Although current exemplar models of category learning are flexible and can capture how different features are emphasized for different categories, they still lack the flexibility to adapt to local changes in category learning, such as the effect of different sequences of study. In this paper, we introduce a new model of category learning, the Sequential Attention Theory Model (SAT-M), in which the encoding of each presented item is influenced not only by its category assignment (global context) as in other exemplar models, but also by how its properties relate to the properties of temporally neighboring items (local context). By fitting SAT-M to data from experiments comparing category learning with different sequences of trials (interleaved vs. blocked), we demonstrate that SAT-M captures the effect of local context and predicts when interleaved or blocked training will result in better testing performance across three different studies. Comparatively, ALCOVE, SUSTAIN, and a version of SAT-M without locally adaptive encoding provided poor fits to the results.Moreover, we evaluated the direct prediction of the model that different sequences of training change what learners encode and determined that the best-fit encoding parameter values match learners’ looking times during training.
Edginer, A., & Goldstone, R. L. (2022). Getting situated: Comparative Analysis of Language models with experimental categorization tasks. Proceedings of the 44th Annual Conference of the Cognitive Science Society. (pp. 230-236). Toronto, Canada. Cognitive Science Society.
Common critiques of natural language processing (NLP) methods cite their lack of multimodal sensory information, claiming an inability to learn situated, action-oriented relations through language alone. Barsalou’s (1983) theory of ad hoc categories, which are formed from to achieve goals in real-world scenarios, correspond theoretically to those types of relations with which language models ought to have great difficulty. Recent NLP models have developed dynamic approaches to word representations, where the same word can have different encodings depending on the context in which it appears. Testing these models using categorization tasks with human response data demonstrates that situated properties may be partially captured through semantic analysis. We discuss possible ways in which different notions of situatedness may be distinguished for future development and testing of NLP models.
Gok, S. & Goldstone, R. L. (2022). The counterintuitive interpretations learned from putatively intuitive simulations. Proceedings of the 44th Annual Conference of the Cognitive Science Society. (pp. 2230-2235). Toronto, Canada. Cognitive Science Society.
Reasoning about sampling distributions is notably challenging for humans. It has been argued that the complexity involved in sampling processes can be facilitated by interactive computer simulations that allow learners to experiment with variables. In the current study, we compared the effects of learning sampling distributions through a simulation-based learning (SBL) versus direct instruction (DI) method. While both conditions resulted in similar improvement in rule learning and graph identification, neither condition improved more distant transfer of concepts. Furthermore, the simulation-based learning method resulted in unintuitive and surprising kinds of misconceptions about how sample size affects estimation of parameters while the direct instruction group used correct intuitive judgments more often. We argue that similar perceptual properties of different sampling processes in the SBL condition overrode learners’ intuitions and led them to make conceptual confusions that they would not typically make. We conclude that conceptually important differences should be grounded in easily interpretable and distinguishable perceptual representations in simulation-based learning methods.
Exposing learners to variability during training has been demonstrated to improve performance in subsequent transfer testing. Such variability benefits are often accounted for by assuming that learners are developing some general task schema or structure. However much of this research has neglected to account for differences in similarity between varied and constant training conditions. In a between-groups manipulation, we trained participants on a simple projectile launching task, with either varied or constant conditions. We replicate previous findings showing a transfer advantage of varied over constant training. Furthermore, we show that a standard similarity model is insufficient to account for the benefits of variation, but, if the model is adjusted to assume that varied learners are tuned towards a broader generalization gradient, then a similarity-based model is sufficient to explain the observed benefits of variation. Our results therefore suggest that some variability benefits can be accommodated within instance-based models without positing the learning of some schemata or structure.
Broad empirical evidence suggests that higher-level cognitive processes, such as language, categorization, and emotion, shape human visual perception. Do these higher-level processes shape human perception of all the relevant items within an immediately available scene, or do they affect only some of them? Here, we study categorical effects on visual perception by adapting a perceptual matching task so as to minimize potential non- perceptual influences. In three experiments with human adults (N = 80; N = 80, N = 82), we found that the learned higher-level categories systematically bias human perceptual matchings away from a caricature of their typical color. This effect, however, unequally biased different objects that were simultaneously present within the scene, thus demonstrating a more nuanced picture of top-down influences on perception than has been commonly assumed. In particular, perception of only the object to be matched, not the matching object, was influenced by animal category and it was gazed at less often by participants. These results suggest that category- based associations change perceptual encodings of the items at the periphery of our visual field or the items stored in concurrent memory when a person moves their eyes from one object to another. The main finding of this study calls for a revision of theories of top-down effects on perception and falsify the core assumption behind the El Greco fallacy criticism of them.
Avery, J. E., Goldstone, R. L, & Jones, M. N. (2021). Reconstructing Maps from Text. Cognitive Systems Research. doi: https://doi.org/10.1016/j.cogsys.2021.07.007
Previous research has demonstrated that Distributional Semantic Models (DSMs) are capable of reconstructing maps from news corpora (Louwerse & Zwaan, 2009) and novels (Louwerse & Benesh, 2012). The capacity for reproducing maps is surprising since DSMs notoriously lack perceptual grounding . In this paper we investigate the statistical sources required in language to infer maps, and the resulting constraints placed on mechanisms of semantic representation. Study 1 brings word co-occurrence under experimental control to demonstrate that standard DSMs cannot reproduce maps when word co-occurrence is uniform. Specifically, standard DSMs require that direct co-occurrences between city names in a corpus mirror the proximity between the city locations in the map in order to successfully reconstruct the spatial map. Study 2 presents an instance-based DSM that is capable of reconstructing maps independent of the frequency of co-occurrence of city names.
We explore different ways in which the human visual system can adapt for perceiving and categorizing the environment. There are various accounts of supervised (categorical) and unsupervised perceptual learning, and different perspectives on the functional relationship between perception and categorization. We suggest that common experimental designs are insufficient to differentiate between hypothesized perceptual learning mechanisms and reveal their possible interplay. We propose a relatively underutilized way of studying potential categorical effects on perception, and we test the predictions of different perceptual learning models using a two-dimensional, interleaved categorizationplus- reconstruction task. We find evidence that the human visual system adapts its encodings to the feature structure of the environment, uses categorical expectations for robust reconstruction, allocates encoding resources with respect to categorization utility, and adapts to prevent miscategorizations.
Fyfe, E., de Leeuw, J. R., Carvalho, P. F., Goldstone, R., Sherman, J., … Motz, B. (2021). ManyClasses 1: Assessing the generalizable effect of immediate versus delayed feedback across many college classes. Advances in Methods and Practices in Psychological Science, 4, 1-24. https://doi.org/10.31234/osf.io/4mvyh
Psychology researchers have long attempted to identify educational practices that improve student learning. However, experimental research on these practices is often conducted in laboratory contexts or in a single course, which threatens the external validity of the results. In this article, we establish an experimental paradigm for evaluating the benefits of recommended practices across a variety of authentic educational contexts—a model we call ManyClasses. The core feature is that researchers examine the same research question and measure the same experimental effect across many classes spanning a range of topics, institutions, teacher implementations, and student populations. We report the first ManyClasses study, in which we examined how the timing of feedback on class assignments, either immediate or delayed by a few days, affected subsequent performance on class assessments. Across 38 classes, the overall estimate for the effect of feedback timing was 0.002 (95% highest density interval = [−0.05, 0.05]), which indicates that there was no effect of immediate feedback compared with delayed feedback on student learning that generalizes across classes. Furthermore, there were no credibly nonzero effects for 40 preregistered moderators related to class-level and student-level characteristics. Yet our results provide hints that in certain kinds of classes, which were undersampled in the current study, there may be modest advantages for delayed feedback. More broadly, these findings provide insights regarding the feasibility of conducting within-class randomized experiments across a range of naturally occurring learning environments.
Dubova, M., & Goldstone, R. L. (2021). Categories affect color perception of only some simultaneously present objects. Proceedings of the 43rd Annual Conference of the Cognitive Science Society. (pp. 2041-2048). Vienna, Austria. Cognitive Science Society.
There is broad empirical evidence suggesting that higher-level cognitive processes, such as language, categorization, and emotion, shape human visual perception. For example, categories that we acquire throughout lifetime have been found to alter our perceptual discriminations and distort perceptual processing. However, many of these studies have been criticized as unable to differentiate between immediate perceptual experience and the arguably concomitant processes, such as memory, judgment, and some kinds of attention. Here, we study categorical effects on perception by adapting the perceptual matching task to minimize the potential non-perceptual influences on the results. We found that the learned category-color associations bias human color matching judgments away from their category ideal on a color continuum. This effect, however, unequally biased two objects (probe and manipulator) that were simultaneously present on the screen, thus demonstrating a more nuanced picture of top-down influences on perception than has been assumed both by the theories of categorical perception and the El Greco methodological fallacy. We suggest that only the concurrent memory for visually present objects is subject to a contrast-from-caricature distortion due to category-association learning.
Across three experiments featuring naturalistic concepts (psychology concepts) and naïve learners, we extend previous research showing an effect of the sequence of study on learning outcomes, by demonstrating that the sequence of examples during study changes the representation the learner creates of the study materials. We compared participants’ performance in test tasks requiring different representations and evaluated which sequence yields better learning in which type of tests. We found that interleaved study, in which examples from different concepts are mixed, leads to the creation of relatively interrelated concepts that are represented by contrast to each other and based on discriminating properties. Conversely, blocked study, in which several examples of the same concept are presented together, leads to the creation of relatively isolated concepts that are represented in terms of their central and characteristic properties. These results argue for the integrated investigation of the benefits of different sequences of study as depending on the characteristics of the study and testing situation.
Avery, J. E., Goldstone, R. L., & Jones, M. N. (2020). Reconstructing Maps from Text. Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pp. 557-563). Toronto, CA. Cognitive Science Society.
Previous research has demonstrated that Distributional Semantic Models (DSMs) are capable of reconstructing maps from news corpora (Louwerse & Zwaan, 2009) and novels (Louwerse & Benesh, 2012). The capacity for reproducing maps is surprising since DSMs notoriously lack perceptual grounding (De Vega et al., 2012). In this paper we investigate the statistical sources required in language to infer maps, and resulting constraints placed on mechanisms of semantic representation. Study 1 brings word co-occurrence under experimental control to demonstrate that direct co-occurrence in language is necessary for traditional DSMs to successfully reproduce maps. Study 2 presents an instance-based DSM that is capable of reconstructing maps independent of the frequency of co-occurrence of city names.
