Alternative theories of concept identification among older adults

The purpose of the present experiment was to investigate some predictions of hypothesis testing and S-R association (frequency) theories regarding memory for intratrial events on a conjunctive concept-identification task. They have received extensive study with young adults but not with older subjects. The individual events under investigation were feedback, responses, hypotheses, and stimuli. Hypothesis-testing theory requires subjects to retain information concerning the correct hypothesis from one trial to the next whereas frequency does not. 75 subjects (60-70 yr. old) participated in the study. Subjects had difficulty in recalling the correct hypothesis stated on previous trials. These errors occurred on problems with negative response trials, not with incorrect feedback. The results contradict predictions based on hypothesis-testing models but are consistent with frequency theory. Unlike in the studies based on younger adults, present subjects did not recall the hypothesis very well under the conditions in which hypothesis testing was made part of the primary task.     

Task and distribution sampling affect auditory category learning

There is substantial evidence that two distinct learning systems are engaged in category learning. One is principally engaged when learning requires selective attention to a single dimension (rule-based), and the other is drawn online by categories requiring integration across two or more dimensions (information-integration). This distinction has largely been drawn from studies of visual categories learned via overt category decisions and explicit feedback. Recent research has extended this model to auditory categories, the nature of which introduces new questions for research. With the present experiment, we addressed the influences of incidental versus overt training and category distribution sampling on learning information-integration and rule-based auditory categories. The results demonstrate that the training task influences category learning, with overt feedback generally outperforming incidental feedback. Additionally, distribution sampling (probabilistic or deterministic) and category type (information-integration or rule-based) both affect how well participants are able to learn. Specifically, rule-based categories are learned equivalently, regardless of distribution sampling, whereas information-integration categories are learned better with deterministic than with probabilistic sampling. The interactions of distribution sampling, category type, and kind of feedback impacted category-learning performance, but these interactions have not yet been integrated into existing category-learning models. These results suggest new dimensions for understanding category learning, inspired by the real-world properties of auditory categories.     

The Learning of Natural Configural Strategies

The learning of natural configural strategies, strategies that match people intuitive theories about configural relationship between variables, is studied in a two-cue probability learning paradigm. The main focus is the learning of disjunctive strategy, a strategy in which response depends primarily on the high cue, and conjunctive strategy, a strategy in which response depends primarily on the low cue. We find that people learn disjunctive strategy better when the target of the prediction is human than when it is non-human, and that they learn conjunctive strategy better when the target is non-human. In addition, in a meaningful context, conjunctive strategy is learned better in the short run, but after a prolonged feedback, disjunctive strategy is learned better. In an abstract context, disjunctive strategy is learned better both in the short run and in the long run. The processes that lead to these differences in the learning of conjunctive and disjunctive strategies are discussed.     

A harbor seal can transfer the same/different concept to new stimulus dimensions

We investigated the formation of an abstract concept of same/different in a harbor seal by means of a two-item same/different task. Stimuli were presented on a TFT monitor. The subject was trained to respond according to whether two horizontally aligned white shapes presented on a black background were the same, or different from each other, by giving a no-go or go response. Training comprised of four stages. First, the same/different task was trained with two shapes forming two same problems (A–A and B–B) and two different problems (A–B and B–A). After the learning criterion was reached, training proceeded with new pairs of shapes. In the second experimental stage, every problem was presented just five times before new problems were introduced. We showed that training to criterion with just two shapes resulted in item-specific learning, whereas reducing the number of presentations to five per problem led to the formation of a same/different learning set as well as some restricted relational learning. Training with trial-unique problems in the third stage of this study resulted in the formation of an abstract concept of same/different which was indicated by a highly significant performance in transfer tests with 120 novel problems. Finally, extra-dimensional transfer of the concept was tested. The harbor seal showed a significantly correct performance on transfer tests with 30 unfamiliar pattern and 60 unfamiliar brightness same/different problems, thus demonstrating that the concept is not restricted to the shape dimension originally learned, but can be generalized across stimulus dimensions.     

