Memory is modified through the act of retrieval. Although retrieving a target piece of information may strengthen the retrieved information itself, it may also serve to weaken retention of related information. This phenomenon, termed retrieval-induced forgetting, has garnered substantial interest for its implications as to why forgetting occurs. The present study attempted to replicate the seminal work by Anderson, Bjork, and Bjork (1994) on retrieval-induced forgetting, given the apparent sensitivity of the effect to certain deviations from the original paradigm developed (...) to study the phenomenon. The study extends the conditions under which retrieval-induced forgetting has been examined by utilizing both a traditional college undergraduate sample (Experiment 1), along with a more diverse internet sample (Experiment 2). In addition, Experiment 3 details a replication attempt of retrieval-induced forgetting using Anderson and Spellman’s (1995) independent cue procedure. Retrieval-induced forgetting was observed when using the traditional retrieval practice paradigm with undergraduate (Experiment 1) and internet (Experiment 2) samples, though the effect was not found when using the independent cue procedure (Experiment 3). Thus, the study can provide an indication as to the robustness of retrieval-induced forgetting to deviations from the traditional college undergraduate samples that have been used in the majority of existing research on the effect. (shrink)

Computational models of semantic memory exploit information about co-occurrences of words in naturally occurring text to extract information about the meaning of the words that are present in the language. Such models implicitly specify a representation of temporal context. Depending on the model, words are said to have occurred in the same context if they are presented within a moving window, within the same sentence, or within the same document. The temporal context model (TCM), which specifies a particular definition of (...) temporal context, has proved useful in the study of episodic memory. The predictive temporal context model (pTCM) uses the same definition of temporal context to generate semantic memory representations. Taken together pTCM and TCM may prove to be part of a general model of declarative memory. (shrink)

Spacing between study trials of an item increases the probability that item will be recalled. This article presents a new model for spacing based on the SAM theory of memory developed by Raaijmakers and Shiffrin (1980, 1981). The model is a generalization of the SAM model as applied to interference paradigms (Mensink & Raaijmakers, 1988, 1989) and may be viewed as a mathematical version of the Component‐Levels theory proposed by Glenberg (1979). It is assumed that on a second presentation of (...) an item, information is added to an existing trace if the episodic memory image corresponding to that item is retrieved. If it is not retrieved, a new image is stored. It is shown that the model predicts many standard findings including the lack of a spacing effect for the recall of at least one of two items each presented once (Ross & Landauer, 1978). (shrink)

This article presents a computational model of the learning of diagnostic knowledge, based on observations of human operators engaged in real-world troubleshooting tasks. We present a model of problem solving and learning in which the reasoner introspects about its own performance on the problem-solving task, identifies what it needs to learn to improve its performance, formulates learning goals to acquire the required knowledge, and pursues its learning goals using multiple learning strategies. The model is implemented in a computer system which (...) provides a case study based on observations of troubleshooting operators and protocol analysis of the data gathered in the test area of an operational electronics manufacturing plant. The model not only addresses issues in human learning, but, in addition, is computationally justified as a uniform, extensible framework for multistrategy learning. (shrink)

Context is an important construct in many domains of cognition, including learning, memory, and emotion. We used dynamical systems methods to demonstrate the episodic nature of experience by showing a natural separation between the scales over which within-context and between-context relationships operate. To do this, we represented an individual's emails extending over about 5 years in a high-dimensional semantic space and computed the dimensionalities of the subspaces occupied by these emails. Personal discourse has a two-scaled geometry with smaller within-context dimensionalities (...) than between-context dimensionalities. Prior studies have shown that reading experience and visual experience have a similar two-scaled structure. Furthermore, the recurrence plot of the emails revealed that experience is predictable and hierarchical, supporting the constructs of some influential theories of memory. The results demonstrate that experience is not scale-free and provide an important target for accounts of how experience shapes cognition. (shrink)