Best, R. M., & Goldstone, R. L. (2019). Bias to (and away from) the Extreme: Comparing Two Models of Categorical Perception Effects. Journal of Experimental Psychology: Learning, Memory, and Cognition, 7, 1166-1176.
Categorical Perception (CP) effects manifest as faster or more accurate discrimination between objects that come from different categories compared to objects that come from the same category, controlling for the physical differences between the objects. The most popular explanations of CP effects have relied on perceptual warping causing stimuli near a category boundary to appear more similar to stimuli within their own category and/ or less similar to stimuli from other categories. Hanley and Roberson (2011), on the basis of a pattern not previously noticed in CP experiments, proposed an explanation of CP effects that relies not on perceptual warping, but instead on inconsistent usage of category labels. Experiments 1 and 2 in this paper show a pattern opposite the one Hanley and Roberson pointed out. Experiment 3, using the same stimuli but with different choice statistics (i.e., different probabilities of each face being the target), obtains the same pattern as the one Hanley and Roberson showed. Simulations show that both category label and perceptual models are able to reproduce the patterns of results from both experiments, provided they include information about the choice statistics. This suggests two conclusions. First, the results described by Hanley and Roberson should not be taken as evidence in favor of a category label model. Second, given that participants did not receive feedback on their choices, there must be some mechanism by which participants monitor their own choices and adapt to the choice statistics present in the experiment.
Humans show a striking penchant for creating tools to benefit our own thought processes. Andy Clark (2003, 2008) has convincingly argued that the tools that we as humans recruit become integrated parts of an extended cognitive system that includes us as just one component. By extending cognition beyond our brains, Clark presents an “embiggened” perspective on what it means to be a cognizer and a person more generally. This perspectival shift runs counter to some recent forms of argumentation that in effect work to minimize personhood. For example, arguments for lack of personal culpability can take the form of “It wasn’t my fault. It was the fault of my ___ ” to be filled in, perhaps, by “upbringing,” “genes,” “neurochemistry,” “diet,” or “improperly functioning amygdala.” Instead, Clark (see also Dennett 1989) offers the opposite line of argumentation, according to which we consist not only of our amygdalae and hippocampi but also potentially our glasses, notebooks, friends, supporting technologies, and culture.
Lara-Dammer, F., Hofstadter, D. R., & Goldstone, R. L. (2019). A Computational Model of Scientific Discovery in a Very Simple World, Aiming at Psychological Realism. Journal of Experimental & Theoretical Artificial Intelligence, 1-22. 10.1080/0952813X.2019.1592234
We propose a computational model of human scientific discovery and perception of the world. As a prerequisite for such a model, we simulate dynamic microworlds in which physical events take place, as well as an observer that visually perceives and makes interpretations of events in the microworld. Moreover, we give the observer the ability to actively conduct experiments in order to gain evidence about natural regularities in the world. We have broken up the description of our project into two pieces. The first piece deals with the interpreter constructing relatively simple visual descriptions of objects and collisions within a context. The second phase deals with the interpreter positing relationships among the entities, winding up with elaborated construals and conjectures of mathematical laws governing the world. This paper focuses only on the second phase. As is the case with most human scientific observation, observations are subject to interpretation, and the discoveries are influenced by these interpretations.
Carvalho, P. F., & Goldstone, R. L. (2019). When does interleaving practice improve learning? In J. Dunlosky & K. A. Rawson (Eds.) The Cambridge Handbook of Cognition and Education. Cambridge, England: Cambridge University Press. (pp. 411-436).
As you flip through the pages of this handbook you will notice that the content does not seem to be randomly organized. The content of the handbook is sequenced in a particular way: foundations before general strategies, background before applications, etc. The editors envisaged a sequence of topics, the authors of each topic envisaged a sequence of information in each chapter, and so on. We selected a particular sequence because we considered it to be effective. Deciding how to sequence information takes place all the time in educational contexts, from educators deciding how to organize their syllabus to educational technology designers deciding how to organize a piece of educational software, from handbook editors and writers deciding how to organize their materials, to students making decisions as to how to organize their study. One might imagine that as long as all students study the same materials, regardless of the sequence in which they study it, they will all learn the same information. This could not be further from the truth. In this chapter, we will review evidence of how and why the sequence of study changes what is learned. In doing so, we will try to uncover the powerful ways in which sequence can improve or deter learning.
Goldstone, R. L., Gopnik, A., Thagard, P., & Ullman, T. D. (2018). Models of human scientific discovery. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pp. 29-30). Madison, Wisconsin: Cognitive Science Society.
The scientific understanding of scientific understanding has been a long-standing goal of cognitive science. A satisfying formal model of human scientific discovery would be a major intellectual achievement, requiring solutions to core problems in cognitive science: the creation and use of apt mental models, the prediction of the behavior of complex systems involving interactions between multiple classes of elements, high-level perception of noisy and multiply interpretable environments, and the active interrogation of a system through strategic interventions on it – namely, via experiments. Over the past decades there have been numerous attempts to build formal models that capture what Perkins (1981) calls some of the “mind’s best work” – scientific explanations for how the natural world works by systematic observation, prediction, and testing. Early work by Hebert Simon and his colleagues (Langley, Simon, Bradshaw, & Zytkow, 1987) developed production rule systems employing heuristics to tame extremely large conjoint search spaces of experiments to run and hypotheses to test. Qualitative physics approaches seek to understand physical phenomena by building non-numeric, relational models of the phenomena (Forbus, 1984). Some early connectionist models interpreted scientific explanation in terms of emerging patterns of strongly activated hypotheses that mutually support one another (Thagard, 1992).
Yu, J., Landy, D., & Goldstone, R. L. (2018). Visual flexibility in arithmetic expressions. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pp. 2750-2755). Madison, Wisconsin: Cognitive Science Society.
We investigated whether, and in what, ways people use visual structures to evaluate mathematical expressions. We also explored the relationship between strategy use and other common measures in mathematics education. Participants organized long sum/products when visual structure was available in algebraic expressions. Two experiments showed a similar pattern: One group of participants primarily calculated from left to right, or combined identical numbers together. A second group calculated adjacent pairs. A third group tended to group terms which either produced easy sums (e.g., 6+4), or participated in a global structure. These different strategies were associated with different levels of success on the task, and, in Experiment 2, with differential math anxiety and mathematical skill. Specifically, problem solvers with lower math anxiety and higher math ability tend to group by chunks and easy calculation. These results identify an important role for the perception of coherent structure and pattern identification in mathematical reasoning.
Yu, J., Goldstone, R. L., & Landy, D. (2018). Experientially grounded learning about the roles of variability, sample size, and difference between means in statistical reasoning. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pp. 2744-2749). Madison, Wisconsin: Cognitive Science Society.
Despite its omnipresence in this information-laden society, statistics is hard. The present study explored the applicability of a grounded cognition approach to learning basic statistical concepts. Participants in 2 experiments interacted with perceptually rich computer simulations designed to foster understanding of the relations between fundamental statistical concepts and to promote the ability to reason with statistics. During training, participants were asked to estimate the probability of two samples coming from the same population, with sample size, variability, and difference between means independently manipulated. The amount of learning during training was measured by the difference between participants’ confidence judgments and those of an Ideal Observer. The amount of transfer was assessed by the increase in accuracy from a pretest to a posttest. Learning and transfer were observed when tailored guidance was given along with the perceptually salient properties. Implications of our quantitative measures of human sensitivity to statistical concepts were discussed.
Most maps of science use a network layout; few use a landscape metaphor. Human users are trained in reading geospatial maps, yet most have a hard time reading even simple networks. Prior work using general networks has shown that map-based visualizations increase recall accuracy of data. This paper reports the result of a comparison of two comparable renderings of the UCSD map of science that are: the original network layout and a novel hexmap that uses a landscape metaphor to layout the 554 subdisciplines grouped into 13 color-coded disciplines of science. Overlaid are HITS metrics that show the impact and transformativeness of different scientific subdisciplines. Both maps support the same interactivity, including search, filter, zoom, panning, and details on demand. Users performed memorization, search, and retrieval tasks using both maps. Results did not show any significant differences in how the two maps were remembered or used by participants. We conclude with a discussion of results and planned future work.
Goldstone, R. L., Rogosky, B. J., Pevtzow, R., & Blair, M. (2017). The construction of perceptual and semantic features during category learning. In H. Cohen & C. Lefebvre (Eds.) Handbook of Categorization in Cognitive Science. (pp. 851-882). Amsterdam: Elsevier.
Category learning not only depends upon perceptual and semantic representations; it also leads to the generation of these representations. We describe two series of experiments that demonstrate how categorization experience alters, rather than simply uses, descriptions of objects. In the first series, participants first learned to categorize objects on the basis of particular sets of line segments. Subsequently, participants were given a perceptual part/whole judgment task. Categorization training influenced participants’ part/whole judgments, indicating that whole objects were more likely to be broken down into parts that were relevant during categorization. In the second series, correlations were created or broken between semantic features of word concepts (e.g., ferocious vs. timid and group-oriented vs. solitary animals). The best transfer was found between category learning tasks that shared the same semantic organization of concepts. Together, the experiments support models of category learning that simultaneously create the elements of categorized objects’ descriptions and associate those elements with categories.
Goldstone, R. L., Kersten, A., & Carvalho, P. F. (2017). Categorization and Concepts. In J. Wixted (Ed.) Stevens’ Handbook of Experimental Psychology and Cognitive neuroscience, Fourth Edition, Volume Three: Language & Thought. New Jersey: Wiley. (pp. 275-317).
Concepts are the building blocks of thought. They are critically involved when we reason, make inferences, and try to generalize our previous experiences to new situations. Behind every word in every language lies a concept, although there are concepts, like the small plastic tubes attached to the ends of shoelaces, that we are familiar with and can think about even if we do not know that they are called aglets . Concepts are indispensable to human cognition because they take the “blooming, buzzing confusion” (James, 1890, p. 488) of disorganized sensory experiences and establish order through mental categories. These mental categories allow us to make sense of the world and predict how worldly entities will behave. We see, hear, interpret, remember, understand, and talk about our world through our concepts, and so it is worthy of reflection time to establish where concepts come from, how they work, and how they can best be learned and deployed to suit our cognitive needs.
