ion was investigated by examining extrapolation behavior in a function-learning task. During training, participants associated stimulus and response magnitudes (in the form of horizontal bar lengths) that covaried according to a linear, exponential, or quadratic function. After training, novel stimulus magnitudes were presented as tests of extrapolation and interpolation. Participants extrapolated well beyond the range of learned responses, and their responses captured the general shape of the assigned functions, with some systematic deviations. Notable individual differences were observed, particularly in the quadratic condition. The number of unique stimulus-response pairs given during training (i.e., density) was also manipulated but did not affect training or transfer performance. Two rule-learning models, an associative-learning model, and a new hybrid model with associative learning and rule-based responding (extrapolation-association model [EXAM]) were evaluated with respect to the transfer data. EXAM best approximated the overall pattern of extrapolation performance. Research on conceptual behavior has historically focused on category learning and the application of categorical knowledge. So dominant is this focus that the terms concept and category are often used interchangeably (e.g., see Bourne, 1966; Smith & Medin, 1981). It is useful to distinguish these two terms, however, because there are many types of concepts that can not be adequately characterized as categories (Busemeyer, McDaniel, & Byun, 1997; Estes, 1995). In general, concepts also pertain to causal variables (e.g., intelligence) and relationships between these variables (e.g., income is correlated with intelligence). This article investigates functions, which conceptualize the relationship between causal variables. By definition, a function maps a set of input values (called the domain of the function) into a set of output values (called the range of the function), such that each input value is assigned only one output value. In function-learning situations, the range is composed of a continuous set of response magnitudes (e.g., predict a student's GPA on the basis of IQ scores). In category learning, on the other hand, outputs consist of discrete and nominal response categories (e.g.,

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According to an order-encoding account of free recall, the free recall of unrelated words is organized according to their order of presentation in the study list, with unusual items attracting more attentional resources to item encoding than usual items, but at the expense of order encoding. This account correctly predicted (a) better free recall and serial-order memory for high-frequency (HF) than low-frequency (LF) words in pure lists and (b) equivalent serial-order memory for HF and LF words but superior recall of LF words in mixed lists. The mixed-list recall results and the finding that overall list recall did not depend on the proportion of HF words comprising a list are inconsistent with G. Gillund and R. M. Shtffrin's (1984) search of associative memory (SAM) explanation. The order-encoding account of the differential effects of other variables (e.g., generation and bizarreness) on free recall in pure versus mixed lists is also discussed.

Four experiments investigated the effects of testing and spacing on the learning of face-name stimulus-response pairs. Experiments 1a and 1b compared the recall of names following intervening tests versus additional study opportunities and found that testing produced better retention of names. Experiments 2 and 3 explored the effects of repeated tests versus study for massed, uniform, or expanded spacing intervals. Tested names were better retained than studied names, spaced names were better retained than massed names, and memory was best for items tested at spaced intervals. Contrary to past findings, expanded schedules did not yield better memory than uniform schedules in either experiment. Theoretical implications for the testing and spacing effects are discussed, along with effective name-learning techniques based on these principles.

Higher recall of bizarre images relative to common images (the bizarreness effect) is consistently found when bizarreness is varied as a within-subject (mixed-list) variable. In Experiment 1, mixed lists, rather than the smaller number of bizarre sentences typically used in such lists, determined the occurrence of the bizarreness effect. Contrary to predictions from expectation-violation theory, Experiments 2 and 3 showed that manipulations designed to augment or attenuate surprise reactions to bizarre sentences had little impact on the bizarreness effect. Experiments 4 and 5 indicated that mixing affected the degree to which participants differentially encoded order information for bizarre and common items. A new account of the bizarreness effect is presented that combines considerations of distinctiveness with the differential use of order information across bizarre and common items.