Reduced information feedback on a selection concept learning task

A procedure to reduce information feedback on selection concept learning problems with nonfixed solutions is described. It has an advantage over similar procedures since it requires no electronic equipment. Female college students solved four concept problems under reduced or standard feedback conditions. The results showed more card choices to solution with reduced feedback and no differences on the other measures. Questionnaire data revealed no significant differences between feedback conditions in perceptions of the task.     

Attribute identification in children as a function of stimulus dimensionality

Thirty-two four-year-old and 32 six-year-old children were presented a conjunctive concept that involved either two values from within a single dimension (unidimensional condition) or two values from different dimensions (bidimensional condition). As predicted, the results showed that the uni- vs bidimensional factor had no effect upon the performance of the younger children, while the older children solved more rapidly in the unidimensional than in the bidimensional condition. The results were interpreted to suggest that the younger children's responding is not under dimensional control and that a major source of difficulty for older children solving the conjunctive concept is the necessity of responding to two dimensions, not to two values.     

Process assessment: An examination of reinforcer effectiveness and predictive validity

This research describes an assessment procedure based on measures of actual learning. First-grade children (N = 120) learned five sight vocabulary words under feedback only, and were then assigned to one of five conditions where they learned five additional words either under feedback, praise, candy, praise and candy, or reproof. In a sixth condition (reciprocal to the first treatment), students learned the first five works under praise and the second five under feedback only. Although results indicated no differences in learning rate under different reinforcement conditions, learning measures under feedback accounted for approximately 39% of the variance in achievement (r = .62), with combined reinforcement learning measures slightly improving prediction (r = .68). The order of treatments had no effect on learning rate. Implications for this process approach to assessment are discussed. Directions for future research are suggested.     

Assessing interactive causal influence

The discovery of conjunctive causes--factors that act in concert to produce or prevent an effect--has been explained by purely covariational theories. Such theories assume that concomitant variations in observable events directly license causal inferences, without postulating the existence of unobservable causal relations. This article discusses problems with these theories, proposes a causal-power theory that overcomes the problems, and reports empirical evidence favoring the new theory. Unlike earlier models, the new theory derives (a). the conditions under which covariation implies conjunctive causation and (b). functions relating observable events to unobservable conjunctive causal strength. This psychological theory, which concerns simple cases involving 2 binary candidate causes and a binary effect, raises questions about normative statistics for testing causal hypotheses regarding categorical data resulting from discrete variables.     

Category dimensionality and feature knowledge: when more features are learned as easily as fewer

Three experiments compared the learning of lower-dimensional family resemblance categories (4 dimensions) with the learning of higher-dimensional ones (8 dimensions). Category-learning models incorporating error-driven learning, hypothesis testing, or limited capacity attention predict that additional dimensions should either increase learning difficulty or decrease learning of individual features. Contrary to these predictions, the experiments showed no slower learning of high-dimensional categories; instead, subjects learned more features from high-dimensional categories than from low-dimensional categories. This result obtained both in standard learning with feedback and in noncontingent, observational learning. These results show that rather than interfering with learning, categories with more dimensions cause individuals to learn more. The authors contrast the learning of family resemblance categories with learning in classical conditioning and probability learning paradigms, in which competition among features is well documented.     

A model of three-choice discrimination learning under complete and incomplete feedback conditions

The Bower and Trabasso model of concept identification was extended to cover problems in which three stimuli were presented simultaneously and S pointed to the one he thought was correct. The E gave complete feedback by indicating the correct stimulus, or incomplete feedback by saying “correct” or “wrong.” The model accurately accounted for the significant difference in total errors between the two feedback conditions by incorporating process assumptions reflecting the logical difference in information content of the two types of feedback. Using a single set of parameter estimates, the model made satisfactory quantitative predictions of several statistics for both feedback conditions. Some deviations from the model's predictions were found in the length of terminal error runs, indicating that Ss were possibly using memory more extensively than posited by the model.     