Trench, M., Tavernini, L. M., & Goldstone, R. L. (2017). Promoting spontaneous analogical transfer by idealizing target representations. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pp. 1206-1211). London, England: Cognitive Science Society.
Recent results demonstrate that inducing an abstract representation of target analogs at retrieval time aids access to analogous situations with mismatching surface features (i.e., the late abstraction principle). A limitation of current implementations of this principle is that they either require the external provision of target-specific information or demand very high intellectual engagement. Experiment 1 demonstrated that constructing an idealized situation model of a target problem increases the rate of correct solutions compared to constructing either concrete simulations or no simulations. Experiment 2 confirmed that these results were based on an advantage for accessing the base analog, and not merely on an advantage of idealized simulations for understanding the target problem in its own terms. This target idealization strategy has broader applicability than prior interventions based on the late abstraction principle, because it can be achieved by a greater proportion of participants and without the need to receive target-specific information.
Carvalho, P. F., & Goldstone, R. L. (2017). The most efficient sequence of study depends on the type of test. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pp. 198-203). London, England: Cognitive Science Society.
Previous research has shown that the sequence in which concepts are studied changes how well they are learned. In a series of experiments featuring naturalistic concepts (psychology concepts) and naïve learners, we extend previous research by showing that the sequence of study changes the representation the learner creates of the study materials. Interleaved study leads to the creation of relatively interrelated concepts that are represented by contrast to each other and based on discriminating properties. Blocked study, instead, leads to the creation of relatively isolated concepts that are represented in terms of their central and characteristic properties. The relative benefits of these representations depend on whether the test of conceptual knowledge requires contrastive or characteristic information. These results argue for the integrated investigation of the benefits of different sequences of study as depending on the characteristics of the study and testing situation as a whole.
Lara-Dammer, F., Hofstadter, D. R., & Goldstone, R. L. (2017). A computer model of context dependent perception in a very simple world. Journal of Experimental & Theoretical Artificial Intelligence, 29:6, 1247-1282. DOI: 10.1080/0952813X.2017.1328463
We propose the foundations of a computer model of scientic discovery that takes into account certain psychological aspects of human observation of the world. To this end, we simulate two main components of such a system. The first is a dynamic microworld in which physical events take place, and the second is an observer that visually perceives entities and events in the microworld. For reason of space, this paper focuses only on the starting phase of discovery, which is the relatively simple visual inputs of objects and collisions.
Goldstone, R. L., Marghetis, T., Weitnauer, E., Ottmar, E. R., & Landy, D. (2017). Adapting perception, action, and technology for mathematical reasoning. Current Directions in Psychological Science, 1-8. DOI: d1o0i.1or1g7/170/.01197673/70926134712717410747808488
Formal mathematical reasoning provides an illuminating test case for understanding how humans can think about things that they did not evolve to comprehend. People engage in algebraic reasoning by 1) creating new assemblies of perception and action routines that evolved originally for other purposes (reuse), 2) adapting those routines to better fit the formal requirements of mathematics (adaptation), and 3) designing cultural tools that mesh well with our perception-action routines to create cognitive systems capable of mathematical reasoning (invention). We describe evidence that a major component of proficiency at algebraic reasoning is Rigged Up Perception-Action Systems (RUPAS), via which originally demanding, strategically-controlled cognitive tasks are converted into learned, automatically executed perception and action routines. Informed by RUPAS, we have designed, implemented, and partially assessed a computer-based algebra tutoring system called Graspable Math with an aim toward training learners to develop perception-action routines that are intuitive, efficient, and mathematically valid.
Meagher, B. J., Carvalho, P. F., Goldstone, R. L., & Nosofsky, R. M. (2017). Organized simultaneous displays facilitate learning of complex natural science categories. Psychonomic Bulletin & Review, DOI 10.3758/s13423-017-1251-6.
Subjects learned to classify images of rocks into the categories igneous, metamorphic, and sedimentary. In accord with the real-world structure of these categories, the to-beclassified rocks in the experiments had a dispersed similarity structure. Our central hypothesis was that learning of these complex categories would be improved through observational study of organized, simultaneous displays of the multiple rock tokens. In support of this hypothesis, a technique that included the presentation of the simultaneous displays during phases of the learning process yielded improved acquisition (Experiment 1) and generalization (Experiment 2) compared to methods that relied solely on sequential forms of study and testing. The technique appears to provide a good starting point for application of cognitive-psychology principles of effective category learning to the science classroom.
Carvalho, P. F., & Goldstone, R. L. (2017). The sequence of study changes what information is attended to, encoded and remembered during category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43, 1699-1719.
The sequence of study influences how we learn. Previous research has identified different sequences as potentially beneficial for learning in different contexts and with different materials. Here we investigate the mechanisms involved in inductive category learning that give rise to these sequencing effects. Across 3 experiments we show evidence that the sequence of study changes what information learners attend to during learning, what is encoded from the materials studied and, consequently, what is remembered from study. Interleaved study (alternating between presentation of 2 categories) leads to an attentional focus on properties that differ between successive items, leading to relatively better encoding and memory for item properties that discriminate between categories. Conversely, when learners study each category in a separate block (blocked study), learners encode relatively more strongly the characteristic features of the items, which may be the result of a strong attentional focus on sequential similarities. These results provide support for the sequential attention theory proposing that inductive category learning takes place through a process of sequential comparisons between the current and previous items. Different sequences of items change how attention is deployed depending on this basic process. Which sequence results in better or worse learning depends on the match between what is encoded and what is required at test.
Transfer of knowledge is the application of knowledge learned in one context to new, dissimilar problems or situations where the knowledge would be useful. Teachers, coaches, camp counselors, parents, and learners often have the experience of a learner showing apparent understanding when questioned about a topic in a way that closely matches how it was initially presented but showing almost no understanding when queried in a new context or with novel examples. This entry further explains the concept of knowledge transfer. It then discusses several different strategies used to support knowledge transfer.
Comparison and reminding have both been shown to support learning and transfer. Comparison is thought to support transfer because it allows learners to disregard non-matching features of superficially different episodes in order to abstract the essential structure of concepts. Remindings promote memory for the individual episodes and generalization because they prompt learners to retrieve earlier episodes during the encoding of later related episodes and to compare across episodes. Across three experiments, we compared the consequences of comparison and reminding on memory and transfer. Participants studied a sequence of related, but superficially different, proverb pairs. In the comparison condition, participants saw proverb pairs presented together and compared their meaning. In the reminding condition, participants viewed proverbs one at a time and retrieved any prior studied proverb that shared the same deep meaning as the current proverb. Experiment 1 revealed that participants in the reminding condition recalled more proverbs than those in the comparison condition. Experiment 2 showed that the mnemonic benefits of reminding persisted over a one-week retention interval. Finally, in Experiment 3, we examined the ability of participants to generalize their remembered information to new items in a task that required participants to identify unstudied proverbs that shared the samemeaning as studied proverbs. Comparison led to worse discrimination between proverbs related to studied proverbs and proverbs unrelated to studied proverbs than reminding. Reminding supported better memory for individual instances and transfer to new situations than comparison.
Carvalho, P.F., Braithwaite, D.W., de Leeuw, J.R., Motz, B.A., & Goldstone, R.L. (2016). An in vivo study of self-regulated study sequencing in introductory psychology courses. PLoS ONE 11(3): e0152115.
Study sequence can have a profound influence on learning. In this study we investigated how students decide to sequence their study in a naturalistic context and whether their choices result in improved learning. In the study reported here, 2061 undergraduate students enrolled in an Introductory Psychology course completed an online homework tutorial on measures of central tendency, a topic relevant to an exam that counted towards their grades. One group of students was enabled to choose their own study sequence during the tutorial (Self-Regulated group), while the other group of students studied the same materials in sequences chosen by other students (Yoked group). Students who chose their sequence of study showed a clear tendency to block their study by concept, and this tendency was positively associated with subsequent exam performance. In the Yoked group, study sequence had no effect on exam performance. These results suggest that despite findings that blocked study is maladaptive when assigned by an experimenter, it may actually be adaptive when chosen by the learner in a naturalistic context.
The idea that cognitive development involves a shift towards abstraction has a long history in psychology. One incarnation of this idea holds that development in the domain of mathematics involves a shift from non-formal mechanisms to formal rules and axioms. Contrary to this view, the present study provides evidence that reliance on non-formal mechanisms may actually increase with age. Participants – Dutch primary school children – evaluated three-term arithmetic expressions in which violation of formally correct order of evaluation led to errors, termed foil errors. Participants solved the problems as part of their regular mathematics practice through an online study platform, and data were collected from over 50,000 children representing approximately 10% of all primary schools in the Netherlands, suggesting that the results have high external validity. Foil errors were more common for problems in which formally lower-priority sub-expressions were spaced close together, and also for problems in which such sub-expressions were relatively easy to calculate. We interpret these effects as resulting from reliance on two non-formal mechanisms, perceptual grouping and opportunistic selection, to determine order of evaluation. Critically, these effects reliably increased with participants’ grade level, suggesting that these mechanisms are not phased out but actually become more important over development, even when they cause systematic violations of formal rules. This conclusion presents a challenge for the shift towards abstraction view as a description of cognitive development in arithmetic. Implications of this result for educational practice are discussed.
Recent research in relational learning has suggested that simple training instances may lead to better generalization than complex training instances. We examined the perceptual encoding mechanisms that might undergird this Simple advantage by testing category and perceptual learning in adults with simplified and traditional (more complex) Chinese scripts. In Experiment 1, participants learned Chinese characters and their English translations, performed a memorization test, and generalized their learning to the corresponding characters written in the other script. In Experiment 2, we removed the training phase and modified the tests to examine transfer based purely on the perceptual similarities between simplified and traditional characters. We found the simple advantage in both experiments. Training with simplified characters produced better generalization than training with traditional characters when generalization relied on either recognition memory or pure perceptual similarities. On the basis of the results of these two experiments,we propose a simple processmodel to explain the perceptual mechanism that might drive this simple advantage, and in Experiment 3 we tested novel predictions of this model by examining the effect of exposure duration on the simple advantage. We found support for our model that the simple advantage is driven primarily by differences in the perceptual encoding of the information available from simple and complex instances. These findings advance our understanding of how the perceptual features of a learning opportunity interact with domain-general mechanisms to prepare learners for transfer.
