In the single-store model of memory, the enhanced recall for the last items in a free-recall task (i.e., the recency effect) is understood to reflect a general property of memory rather than a separate short-term store. This interpretation is supported by the finding of a long-term recency effect under conditions that eliminate the contribution from the short-term store. In this article, evidence is reviewed showing that recency effects in the short and long terms have different properties, and it is suggested that 2 memory components are needed to account for the recency effects: an episodic contextual system with changing context and an activation-based short-term memory buffer that drives the encoding of item–context associations. A neurocomputational model based on these 2 components is shown to account for previously observed dissociations and to make novel predictions, which are confirmed in a set of experiments.

www.wjh.harvard.edu/~cfc Chapter 19 in Roberts, M. J. (Ed.) (2007). Integrating the mind: Domain general versus domain specific processes in higher cognition (pp. 449–491). Hove, UK: Psychology Press.

Two studies investigated the relationship between working memory capacity (WMC), adult age, and the resolution of conflict between familiarity and recollection in short-term recognition tasks. Experiment 1 showed a specific deficit of young adults with low WMC in rejecting intrusion probes (i.e., highly familiar probes) in a modified Sternberg task, which was similar to the deficit found in old adults in a parallel experiment (K. Oberauer, 2001). Experiment 2 generalized these results to 3 recognition paradigms (modified Sternberg, local recognition, and n back tasks). Old adults showed disproportional performance deficits on intrusion probes only in terms of reaction times, whereas young adults with low WMC showed them only in terms of errors. The generality of the effect across paradigms is more compatible with a deficit in content–context bindings subserving recollection than with a deficit in inhibition of irrelevant information in working memory. Structural equation models showed that WMC is related to the efficiency of recollection but not of familiarity.

This paper serves as the overview and introduction to a symposium of the same name. The symposium is made up of this introduction and six other papers on cognitive architectures in HCI. As many readers may not be familiar with cognitive architectures, a description of what cognitive architectures are is presented first. In an effort to be accessible to a wide audience, this description is fairly abstract. Once it is clear what is meant by a cognitive architecture, and what a model derived from such an architecture is, then the potential uses of such models in HCI efforts, both research and practical, can be laid out. While there is a great deal of promise, there are still challenges involved with using cognitive models in HCI, which are detailed in the third section. Finally, an overview of the other symposium papers is presented along with some orienting context. 1 What are Cognitive Architectures? There are multiple ways to answer this question. In one sense, a cognitive architecture is a theoretical entity. That is, it is a broad theory of human cognition based on a wide selection of experimental data. Cognitive psychology is replete with theories about particular aspects of human cognition; a cognitive architecture is an attempt to build an integrated theory that encompasses a broad spectrum of what is known about human cognition and performance. Cognitive psychology has, for many years, been driven primarily by a divide-and-conquer approach, so cognitive architectures represent something of a departure

In human-machine-interaction, interruptability and resumption of different tasks are common aspects to influence human performance. To understand human behavior in such situations, we conducted a multitasking experiment where subjects had to perform a test of attention when driving. In this paper, we present an ACT-R/PM model on how people perform the test of attention (secondary task of multitasking scenario). This first model serves as basis for our long-term-objective: to model multitasking, i.e. to simulate how people interrupt a task and recover, considering and integrating individual differences in human performance models. The reported study is a first attempt and smoothes the way for ongoing studies.

How to model different strategies in dynamic task environments In a study about interaction with in-vehicle information systems, participants were put in a dual-tasking scenario. They had to operate a basic research test while driving in a driving simulator. Individual differences were found both in single tasking as well as in multitasking condition. It turned out that during multitasking participants seem to change their interaction strategies. In an immediate follow up single task setting, the participants retain these newly learned strategies. This paper introduces the experimental background of the study, presents corresponding ACT-R models that reflect the participants ` behavior before and after the dual tasking treatment. Individual differences

This paper reviews hybrid cognitive architectures that include both symbolic and non-symbolic components, a currently very active area of cognitive modeling. These architectures support new research directions including models of emotions. This paper reviews existing work with three hybrid architectures and notes some exciting problems that are now tractable. There remain problems creating models in these architectures, which itself remains a research and engineering problem. Thus, it introduces the term cognitive science engineering as an area that would support making models easier to

On the basis of a meta-analysis of pairwise correlations between working memory tasks and cognitive

The main challenge for theories of multitasking is to predict when and how tasks interfere. Here, we focus on interference related to the problem state, a directly accessible intermediate representation of the current state of a task. On the basis of Salvucci and Taatgen’s (2008) threaded cognition theory, we predict interference if 2 or more tasks require a problem state but not when only one task requires one. This prediction was tested in a series of 3 experiments. In Experiment 1, a subtraction task and a text entry task had to be carried out concurrently. Both tasks were presented in 2 versions: one that required maintaining a problem state and one that did not. A significant overadditive interaction effect was observed, showing that the interference between tasks was maximal when both tasks required a problem state. The other 2 experiments tested whether the interference was indeed due to a problem state bottleneck, instead of cognitive load (Experiment 2: an alternative subtraction and text entry experiment) or a phonological loop bottleneck (Experiment 3: a triple-task experiment that added phonological processing). Both experiments supported the problem state hypothesis. To account for the observed behavior, computational cognitive models were developed using threaded cognition within the context of the cognitive architecture ACT-R (Anderson, 2007). The models confirm that a problem state bottleneck can explain the observed interference.

journal homepage: www.elsevier.com/locate/cogpsych