Long-term symbolic learning

What are the characteristics of long-term learning? We investigated the characteristics of long-term, symbolic learning using the Soar and ACT-R cognitive architectures running cognitive models of two simple tasks. Long sequences of problems were run collecting data to answer fundamental questions about long-term, symbolic learning. We examined whether symbolic learning continues indefinitely, how the learned knowledge is used, and whether computational performance degrades over the long term. We report three findings. First, in both systems, symbolic learning eventually stopped. Second, learned knowledge was used differently in different stages but the resulting production knowledge was used uniformly. Finally, both Soar and ACT-R do eventually suffer from degraded computational performance with long-term continuous learning. We also discuss ACT-R implementation and theoretic causes of ACT-R’s computational performance problems and settings that appear to avoid the performance problems in ACT-R.     

Learning efficient visual search for stimuli containing diagnostic spatial configurations and color-shape conjunctions

Visual search is often slow and difficult for complex stimuli such as feature conjunctions. Search efficiency, however, can improve with training. Search for stimuli that can be identified by the spatial configuration of two elements (e.g., the relative position of two colored shapes) improves dramatically within a few hundred trials of practice. Several recent imaging studies have identified neural correlates of this learning, but it remains unclear what stimulus properties participants learn to use to search efficiently. Influential models, such as reverse hierarchy theory, propose two major possibilities: learning to use information contained in low-level image statistics (e.g., single features at particular retinotopic locations) or in high-level characteristics (e.g., feature conjunctions) of the task-relevant stimuli. In a series of experiments, we tested these two hypotheses, which make different predictions about the effect of various stimulus manipulations after training. We find relatively small effects of manipulating low-level properties of the stimuli (e.g., changing their retinotopic location) and some conjunctive properties (e.g., color-position), whereas the effects of manipulating other conjunctive properties (e.g., color-shape) are larger. Overall, the findings suggest conjunction learning involving such stimuli might be an emergent phenomenon that reflects multiple different learning processes, each of which capitalizes on different types of information contained in the stimuli. We also show that both targets and distractors are learned, and that reversing learned target and distractor identities impairs performance. This suggests that participants do not merely learn to discriminate target and distractor stimuli, they also learn stimulus identity mappings that contribute to performance improvements.     

When does feedback facilitate learning of words?

Some researchers have suggested that although feedback may enhance performance during associative learning, it does so at the expense of later retention. To examine this issue, subjects (N = 258) learned Luganda-English word pairs. After 2 initial exposures to the materials, subjects were tested on each item several times, with the presence and type of feedback varying between subjects. A final test followed after 1 week. Supplying the correct answer after an incorrect response not only improved performance during the initial learning session--it also increased final retention by 494%. On the other hand, feedback after correct responses made little difference either immediately or at a delay, regardless of whether the subject was confident in the response. Practical and theoretical implications are discussed.     

Children's performance in simple and successive-reversal concept identification problems

In Experiment I sixth-grade children learned two concept identification (CI) problems, a simple and a successive-reversal problem, either sequentially (Se) or concurrently (Con). Retention tests given during the CI problems indicated no significant differences in stimulus or response retention for any of the conditions. CI performance was poorer in the Con condition than in the Se condition. Contrary to adult data and predictions derived from the Bower and Trabasso (1964) model, there were fewer informed errors in the successive-reversal problem than the simple problem.     

Written Responses in a Musical Situation as a Function of the Stability of Emotional Behavior

The present study investigated the degree to which learning sets developed during formation of 20 successive concepts. Forty S s were evenly distributed among eight experimental conditions. Conditions compared were rule with attribute identification, conjunctive with disjunctive concepts, and random with ordered arrays of figures. Results showed that learning sets formed with rule identification for both conjunctive and disjunctive concepts, but not with attribute identification. Concepts were easier to learn when using systematic compared to random arrays of figures (of questionable significance), when forming conjunctive rather than disjunctive concepts (not significant), and when using rule identification instead of attribute identification. Procedural differences among studies in this area appear to be major contributors to differences among studies in the results found.     