Prior research has established that while the use of concrete, familiar examples can provide many important benefits for learning, it is also associated with some serious disadvantages, particularly in learners’ ability to recognize and transfer their knowledge to new analogous situations. However, it is not immediately clear whether this pattern would hold in real world educational contexts, in which the role of such examples in student engagement and ease of processing might be of enough importance to overshadow any potential negative impact. We conducted two experiments in which curriculum-relevant material was presented in natural classroom environments, first with college undergraduates and then with middle-school students. All students in each study received the same relevant content, but the degree of contextualization in these materials was varied between students. In both studies, we found that greater contextualization was associated with poorer transfer performance. We interpret these results as reflecting a greater degree of embeddedness for the knowledge acquired from richer, more concrete materials, such that the underlying principles are represented in a less abstract and generalizable form.
Schwartz, D. L, & Goldstone, R. L. (2016). Learning as coordination: Cognitive psychology and education. In L. Corno & E. M. Anderman (Eds.) Handbook of Educational Psychology, 3rd edition. New York: Routledge (pp. 61-75).
The chapter follows a central thesis: A major task of teaching and instruction is to help learners coordinate categories of cognitive processes, capabilities, and representations. While nature confers basic abilities, education synthesizes them to suit the demands of contemporary culture. So, rather than treating categories of learning and instruction as an either–or problem, the problem is how to coordinate learning processes so they can do more together than they can alone. This thesis, which proposes a systems level analysis, is not the norm when thinking about teaching and learning. More common is the belief that learning involves strengthening select cognitive processes rather than coordination across processes. Our chapter, therefore, needs to develop the argument for learning as coordination. To do so, we introduce findings from the field of cognitive psychology.
Learning abstract concepts through concrete examples may promote learning at the cost of inhibiting transfer. The present study investigated one approach to solving this problem: systematically varying superficial features of the examples. Participants learned to solve problems involving a mathematical concept by studying either superficially similar or varied examples. In Experiment 1, less knowledgeable participants learned better from similar examples,while more knowledgeable participants learned better from varied examples. In Experiment 2, prior to learning how to solve the problems, some participants received a pretraining aimed at increasing attention to the structural relations underlying the target concept. These participants, like the more knowledgeable participants in Experiment 1, learned better from varied examples. Thus, the utility of varied examples depends on prior knowledge and, in particular, ability to attend to relevant structure. Increasing this ability can prepare learners to learn more effectively from varied examples.
Cavalho, P. F., Braithwaite, D. W., de Leeuw, J. R., Motz, B. A., & Goldstone, R. L. (2015). Effectiveness of learner-regulated study sequence: An in-vivo study in introductory psychology courses. Proceedings of the Thirty-Seventh Annual Conference of the Cognitive Science Society. (pp. 309-314). Pasadena, CA: Cognitive Science Society.
Study sequence can have a profound impact on learning. Previous research has often shown advantages for interleaved over blocked study, though the reverse has also been found. Learners typically prefer blocking even in situations for which interleaving is superior. The present study investigated learner regulation of study sequence, and its effects on learning in an ecologically valid context – university students using an online tutorial relevant to an exam that counted toward their course grades. The majority of participants blocked study by problem category, and this tendency was positively associated with subsequent exam performance. The results suggest that preference for blocked study may be adaptive under some circumstances, and highlight the importance of identifying task environments under which different study sequences are most effective.
Kost, A., Cavalho, P. F., & Goldstone, R. L. (2015). Can you repeat that? The effect of item repetition on interleaved and blocked study. Proceedings of the Thirty-Seventh Annual Conference of the Cognitive Science Society. (pp. 1189-1194). Pasadena, CA: Cognitive Science Society.
Three experiments explore differences between blocked and interleaved study with and without item repetition. In the first experiment we find that when items are repeated during study, blocked study results in higher test performance than interleaved study. In the second experiment we find that when there is no item repetition, interleaved and blocked study result in equivalent performance during the test phase. In the third experiment we find that when the study is passive and includes no item repetition, interleaved study results in higher test performance. We propose that learners create associations between items of the same category during blocked study and item repetition strengthens these associations. Interleaved study leads to weaker associations between items of the same category and therefore results in worse performance during test when there are item repetitions.
Weitnauer, E., Landy, D., Goldstone, R. L., & Ritter, H. (2015). A computational model for learning structured concepts from physical scenes. Proceedings of the Thirty-Seventh Annual Conference of the Cognitive Science Society. (pp. 2631-2636). Pasadena, CA: Cognitive Science Society.
Category learning is an essential cognitive mechanism for making sense of the world. Many existing computational category learning models focus on categories that can be represented as feature vectors, and yet a substantial part of the categories we encounter have members with inner structure and inner relationships. We present a novel computational model that perceives and learns structured concepts from physical scenes. The perception and learning processes happen simultaneously and interact with each other. We apply the model to a set of physical categorization tasks and promote specific types of comparisons by manipulating presentation order of examples. We find that these manipulations affect the algorithm similarly to human participants that worked on the same task. Both benefit from juxtaposing examples of different categories – especially ones that are similar to each other. When juxtaposing examples from the same category they do better if the examples are dissimilar to each other.
Inductive category learning takes place across time. As such, it is not surprising that the sequence in which information is studied has an impact in what is learned and how efficient learning is. In this paper we review research on different learning sequences and how this impacts learning. We analyze different aspects of interleaved (frequent alternation between categories during study) and blocked study (infrequent alternation between categories during study) that might explain how and when one sequence of study results in improved learning. While these different sequences of study differ in the amount of temporal spacing and temporal juxtaposition between items of different categories, these aspects do not seem to account for the majority of the results available in the literature. However, differences in the type of category being studied and the duration of the retention interval between study and test may play an important role. We conclude that there is no single aspect that is able to account for all the evidence available. Understanding learning as a process of sequential comparisons in time and how different sequences fundamentally alter the statistics of this experience offers a promising framework for understanding sequencing effects in category learning. We use this framework to present novel predictions and hypotheses for future research on sequencing effects in inductive category learning.
Research on how information should be studied during inductive category learning has identified both interleaving of categories and blocking by category as beneficial for learning. Previous work suggests that this mixed evidence can be reconciled by taking into account within- and between-category similarity relations. In this paper we present a new moderating factor. Across two experiments, one group of participants studied categories actively (by studying the objects without correct category assignment and actively figuring out what the category is), either interleaved or blocked. Another group studied the same categories passively (objects and correct category assignment were simultaneously provided). Results from a subsequent generalization task show that whether interleaved or blocked study result in better learning depend on whether study is active or passive. One account of these results is that different presentation sequences and tasks promote different patterns of attention to stimulus components. Passive learning and blocking promote attending to commonalities within categories, while active learning and interleaving promote attending to differences between categories.
Perceptual modules adapt at evolutionary, lifelong, and moment-to-moment temporal scales to better serve the informational needs of cognizers. Perceptual learning is a powerful way for an individual to become tuned to frequently recurring patterns in its specific local environment that are pertinent to its goals without requiring costly executive control resources to be deployed. Mechanisms like predictive coding, categorical perception, and action-informed vision allow our perceptual systems to interface well with cognition by generating perceptual outputs that are systematically guided by how they will be used. In classic conceptions of perceptual modules, people have access to the modules’ outputs but no ability to adjust their internal workings. However, humans routinely and strategically alter their perceptual systems via training regimes that have predictable and specific outcomes. In fact, employing a combination of strategic and automatic devices for adapting perception is one of the most promising approaches to improving cognition.
Weitnauer, E., Carvalho, P. F., Goldstone, R. L., & Ritter, H. (2014). Similarity-based ordering of instances for efficient concept learning. Proceedings of the Thirty-Sixth Annual Conference of the Cognitive Science Society. (pp. 1760-1765). Quebec City, Canada: Cognitive Science Society.
Theories in concept learning predict that interleaving instances of different concepts is especially beneficial if the concepts are highly similar to each other, whereas blocking instances belonging to the same concept provides an advantage for learning low-similarity concept structures. This suggests that the performance in concept learning tasks can be improved by grouping the instances of given concepts based on their similarity. To explore this hypothesis, we use Physical Bongard Problems, a rich categorization task with an open feature space, to analyze the combined effects of comparing dissimilar and similar instances within and across categories. We manipulate the within- and between-category similarity of instances presented close to each other in blocked, interleaved and simultaneous presentation schedules. The results show that grouping instances to promote dissimilar within- and similar between category comparisons improves the learning results, to a degree depending on the strategy used by the learner.
Braithwaite, D. W., & Goldstone, R. L. (2014). Benefits of variation increase with preparation. Proceedings of the Thirty-Sixth Annual Conference of the Cognitive Science Society. (pp. 1940-1945). Quebec City, Canada: Cognitive Science Society.
Abstract concepts are characterized by their underlying structure rather than superficial features. Variation in the examples used to teach abstract concepts can draw attention towards shared structure and away from superficial detail, but too much variation can inhibit learning. The present study tested the possibility that increasing attention to underlying structural relations could alleviate the latter difficulty and thereby increase the benefits of varied examples. Participants were trained with either varied or similar examples of a mathematical concept, and were then tested on their ability to apply the concept to new cases. Before training, some participants received pre training aimed at increasing attention to the structural relations underlying the concept. The relative advantage of varied over similar examples was increased among participants who received the pretraining. Thus, preparation that promotes attention to the relations underlying abstract concepts can increase the benefits of learning from varied examples.
