automatization posits that, after a period of training, algorithm‐based performance is replaced by retrieval‐based performance. This theory has been tested using alphabet‐arithmetic verification tasks (e.g., is A + 4 = E?), in which the equations are necessarily solved by counting at the beginning of practice but can be solved by memory retrieval after practice. A way to infer individuals’ strategies in this task was supposedly provided by the opportunistic‐stopping phenomenon, according (...) to which, if individuals use counting, they can take the opportunity to stop counting when a false equation associated with a letter preceding the true answer has to be verified (e.g., A + 4 = D). In this case, such within‐count equations would be rejected faster than false equations associated with letters following the true answers (e.g., A + 4 = F, i.e., outside‐of‐count equations). Conversely, the absence of opportunistic stopping would be the sign of retrieval. However, through a training experiment involving 19 adults, we show that opportunistic stopping is not a phenomenon that can be observed in the context of an alphabet‐arithmetic verification task. Moreover, we provide an explanation of how and why it was wrongly inferred in the past. These results and conclusions have important implications for learning theories because they demonstrate that a shift from counting to retrieval over training cannot be deduced from verification time differences between outside and within‐count equations in an alphabet‐arithmetic task. (shrink)