Attention and learning processes in the identification and categorization of integral stimuli

The relationship between subjects' identification and categorization learning of integral-dimension stimuli was studied within the framework of an exemplar-based generalization model. The model was used to predict subjects' learning in six different categorization conditions on the basis of data obtained in a single identification learning condition. A crucial assumption in the model is that because of selective attention to component dimensions, similarity relations may change in systematic ways across different experimental contexts. The theoretical analysis provided evidence that, at least under unspeeded conditions, selective attention may play a critical role in determining the identification-categorization relationship for integral stimuli. Evidence was also provided that similarity among exemplars decreased as a function of identification learning. Various alternative classification models, including prototype, multiple-prototype, average distance, and "value-on-dimensions" models, were unable to account for the results.     

Hypothesis sampling systems among preoperational and concrete operational kindergarten children

Groups of 60 preoperational and 60 concrete operational kindergarten children received stimulus differentiation training either with feedback (experimental groups) or without (control groups), prior to a series of discrimination-learning problems in which a blank-trial probe, used to detect the child's hypothesis, followed each feedback trial. The concrete operational children manifested significantly better performances than the preoperational on seven of eight dependent measures examined. There were also significant differences in favor of the experimental groups on three dependent measures. While the results were generally consistent with predictions derived from Piagetian stage theory, it was suggested that this theory must be elaborated to include a perspective derived from conventional developmental learning theory in order to adequately account for these and other data.     

The history of imitation in learning theory: the language acquisition process

The concept of imitation has undergone different analyses in the hands of different learning theorists throughout the history of psychology. From Thorndike's connectionism to Pavlov's classical conditioning, Hull's monistic theory, Mowrer's two-factor theory, and Skinner's operant theory, there have been several divergent accounts of the conditions that produce imitation and the conditions under which imitation itself may facilitate language acquisition. In tracing the roots of the concept of imitation in the history of learning theory, the authors conclude that generalized imitation, as defined and analyzed by operant learning theorists, is a sufficiently robust formulation of learned imitation to facilitate a behavior-analytic account of first-language acquisition.     

Cognitive changes in conjunctive rule-based category learning: An ERP approach

When learning rule-based categories, sufficient cognitive resources are needed to test hypotheses, maintain the currently active rule in working memory, update rules after feedback, and to select a new rule if necessary. Prior research has demonstrated that conjunctive rules are more complex than unidimensional rules and place greater demands on executive functions like working memory. In our study, event-related potentials (ERPs) were recorded while participants performed a conjunctive rule-based category learning task with trial-by-trial feedback. In line with prior research, correct categorization responses resulted in a larger stimulus-locked late positive complex compared to incorrect responses, possibly indexing the updating of rule information in memory. Incorrect trials elicited a pronounced feedback-locked P300 elicited which suggested a disconnect between perception, and the rule-based strategy. We also examined the differential processing of stimuli that were able to be correctly classified by the suboptimal single-dimensional rule (“easy” stimuli) versus those that could only be correctly classified by the optimal, conjunctive rule (“difficult” stimuli). Among strong learners, a larger, late positive slow wave emerged for difficult compared with easy stimuli, suggesting differential processing of category items even though strong learners performed well on the conjunctive category set. Overall, the findings suggest that ERP combined with computational modelling can be used to better understand the cognitive processes involved in rule-based category learning.     

Base-rate effects in category learning: a comparison of parallel network and memory storage-retrieval models

Exemplar-memory and adaptive network models were compared in application to category learning data, with special attention to base rate effects on learning and transfer performance. Subjects classified symptom charts of hypothetical patients into disease categories, with informative feedback on learning trials and with the feedback either given or withheld on test trials that followed each fourth of the learning series. The network model proved notably accurate and uniformly superior to the exemplar model in accounting for the detailed course of learning; both the parallel, interactive aspect of the network model and its particular learning algorithm contribute to this superiority. During learning, subjects' performance reflected both category base rates and feature (symptom) probabilities in a nearly optimal manner, a result predicted by both models, though more accurately by the network model. However, under some test conditions, the data showed substantial base-rate neglect, in agreement with Gluck and Bower (1988b).