Studying different concepts by frequently alternating between them (i.e., interleaving), improves discriminative contrast between different categories, while studying each con- cept in separate blocks emphasizes the similarities within each category. Interleaved study has been shown to improve learning of high similarity categories by increasing between- category comparison, while blocked study improves learning of low similarity categories by increasing within-category comparison. In addition, interleaved study presents greater temporal spacing between repetitions of each category compared to blocked study, which might present long-term memory benefits. In this study we asked if the benefits of temporal spacing would interact with the benefits of sequencing for making comparisons when testing was delayed, particularly for low similarity categories. Blocked study might be predicted to promote noticing similarities across members of the same category and result in short-term benefits. However, the increase in temporal delay between repetitions inherent to interleaved study might benefit both types of categories when tested after a longer retention interval. Participants studied categories either interleaved or blocked and were tested immediately and 24 h after study. We found an interaction between schedule of study and the type of category studied, which is consistent with the differential emphasis promoted by each sequential schedule. However, increasing the retention interval did not modulate this interaction or resulted in improved performance for interleaved study. Overall, this indicates that the benefit of interleaving is not primarily due to temporal spacing during study, but rather due to the cross-category comparisons that interleaving facilitates. We discuss the benefits of temporal spacing of repetitions in the context of sequential study and how it can be integrated with the attentional bias hypothesis proposed by Carvalho and Goldstone (2014a).
Carvalho, P. F., & Goldstone, R. L., (2014). Putting category learning in order: category structure and temporal arrangement affect the benefit of interleaved over blocked study. Memory & Cognition, 42(3), 481-495.
Recent research in inductive category learning has demonstrated that interleaved study of category exemplars results in better performance than does studying each category in separate blocks. However, the questions of how the category structure influences this advantage and how simultaneous presentation interacts with the advantage are open issues. In this article, we present three experiments. The first experiment indicates that the advantage of interleaved over blocked study is modulated by the structure of the categories being studied. More specifically, interleaved study results in better generalization for categories with high within- and between-category similarity, whereas blocked presentation results in better generalization for categories with low within- and between-category similarity. In Experiment 2, we present evidence that when presented simultaneously, between-category comparisons (interleaved presentation) result in a performance advantage for high-similarity categories, but no differences were found for low-similarity categories. In Experiment 3, we directly compared simultaneous and successive presentation of low-similarity categories. We again found an overall benefit for blocked study with these categories. Overall, these results are consistent with the proposal that interleaving emphasizes differences between categories, whereas blocking emphasizes the discovery of commonalities among objects within the same category.
A longstanding debate concerns the use of concrete versus abstract instructional materials, particularly in domains such as mathematics and science. Although decades of research have focused on the advantages and disadvantages of concrete and abstract materials considered independently, we argue for an approach that moves beyond this dichotomy and combines their advantages. Specifically, we recommend beginning with concrete materials and then explicitly and gradually fading to the more abstract. Theoretical benefits of this “concreteness fading” technique for mathematics and science instruction include: (1) helping learners interpret ambiguous or opaque abstract symbols in terms of well-understood concrete objects, (2) providing embodied perceptual and physical experiences that can ground abstract thinking, (3) enabling learners to build up a store of memorable images that can be used when abstract symbols lose meaning, and (4) guiding learners to strip away extraneous concrete properties and distill the generic, generalizable properties. In these ways, concreteness fading provides advantages that go beyond the sum of the benefits of concrete and abstract materials.
Graphs and tables differentially support performance on specific tasks. For tasks requiring reading off single data points, tables are as good as or better than graphs, while for tasks involving relationships among data points, graphs often yield better performance. However, the degree to which graphs and tables support flexibility across a range of tasks is not well-understood. In two experiments, participants detected main and interaction effects in line graphs and tables of bivariate data. Graphs led to more efficient performance, but also lower flexibility, as indicated by a larger discrepancy in performance across tasks. In particular, detection of main effects of variables represented in the graph legend was facilitated relative to detection of main effects of variables represented in the x-axis. Graphs may be a preferable representational format when the desired task or analytical perspective is known in advance, but may also induce greater interpretive bias than tables, necessitating greater care in their use and design.
The terms concreteness fading and progressive formalization have been used to describe instructional approaches to science and mathematics that use grounded representations to introduce concepts and later transition to more formal representations of the same concepts. There are both theoretical and empirical reasons to believe that such an approach may improve learning outcomes relative to instruction employing only grounded or only formal representations (Freudenthal, 1991; Goldstone & Son, 2005; McNeil & Fyfe, 2012; but see Kaminski, Sloutsky, & Heckler, 2008). Two experiments tested the effectiveness of this approach to instruction in the mathematical domain of combinatorics, using outcome listing and numerical calculation as examples of grounded and formal representations, respectively. The study employed a pretest-training, posttest design. Transfer performance, that is, participants’ improvement from pretest to posttest, was used to assess the effectiveness of instruction received during training. In Experiment 1, transfer performance was compared for 4 types of instruction, which differed only in the types of representation they employed: pure listing (i.e., listing only), pure formalism (i.e., numerical calculation only), list fading (i.e., listing followed by numerical calculation), and formalism first (i.e., listing introduced after numerical calculation). List fading instruction led to transfer performance on par with pure formalism instruction and higher than formalism first and pure listing instruction. In Experiment 2, an enhanced version of list fading training was again compared to pure formalism. However, no difference in transfer performance due to training was found. The results suggest that combining grounded and formal representations can be an effective approach to combinatorics instruction but is not necessarily preferable to using formal representations alone. If both grounded and formal representations are employed, the former should precede rather than follow the latter in the instructional sequence.
Jones, M., & Goldstone, R. L. (2013). The structure of integral dimensions: Contrasting topological and Cartesian representations. Journal of Experimental Psychology: Human Perception and Performance, 39, 111-132.
Diverse evidence shows that perceptually integral dimensions, such as those composing color, are represented holistically. However, the nature of these holistic representations is poorly understood. Extant theories, such as those founded on multidimensional scaling or general recognition theory, model integral stimulus spaces using a Cartesian coordinate system, just as with spaces defined by separable dimensions. This approach entails a rich geometrical structure that has never been questioned but may not be psychologically meaningful for integral dimensions. In particular, Cartesian models carry a notion of orthogonality of component dimensions, such that if 1 dimension is diagnostic for a classification or discrimination task, another can be selected as uniquely irrelevant. This article advances an alternative model in which integral dimensions are characterized as topological spaces. The Cartesian and topological models are tested in a series of experiments using the perceptual-learning phenomenon of dimension differentiation, whereby discrimination training with integral-dimension stimuli can induce an analytic representation of those stimuli. Under the present task design, the 2 models make contrasting predictions regarding the analytic representation that will be learned. Results consistently support the Cartesian model. These findings indicate that perceptual representations of integral dimensions are surprisingly structured, despite their holistic, unanalyzed nature.
Typical disjunctive artificial classification tasks require participants to sort stimuli according to rules such as “x likes cars only when black and coupe OR white and SUV.” For cate-gories like this, increasing the salience of the diagnostic dimensions has two simultaneous effects: increasing the distance between members of the same category and increas-ing the distance between members of opposite categories. Potentially, these two effects respectively hinder and facilitate classification learning, leading to competing predictions for learning. Increasing saliency may lead to members of the same category to be consid-ered less similar, while the members of separate categories might be considered more dissimilar. This implies a similarity-dissimilarity competition between two basic classifica-tion processes. When focusing on sub-category similarity, one would expect more difficult classification when members of the same category become less similar (disregarding the increase of between-category dissimilarity); however, the between-category dissimi-larity increase predicts a less difficult classification. Our categorization study suggests that participants rely more on using dissimilarities between opposite categories than finding similarities between sub-categories.We connect our results to rule- and exemplar-based classification models.The pattern of influences of within- and between-category similarities are challenging for simple single-process categorization systems based on rules or exem-plars. Instead, our results suggest that either these processes should be integrated in a hybrid model, or that category learning operates by forming clusters within each category.
An enormous amount of ink has been spilled in the psychology literature on the topic of similarity. There are two reasons that this seemingly intuitive and prosaic concept has been the subject of such intense scrutiny. First, there is virtually no area of cognitive processing in which similarity does not seem to play a role. William James observed that “This sense of Sameness is the very keel and backbone of our thinking” (James 1890/1950: 459). Ivan Pavlov first noted that dogs would generalize their learned salivation response to new sounds as a function of their similarity to the original tone, and this pattern of generalization appears to be ubiquitous across species and stimuli. People group things together based on their similarity, both during visual processing and categorization. Research suggests that memories are retrieved when they involve similar features or similar processing to a current situation. Problem solutions are likely to be retrieved from similar prior problems, inductive inference is largely based on the similarity between the known and unknown cases, and the list goes on and on.
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Brunel, L., Goldstone, R. L., Vallet, G. Riou, V., & Versace, R. (2013). When Seeing a Dog Activates the Bark: Multisensory Generalization and Distinctiveness Effects. Experimental Psychology, 60, 100-112.
The goal of the present study was to find evidence for a multisensory generalization effect (i.e., generalization from one sensory modality to another sensory modality). The authors used an innovative paradigm (adapted from Brunel, Labeye, Lesourd, & Versace, 2009) involving three phases: a learning phase, consisting in the categorization of geometrical shapes, which manipulated the rules of association between shapes and a sound feature, and two test phases. The first of these was designed to examine the priming effect of the geometrical shapes seen in the learning phase on target tones (i.e., priming task), while the aim of the second was to examine the probability of recognizing the previously learned geometrical shapes (i.e., recognition task). When a shape category was mostly presented with a sound during learning, all of the primes (including those not presented with a sound in the learning phase) enhanced target processing compared to a condition in which the primes were mostly seen without a sound during learning. A pattern of results consistent with this initial finding was also observed during recognition, with the participants being unable to pick out the shape seen without a sound during the learning phase. Experiment 1 revealed a multisensory generalization effect across the members of a category when the objects belonging to the same category share the same value on the shape dimension. However, a distinctiveness effect was observed when a salient feature distinguished the objects within the category (Experiment 2a vs. 2b).
Carvalho, P. F., & Goldstone, R. L. (2013). How to present exemplars of several categories? Interleave during active learning and block during passive learning. Proceedings of the Thirty-Fifth Annual Conference of the Cognitive Science Society. (pp. 1982-1987). Berlin, Germany: Cognitive Science Society.
Research on how information should be presented during inductive category learning has identified both interleaving of categories and blocking by category as beneficial for learning. Previous work suggests that this mixed evidence can be reconciled by taking into account within- and between-category similarity relations. In this paper we present a new moderating factor. One group of participants studied categories actively, either interleaved or blocked. Another group studied the same categories passively. Results from a subsequent generalization task show that active learning benefits from interleaved presentation while passive learning benefits from blocked presentation.
