The generalization of deferred imitation in enculturated chimpanzees (Pan troglodytes)

Deferred imitation of object-related actions and generalization of imitation to similar but not identical tasks was assessed in three human-reared (enculturated) chimpanzees, ranging in age from 5 to 9 years. Each ape displayed high levels of deferred imitation and only slightly lower levels of generalization of imitation. The youngest two chimpanzees were more apt to generalize the model's actions when they had displayed portions of the target behaviors at baseline, consistent with the idea that learning is more likely to occur when working within the "zone of proximal development." We argue that generalization of imitation is the best evidence to date of imitative learning in chimpanzees. Electronic Publication     

It's in the sample: the effects of sample size and sample diversity on the breadth of inductive generalization

Developmental studies have provided mixed evidence with regard to the question of whether children consider sample size and sample diversity in their inductive generalizations. Results from four experiments with 105 undergraduates, 105 school-age children (M = 7.2 years), and 105 preschoolers (M = 4.9 years) showed that preschoolers made a higher rate of projections from large samples than from small samples when samples were diverse (Experiments 1 and 3) but not when samples were homogeneous (Experiment 4) and not when the task required a choice between two samples (Experiment 2). Furthermore, when a property occurred in large and diverse samples, preschoolers exhibited a broad pattern of projection, generalizing the property to items from categories not represented in the evidence. In contrast, adults followed a normative pattern of induction and never attributed properties to items from categories not represented in the evidence. School-age children showed a mixed pattern of results.     

We're all in this together now: group performance feedback to increase classroom team data collection

This study's primary goal was to evaluate the use of performance feedback procedures delivered to a classroom team to increase daily data collection. Performance feedback (PFB) was delivered to four classroom teams responsible for the daily collection of data representing student performance during prescribed instructional activities. Using a multiple-baseline design, the effects of the team performance-feedback were evaluated for the target student, and for generalization to data collection for all classroom students. A secondary question evaluated if student on-task behavior correlated with increased data collection. Finally, social validity was investigated to evaluate team satisfaction with the PFB intervention. The results demonstrate improved data collection across all four classroom teams for the target student in each classroom and generalization within classrooms to all remaining students. Slight increases in student on-task behavior were observed in three of the four classrooms, and teacher satisfaction ratings were high.     

Learning to learn: From within-modality to cross-modality transfer during infancy

One critical aspect of learning is the ability to apply learned knowledge to new situations. This ability to transfer is often limited, and its development is not well understood. The current research investigated the development of transfer between 8 and 16 months of age. In Experiment 1, 8- and 16-month-olds (who were established to have a preference to the beginning of a visual sequence) were trained to attend to the end of a sequence. They were then tested on novel visual sequences. Results indicated transfer of learning, with both groups changing baseline preferences as a result of training. In Experiment 2, participants were trained to attend to the end of a visual sequence and were then tested on an auditory sequence. Unlike Experiment 1, only older participants exhibited transfer of learning by changing baseline preferences. These findings suggest that the generalization of learning becomes broader with development, with transfer across modalities developing later than transfer within a modality.     

Generalization gradients in human predictive learning: Effects of discrimination training and within-subjects testing

Generalization gradients have been investigated widely in animal conditioning experiments, but much less so in human predictive learning tasks. Here, we apply the experimental design of a recent study on conditioned fear generalization in humans (Lissek et al., 2008) to a predictive learning task, and examine the effects of a number of relevant procedural parameters drawn from the generalization literature in animal conditioning. Experiment 1 shows that prior discrimination learning and steady-state testing procedures sharpen the gradient; Experiment 2 shows that within-subjects testing of the range of generalization stimuli also sharpens the gradient. In addition, Experiment 2 shows that, in case of very flat initial generalization, an orderly gradient can reveal itself through differential rates of extinction learning. Finally, Experiment 2 also evidenced an orderly gradient of generalization-of-extinction. These results suggest that discrimination processes have an important effect on the generalization of predictive learning in humans, and highlight behavioral analogies between animal conditioning and human predictive learning.     