Weitnauer, E., Carvalho, P. F., Goldstone, R. L., & Ritter, H. (2013). Grouping by Similarity Helps Concept Learning. Proceedings of the Thirty-Fifth Annual Conference of the Cognitive Science Society. (pp. 3747-3752). Berlin, Germany: Cognitive Science Society.
In inductive learning, the order in which concept instances are presented plays an important role in learning performance. Theories predict that interleaving instances of different concepts is especially beneficial if the concepts are highly similar to each other, whereas blocking instances belonging to the same concept provides an advantage for learning lowsimilarity concept structures. This leaves open the question of the relative influence of similarity on interleaved versus blocked presentation. To answer this question, we pit withinand between-category similarity effects against each other in a rich categorization task called Physical Bongard Problems. We manipulate the similarity of instances shown temporally close to each other with blocked and interleaved presentation. The results indicate a stronger effect of similarity on interleaving than on blocking. They further show a large benefit of comparing similar between-category instances on concept learning tasks where the feature dimensions are not known in advance but have to be constructed.
After more than 100 years of interest and study, knowledge transfer remains among the most challenging, contentious, and important issues for both psychology and education. In this article, we review and discuss many of the more important ideas and findings from the existing research and attempt to bridge this body of work with the exciting new research directions suggested by the following articles.
Understanding how to get learners to transfer their knowledge to new situations is a topic of both theoretical and practical importance. Theoretically, it touches on core issues in knowledge representation, analogical reasoning, generalization, embodied cognition, and concept formation. Practically, learning without transfer of what has been learned is almost always unproductive and inefficient. Although schools often measure the efficiency of learning in terms of speed and retention of knowledge, a relatively neglected and subtler component of efficiency is the generality and applicability of the acquired knowledge. This special issue of Educational Psychologist collects together new approaches toward understanding and fostering appropriate transfer in learners. Three themes that emerge from the collected articles are (a) the importance of the perspective/stance of the learner for achieving robust transfer, (b) the neglected role of motivation in determining transfer, and (c) the existence of specific, validated techniques for teaching with an eye toward facilitating students’ transfer of their learning.
Son, J. Y., Smith, L. B., Goldstone, R. L., & Leslie, M. (2012). The Importance of Being Interpreted: Grounded Words and Children’s Relational Reasoning, Frontiers in Developmental Psychology, 3, 1-12.
Although young children typically have trouble reasoning relationally, they are aided by the presence of relational words (e.g., Gentner & Rattermann, 1991). They also reason well about commonly experienced event structures (e.g., Fivush, 1984). Relational words may benefit relational reasoning because they activate well-understood event structures. Two candidate hypotheses were tested: (1) the Schema hypothesis, according to which words help relational reasoning because they are grounded in schematized experiences and (2) the Optimal Vagueness hypothesis, by which words benefit relational reasoning because the activated schema is open enough (without too much specificity) so that it can be applied analogically to novel problems. Four experiments examine these two hypotheses by examining how training with a label influences schematic interpretations of a scene, the kinds of scenes that are conducive to schematic interpretations, and whether children must figure out the interpretation themselves to benefit from the act of interpreting a scene as an event. Experiment 1 shows the superiority of schema-evoking words over words that do not connect to schematized experiences. Experiments 2 and 3 further reveal that these words must be applied to vaguely related perceptual instances rather than unrelated or concretely related instances in order to draw attention to relational structure. Experiment 4 provides evidence that even when children do not work out an interpretation for themselves, just the act of interpreting an ambiguous scene is potent for relational generalization. The present results suggest that relational words (and in particular their meanings) are created from the act of interpreting a perceptual situation in the context of a word grounded in meaningful experiences.
Braithwaite, D. W., & Goldstone, R. L. (2012). Inducing mathematical concepts from specific examples: The role of schema-level variation. Proceedings of the Thirty-Fourth Annual Conference of the Cognitive Science Society. (pp. 138-143). Sapporo, Japan: Cognitive Science Society.
Previous research suggests that comparing multiple specific examples of a general concept can promote knowledge transfer. The present study investigated whether this approach could be made more effective by systematic variation in the semantic content of the specific examples. Participants received instruction in a mathematical concept in the context of several examples, which instantiated either a single semantic schema (non-varied condition) or two different schemas (varied condition). Schema-level variation during instruction led to better knowledge transfer, as predicted. However, this advantage was limited to participants with relatively high performance before instruction. Variation also improved participants’ ability to describe the target concept in abstract terms. Surprisingly, however, this ability was not associated with successful knowledge transfer.
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Carvalho, P. F., & Goldstone, R. L. (2012). Category structure modulates interleaving and blocking advantage in inductive category acquisition. Proceedings of the Thirty-Fourth Annual Conference of the Cognitive Science Society. (pp. 186-191). Sapporo, Japan: Cognitive Science Society.
Research in inductive category learning has demonstrated that interleaving exemplars of categories results in better performance than presenting each category in a separate block. Two experiments indicate that the advantage of interleaved over blocked presentation is modulated by the structure of the categories being presented. More specifically, interleaved presentation results in better performance for categories with high within- and between-category similarity while blocked presentation results in better performance for categories with low within- and between-category similarity.
This interaction is predicted by accounts in which blocking promotes discovery of features shared by the members of a category whereas interleaving promotes discovery of features that discriminate between categories.
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Engle, J. T. Feng, Y., Goldstone, R. L. (2012). Mining relatedness graphs for data integration. Proceedings of the Thirty-Fourth Annual Conference of the Cognitive Science Society. (pp. 1524-1529). Sapporo, Japan: Cognitive Science Society.
In this paper, we present the AbsMatcher system for schema matching which uses a graph based approach. The primary contribution of this paper is the development of new types of relationships for generating graph edges and the effectiveness of integrating schemas using those graphs. AbsMatcher creates a graph of related attributes within a schema, mines similarity between attributes in different schemas, and then combines all information using the ABSURDIST graph matching algorithm. The attribute-to-attribute relationships this paper focuses on are semantic in nature and have few requirements for format or structure. These relationships sources provide a baseline which can be improved upon with relationships specific to formats, such as XML or a relational database. Simulations demonstrate how the use of automatically mined graphs of within-schema relationships, when combined with cross-schema pair-wise similarity, can result in matching accuracy not attainable by either source of information on its own.
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Hendrickson, A. T., Carvalho, P. F., & Goldstone, R. L. (2012). Going to extremes: The influence of unsupervised categories on the mental caricaturization of faces and asymmetries in perceptual discrimination. Proceedings of the Thirty-Fourth Annual Conference of the Cognitive Science Society. (pp. 1662-1667). Sapporo, Japan: Cognitive Science Society.
Recent re-analysis of traditional Categorical Perception (CP) effects show that the advantage for between category judgments may be due to asymmetries of within-category judgments (Hanley & Roberson, 2011). This has led to the hypothesis that labels cause CP effects via these asymmetries due to category label uncertainty near the category boundary. In Experiment 1 we demonstrate that these “within-category” asymmetries exist before category training begins. Category learning does increase the within-category asymmetry on a category relevant dimension but equally on an irrelevant dimension. Experiment 2 replicates the asymmetry found in Experiment 1 without training and shows that it does not increase with additional exposure in the absence of category training. We conclude that the within-category asymmetry may be a result of unsupervised learning of stimulus clusters that emphasize extreme instances and that category training increases this caricaturization of stimulus representations.
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Hendrickson, A. T., Kachergis, G., Fausey, C. M., & Goldstone, R. L. (2012). Re-learning labeled categories reveals structured representations. Proceedings of the Thirty-Fourth Annual Conference of the Cognitive Science Society. (pp. 1668-1673). Sapporo, Japan: Cognitive Science Society.
How do people learn to group and re-group objects into labeled categories? In this paper, we examine mechanisms that guide how people re-represent categories. In two experiments, we examine what is easy and what is hard to relearn as people update their knowledge about labeled groups of objects. In Study 1, we test how people learn and re-learn to group objects that share no perceptual features. Data suggest that people easily learn to re-label objects when the category structure remains the same. In Study 2, we test whether more general types of labeling conventions — words that do or do not correspond with object similarities — influence learning and re-learning. Data suggest that people are able to learn either kind of convention and may have trouble switching between them when re-structuring their knowledge. Implications for category learning, second language acquisition and updating representations are discussed.
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Ottmar, E., Landy, D., & Goldstone, R. L. (2012). Teaching the Perceptual Structure of Algebraic Expressions: Preliminary Findings from the Pushing Symbols Intervention. Proceedings of the Thirty- Fourth Annual Conference of the Cognitive Science Society. (pp. 2156-2161). Sapporo, Japan: Cognitive Science Society.
We describe an intervention being developed by our research team, Pushing Symbols (PS). This intervention is designed to encourage learners to treat symbol systems as physical objects that move and change over time according to dynamic principles. We provide students with the opportunities to explore algebraic structure by physically manipulating and interacting with concrete and virtual symbolic systems that enforce rules through constraints on physical transformations. Here we present an instantiation of this approach aimed at helping students learn the structure of algebraic notation in general, and in particular learn to simplify like terms. This instantiation combines colored symbol tiles with a new touchscreen software technology adapted from the commercial Algebra Touch software. We present preliminary findings from a study with 70 middle-school students who participated in the PS intervention over a three-hour period.
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Terai, A., & Goldstone, R. L. (2012). An Experimental Examination of Emergent Features in Metaphor Interpretation Using Semantic Priming Effects. Proceedings of the Thirty- Fourth Annual Conference of the Cognitive Science Society. (pp. 2399-2404). Sapporo, Japan: Cognitive Science Society.
In comprehension of the metaphor “TOPIC is VEHICLE,” emergent features in the interpretation of metaphors are characteristic neither of the topic nor the vehicle. An experiment examines the hypothesis that new features emerge as metaphoric interpretations through association with nonemergent features connected with the topic, vehicle, or both. In the experiment, participants were presented with a nonemergent feature as a prime, a metaphor, and an emergent feature, sequentially. Participants were then asked to respond as to whether the emergent feature is an appropriate interpretation of the metaphor. The results showed that primed non-emergent features derived from the vehicle facilitate the recognition of emergent features. The results support an account in which new features emerge through two processes – non-emergent features are recognized as interpretations of the metaphor and then these non-emergent features facilitate the recognition of emergent features.
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Goldstone, R. L., Kersten, A., & Cavalho, P. F. (2012). Concepts and Categorization. In A. F. Healy & R. W. Proctor (Eds.) Comprehensive handbook of psychology, Volume 4: Experimental psychology. (pp. 607-630). New Jersey: Wiley.
Issues related to concepts and categorization are nearly ubiquitous in psychology because of people’s natural tendency to perceive a thing as something. We have a powerful impulse to interpret our world. This act of interpretation, an act of “seeing something as X” rather than simply seeing it (Wittgenstein, 1953), is fundamentally an act of categorization. The attraction of research on concepts is that an extremely wide variety of cognitive acts can be understood as categorizations (Murphy, 2002).
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Son, J. Y., Smith, L. B., & Goldstone, R. L. (2011). Connecting instances to promote children’s relational reasoning. Journal of Experimental Child Psychology, 108, 260-277.
The practice of learning from multiple instances seems to allow children to learn about relational structure. The experiments reported here have focused on two issues regarding relational learning from multiple instances: (1) what kind of perceptual situations foster such learning and (2) how particular object properties, such as complexity or similarity, interact with relational learning. Two kinds of perceptual situations were of interest here: simultaneous view, where instances are viewed at once, and sequential view, instances are viewed one at a time, one right after the other. We examine the influence of particular perceptual situations and object properties using two tests of relational reasoning: a common match-to-sample task (where new instances are compared to a common sample) and a variable match-to-sample task (where new instances are compared to a sample that varies on each trial). Experiments 1 and 2 indicate that simultaneous presentation of even highly dissimilar instances, one simple and one complex, effectively connects them together and improves relational generalization in both match-to-sample tasks. Experiment 3 showed simple samples are more effective than complex ones in the common match-to-sample task. However, when one instance is not used a common sample and various pairs of instances are simply compared (Experiment 4), simple and rich instances are equally effective at promoting relational learning. These results bear on our understanding of how children connect instances and how those initial connections affect learning and generalization.
Terai, A. & Goldstone, R. L. (2011). Processing emergent features in metaphor comprehension. Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society. (pp. 2043-2048). Boston, Massachusetts: Cognitive Science Society.
This study examines the processing of emergent features in metaphors. Emergent features are metaphoric interpretations that are characteristic neither of the target nor the vehicle. In the first experiment, participants were asked to respond as to whether a verbal feature is an appropriate interpretation of the metaphor, which was presented as a prime. They are asked to respond immediately after a tone is presented which has a variable temporal lag after the feature. The timing of each tone controlled the participants’ response times. The results show that the response deadline given to the participants only slightly affected their judgments. In a second experiment, the time to interpret a metaphor was controlled by varying the pre- sentation time of the metaphor. The results showed that emer- gent features require more time for recognition as a metaphoric interpretation than do non-emergent features. The results sup- port the hypothesis that interaction among features causes feature emergence.
Day, S. B., Manlove, S., & Goldstone, R. L. (2011). Transfer, and the effects of context outside of the training task. Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society. (pp. 2637-2642). Boston, Massachusetts: Cognitive Science Society.
While the use of concrete, contextualized and personally relevant examples can benefit learners in terms of comprehension and motivation, these types of examples can come with a cost. Examples may become too bound to their particular context, and individuals may have a difficult time recognizing when the underlying principles are relevant in new situations. In the current study, we provide evidence that contextualization may impair knowledge transfer even when that context occurs outside of the training example itself. Specifically, when students were taught about positive feedback systems in the context of polar ice-albedo effects, those individuals that had previously learned about the effects of global warming on polar bear populations showed reliably poorer transfer performance.
Previous research has consistently found that spontaneous analogical transfer is strongly tied to concrete and contextual similarities between the cases. However, that work has largely failed to acknowledge that the relevant factor in transfer is the similarity between individuals’ mental representations of the situations, rather than the overt similarities between the cases themselves. Across several studies, we find that participants are able to transfer strategies learned from a perceptually concrete simulation of a physical system to a task with very dissimilar content and appearance. This transfer is reflected in better performance on the transfer task when its underlying dynamics are consistent rather than inconsistent with the preceding training task. Our data indicate that transfer in these tasks relies on the perceptual and spatial nature of the training task, but does not depend on direct interaction with the system, with participants performing equally well after simply observing the concrete simulation. We argue that participants in these studies are using the concrete, spatial, dynamic information presented in the training simulation as the basis for a concretely similar mental model of the dissimilar transfer task. Unexpectedly, our data consistently showed that transfer was independent of reported recognition of the analogy between tasks: while such recognition was associated with better overall performance, it was not associated with better transfer (in terms of applying an appropriate strategy). Together, these findings suggest that analogical transfer between overtly dissimilar cases may be much more common—and much more relevant to our cognitive processing—than is generally assumed.
Byrge, L. A., & Goldstone, R. L. (2011). Distinguishing levels of grounding that underlie transfer of learning. Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society. (pp. 2818-2823). Boston, Massachusetts: Cognitive Science Society.
We find that transfer of learning from a perceptually concrete simulation to an isomorphic but superficially dissimilar text- based problem is sensitive to the congruence between the force dynamics common to both systems and the kinesthetic schema induced via action in the first, perceptually concrete, simulation. Counterintuitively, incompatibility between the force dynamics and the kinesthetic schema has a beneficial effect on transfer, relative to compatibility as well as an unrelated control. We suggest that this incompatibility between action and system dynamics may make the system’s relational structure more salient, leading to a more flexible conceptualization that ultimately benefits transfer. In addition, we suggest that too much “action concreteness” in hands-on learning may actually limit transfer, by fostering an understanding that is tied to that action and therefore less available for transfer in situations where that action is no longer relevant.
Braithwaite, D. W., & Goldstone, R. L. (2011). Effects of grounded and formal representations on combinatorics learning. Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society. (pp. 3431-3436). Boston, Massachusetts: Cognitive Science Society.
Two experiments examined the differential effects of ground- ed and formal representations on learning of mathematics. Both involved combinatorics, using outcome listing and com- binatorics formulas as examples of grounded and formal rep- resentations, respectively. Experiment 1 compared perfor- mance on near and far transfer problems following instruc- tions involving listing or formulas. Instruction in formulas led to more near transfer, while far transfer performance did not differ by condition. Experiment 2 compared performance fol- lowing four types of instruction: listing only, formulas only, listing fading (listing followed by formulas), and listing intro- duction (formulas followed by listing). The listing fading condition led to performance on par with the formulas only condition, and for near transfer problems, significantly higher than the listing introduction and pure listing conditions. The results support the inclusion of grounded representations in combinatorics instruction, and suggest that such representa- tions should precede rather than follow formal representations in the instructional sequence.
Carvalho, P. F., & Goldstone, R. L. (2011). Sequential similarity and comparison effects in category learning. Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society. (pp. 2977-2982). Boston, Massachusetts: Cognitive Science Society.
Order effects in category learning have been previously demonstrated. Specifically, alternation between exemplars of two categories has been shown to improve category learning and discrimination, compared to presenting exemplars of each category in separate blocks. However, the mechanisms under- lying order effects are still not completely known. Remaining issues pertain to the relevance of within and between category similarities, and the role of comparing sequentially presented objects. We present two experiments: in Experiment 1 within- and between-category similarity are manipulated simultane- ously with presentation schedule. In Experiment 2, alternation between categories is compared to two blocked conditions: one in which very similar stimuli are presented successively, and another in which they are dissimilar. Our results show a clear overall advantage of low similarity in categorization performance, but no effect of presentation schedule. Also, al- ternation between categories is shown to result in better per- formance than the blocked condition with more dissimilar stimuli.
Day, S., & Goldstone, R. L. (2010). The Effects of Similarity and Individual differences on Comparison and Transfer. Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society. (pp. 465-470). Portland, Oregon: Cognitive Science Society.
Prior research has found that while people are generally quite poor at recognizing when a new situation is structurally similar to a known case, comparison of two analogous cases greatly improves the likelihood of achieving such recognition. Our study examines the effects of varying the similarity between these compared cases, both featurally and structurally. We find that between-case similarity has a significant impact on transfer, and that these effects interact with characteristics of the learner.
Goldstone, R. L., Hills, T. T., & Day, S. B. (2010). Concept formation. In. I. B. Weiner & W. E. Craighead (Eds.) The Corsini Encyclopedia of Psychology. New York: John Wiley & Sons. (pp. 381-383).
A concept is a mentally possessed idea or notion that can be used to categorize information or objects. Over the course of each person’s lifetime, thousands of concepts are learned, for nouns like corkscrew, justice, and doorknob, adjectives like green, symmetric, and beautiful, and verbs like kick, climb, and eschew. While some philosophers have maintained that we do not genuinely learn new concepts through induction (Fodor, 1988), most psychologists believe that concepts can be learned, and that the representational capacity of the learner increases as they acquire new concepts. Most efforts have been spent developing accounts of how people acquire and represent concepts, including models based on: rules, prototypes, exemplars, boundaries, and theories.
Goldstone, R. L., & Hendrickson, A. T. (2010). Categorical Perception. Interdisciplinary Reviews: Cognitive Science, 1, 65-78.
Categorical perception (CP) is the phenomenon by which the categories possessed by an observer influences their perception. Experimentally, CP is revealed when an observer’s ability to make perceptual discriminations between things is better when those things belong to different categories rather than the same category, controlling for the physical difference between the things. We consider several core questions related to CP: Is it caused by innate and/or learned categories, how early in the information processing stream do categories influence perception, and what is the relation between ongoing linguistic processing and CP? CP for both speech and visual entities are surveyed, as are computational and mathematical models of CP. CP is an important phenomenon in cognitive science because it represents an essential adaptation of perception to support categorizations that an organism needs to make. Sensory signals that could be linearly related to physical qualities are warped in a non-linear manner, transforming analog inputs into quasi-digital, quasi-symbolic encodings.
Goldstone, R. L., Landy, D. H., & Son, J. Y. (2010). The education of perception. Topics in Cognitive Science, 2, 265-284.