Adult language use and infant comprehension of English: Associations with encoding and generalization across cues at 20 months

Adult-provided language shapes event memory in children who are preverbal and in those who are able to discuss the past using language. The research conducted to date, however, has not yet established whether infant language comprehension abilities moderate the extent to which preverbal infants benefit from adult-provided supportive language. The present study was conducted to address this question by examining immediate imitation and 1-week delayed generalization across cues in 20-month-old infants as a function of (a) variability in adult-provided linguistic support at encoding and test, (b) infant language comprehension abilities, and (c) their interaction. The provision of supportive adult language at encoding and test was associated with delayed generalization across cues although supportive adult language at encoding did not influence performance at immediate imitation. Infant language comprehension abilities were associated with performance at immediate imitation and delayed generalization across cues. In addition, infant language comprehension abilities moderated the extent to which infants benefited from adult-provided supportive language at encoding and test. The findings contribute to the literature by demonstrating that adult language use and infant language comprehension are independently and differentially associated with immediate imitation and 1-week delayed generalization across cues but also serve to jointly structure event memory in the second year of life.     

Adding Types,But Not Tokens,Affects Property Induction

The extent to which we generalize a novel property from a sample of familiar instances to novel instances depends on the sample composition. Previous property induction experiments have only used samples consisting of novel types (unique entities). Because real-world evidence samples often contain redundant tokens (repetitions of the same entity), we studied the effects on property induction of adding types and tokens to an observed sample. In Experiments 1–3, we presented participants with a sample of birds or flowers known to have a novel property and probed whether this property generalized to novel items varying in similarity to the initial sample. Increasing the number of novel types (e.g., new birds with the target property) in a sample produced tightening, promoting property generalization to highly similar stimuli but decreasing generalization to less similar stimuli. On the other hand, increasing the number of tokens (e.g., repeated presentations of the same bird with the target property) had little effect on generalization. Experiment 4 showed that repeated tokens are encoded and can benefit recognition, but appear to be given little weight when inferring property generalization. We modified an existing Bayesian model of induction (Navarro, Dry, & Lee, 2012) to account for both the information added by new types and the discounting of information conveyed by tokens.     

Contrastive Constraints Guide Explanation‐Based Category Learning

This paper provides evidence for a contrastive account of explanation that is motivated by pragmatic theories that recognize the contribution that context makes to the interpretation of a prompt for explanation. This study replicates the primary findings of previous work in explanation‐based category learning (Williams & Lombrozo, 2010), extending that work by illustrating the critical role of the context in this type of learning. Participants interacted with items from two categories either by describing the items or explaining their category membership. We manipulated the feature overlap between the categories and examined both the explanations generated and acquired knowledge of the categories. Explanations for membership in a given category were influenced by the unprompted contrast category, indicating an important role for contrastive processing in the generation of explanations. The influence of the contrast category was similarly seen in the transfer performance of the participants.     

Three ideal observer models for rule learning in simple languages

Children learning the inflections of their native language show the ability to generalize beyond the perceptual particulars of the examples they are exposed to. The phenomenon of “rule learning”—quick learning of abstract regularities from exposure to a limited set of stimuli—has become an important model system for understanding generalization in infancy. Experiments with adults and children have revealed differences in performance across domains and types of rules. To understand the representational and inferential assumptions necessary to capture this broad set of results, we introduce three ideal observer models for rule learning. Each model builds on the next, allowing us to test the consequences of individual assumptions. Model 1 learns a single rule, Model 2 learns a single rule from noisy input, and Model 3 learns multiple rules from noisy input. These models capture a wide range of experimental results—including several that have been used to argue for domain-specificity or limits on the kinds of generalizations learners can make—suggesting that these ideal observers may be a useful baseline for future work on rule learning.