While the field of perceptual learning has mostly been concerned with low- to middle-level changes to perceptual systems due to experience, we consider high-level perceptual changes that accompany learning in science and mathematics. In science, we explore the transfer of a scientific principle (competitive specialization) across superficially dissimilar pedagogical simulations. We argue that transfer occurs when students develop perceptual interpretations of an initial simulation and simply continue to use the same interpretational bias when interacting with a second simulation. In arithmetic and algebraic reasoning, we find that proficiency in mathematics involves executing spatially explicit transformations to notational elements. People learn to attend mathematical operations in the order in which they should be executed, and the extent to which students employ their perceptual attention in this manner is positively correlated with their mathematical experience. For both science and mathematics, relatively sophisticated performance is achieved not by ignoring perceptual features in favor of deep conceptual features, but rather by adapting perceptual processing so as to conform with and support formally sanctioned responses. These “Rigged Up Perceptual Systems” (RUPS) offer a promising approach to educational reform.
Gureckis, T. M. and Goldstone, R. L. (2010) Schema. In P. C. Hogan (Ed.) The Cambridge Encyclopedia of the Language Sciences. Cambridge, England: Cambridge University Press. (pp. 725-727).
A schema is a high-level conceptual structure or framework that organizes prior experience and helps us to interpret new situations. The key function of a schema is to provide a summary of our past experiences by abstracting out their important and stable components. For example, we might have a schema for a classroom that includes the fact that it typically contains a chalkboard, bookshelves, and chairs. Schemas provide a framework for rapidly processing information in our environment. For example, each time we enter a classroom, we do not have to consider each element in the room individually (e.g., chair, table, chalkboard). Instead, our schemas “fi ll in” what we naturally expect to be present, helping to reduce cognitive load. Similarly, schemas also allow us to predict or infer unknown information in completely new situations. If we read about a third grade classroom in a book, we can use our established classroom schema to predict aspects of its appearance, including the presence of a coatroom and the types of posters that might decorate the walls.
Hendrickson, A. T., Kachergis, G., Gureckis, T. M., & Goldstone, R. L. (2010). The effect of verbal interference and the internal structure of categories on perceptual discrimination.Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society. (pp. 1216-1221). Portland, Oregon: Cognitive Science Society.
Recent research has argued that categorization is strongly tied to language processing. For example, language (in the form of verbal category labels) has been shown to influence perceptual discriminations of color (Winawer et al., 2007). However, does this imply that categorical perception is essentially verbally mediated perception? The present study extends recent findings in our lab showing that categorical perception can occur even in the absence of overt labels. In particular, we evaluate the degree to which certain interference tasks (verbal, spatial) reduce the effect of learned categorical perception for complex visual stimuli (faces). Contrary to previous findings, our results show that a verbal interference task does not disrupt learned categorical perception effects for faces. Our results are interpreted in light of the ongoing debate about the role of language in categorization. In particular, we suggest that at least a sub-set of categorical perception effects may be effectively “language-free”.
Son, J. Y., Doumas, L. A., & Goldstone, R. L. (2010). When do words promote analogical transfer? The Journal of Problem Solving, 3, 52-92.
The purpose of this paper is to explore how and when verbal labels facilitate relational reasoning and transfer. We review the research and theory behind two ways words might direct attention to relational information: (1) words generically invite people to compare and thus highlight relations (the Generic Tokens [GT] hypothesis), and/or (2) words carry semantic cues to common structure (the Cues to Specific Meaning [CSM] hypothesis). Four experiments examined whether learning Signal Detection Theory (SDT) with relational words fostered better transfer than learning without relational words in easily alignable and less alignable situations (testing the GT hypothesis) as well as when the relational words matched and mismatched the semantics of the learning situation (testing the CSM hypothesis). The results of the experiments found support for the GT hypothesis because the presence of relational labels produced better transfer when two situations were alignable. Although the CSM hypothesis does not explain how words facilitate transfer, we found that mismatches between words and their labeled referents can produce a situation where words hinder relational learning.
Hendrickson, A T., & Goldstone, R. L. (2009). Perceptual unitization in part-whole judgmentsProceedings of the Thirty-First Annual Conference of the Cognitive Science Society, 1084-1089. Amsterdam, Netherlands: Cognitive Science Society.
Categorization relies upon the vocabulary of features that comprise the target objects. Previous theoretical work (Schyns, Goldstone, & Thibaut, 1998) has argued this vocabulary may change through learning and experience. Goldstone (2000) demonstrated this perceptual learning during a categorization task when new features are added that create a single feature unit from multiple existing units. We present two experiments that expand on that work using whole-part judgments (Palmer, 1978) to elicit the feature representation learned through categorization. The implications for different classes of computational models of categorization are discussed.
Son, J. Y., & Goldstone, R. L. (2009). Fostering General Transfer with Specific Simulations.Pragmatics and Cognition, 17, 1-42.
Science education faces the difficult task of helping students understand and appropriately generalize scientific principles across a variety of superficially dissimilar specific phenomena. Can cognitive technologies be adapted to benefit both learning specific domains and generalizable transfer? This issue is examined by teaching students complex adaptive systems with computer-based simulations. With a particular emphasis on fostering understanding that transfers to dissimilar phenomena, the studies reported here examine the influence of different descriptions and perceptual instantiations of the scientific principle of competitive specialization. Experiment 1 examines the role of intuitive descriptions to concrete ones, finding that intuitive descriptions leads to enhanced domain-specific learning but also deters transfer. Experiment 2 successfully alleviated these difficulties by combining intuitive descriptions with idealized graphical elements. Experiment 3 demonstrates that idealized graphics are more effective than concrete graphics even when unintuitive descriptions are applied to them. When graphics are concrete, learning and transfer largely depends on the particular description. However, when graphics are idealized, a wider variety of descriptions results in levels of learning and transfer similar to the best combination involving concrete graphics. Although computer-based simulations can be effective for learning that transfers, designing effective simulations requires an understanding of concreteness and idealization in both the graphical interface and its description.
Goldstone, R. L., Gerganov, A., Landy, D., & Roberts, M. E. (2008). Learning to see and conceive. In L. Tommasi, M. Peterson, & L. Nadel (Eds.) The New cognitive sciences (part of the Vienna Series in Theoretical Biology). Cambridge, MA.: MIT Press. (pp. 163-188).
Human concept learning depends upon perception. Our concept of Car is built out of perceptual features such as “engine,” “tire,” and “bumper.” However, recent research indicates that the dependency works both ways. We see bumpers and engines in part because we have acquired Car concepts and detected examples of them. Perception both influences and is influenced by the concepts that we learn. We have been exploring the psychological mechanisms by which concepts and perception mutually influence one another, and building computational models to show that the circle of influences is benign rather than vicious.
Gureckis, T. M., & Goldstone, R. L. (2008). The effect of internal structure of categories on perception. Proceedings of the Thirtieth Annual Conference of the Cognitive Science Society,(pp. 1876-1881). Washington, D.C.: Cognitive Science Society.
A novel study is presented that explores the effect that learning internally organized categories has on the ability to subsequently discriminate category members. The results demonstrate the classic categorical perception effect whereby discrimination of stimuli that belong to different categories is improved following training, while the ability to discriminate stimuli belonging to the same category is reduced. We further report a new within-category perceptual effect whereby category members that share the same category label but fall into different sub-clusters within that category are better discriminated than items that share the same category and cluster. The results show that learners are sensitive to multiple sources structure beyond simply the labels provided during supervised training. A computational model is presented to account for the results whereby multiple levels of encoding (i.e., at the item-, cluster-, and category- level) may simultaneously contribute to perception.
Ionescu, T., & Goldstone, R. L. (2007). Introduction to a special issue on the Development of Categorization, Cognition, Brain, and Behavior, 11, 629-633.
Categorization is indubitably an important cognitive process for humans (as well as other animals, Murai, Kosugi, Tomonaga, Tanaka, Matsuzawa, & Itakura, 2005), one that we constantly engage in to adapt to a very rich environment. We have a powerful impulse to interpret our world. This act of interpretation is fundamentally an act of categorization. We can go back in history at least to Aristotle (see his work on Categories, 350 B.C.E.) and along this way we find discussions of categories often appearing in philosophers’ books. The issue of categorization is also an historically early topic in psychology (see Hull’s experiment in 1920), and a considerable amount of research has been continuously dedicated to it up until the present. One could ask then: Why a special issue on categorization at this point in time? Although the general topic of categorization is venerable, relatively recently we cognitive scientists have changed our view about categorization. We have moved from considering taxonomies (or categories based in logic) as the “real,” mature kind of categorization to understanding that there are multiple kinds of similarities that are taken into account when one groups items (Barsalou, 1993, 2003; Medin, Goldstone, & Gentner, 1993; Ross & Murphy, 1999).
Quinn, P. C., Schyns, P. G., & Goldstone, R. L. (2006). The interplay between perceptual organization and categorization in the representation of complex visual patterns by young infants.Journal of Experimental Child Psychology, 95, 116-127.
The relation between perceptual organization and categorization processes in 3- and 4-month-olds was explored. The question was whether an invariant part abstracted during category learning could interfere with Gestalt organizational processes. A 2003 study by Quinn and Schyns had reported that an initial category familiarization experience in which infants were presented with visual patterns consisting of a pacman shape and a complex polygon could interfere with infants’ subsequent good continuationbased parsing of a circle from visual patterns consisting of a circle and a complex polygon. However, an alternative noninterference explanation for the results was possible because the pacman had been presented with greater frequency and duration than had the circle. The current study repeated Quinn and Schyns’s procedure but provided an equivalent number of familiarization trials and duration of study time for the infants to process the pacman during initial familiarization and the circle during subsequent familiarization. The results replicated the previous Wndings of Quinn and Schyns. The data are consistent with the interference account and suggest that a cognitive system of adaptable feature creation can take precedence over organizational principles with which a perceptual system comes preequipped.
Landy, D., & Goldstone, R. L. (2005). How we learn about things we don’t already understand. Journal of Experimental and Theoretical Artificial Intelligence, 17, 343-369.
The computation-as-cognition metaphor requires that all cognitive objects are constructed from a fixed set of basic primitives; prominent models of cognition and perception try to provide that fixed set. Despite this effort, however, there are no extant computational models that can actually generate complex concepts and processes from simple and generic basic sets, and there are good reasons to wonder whether such models may be forthcoming. We suggest that one can have the benefits of computationalism without a commitment to fixed feature sets, by postulating processes that slowly develop special-purpose feature languages, from which knowledge is constructed. This provides an alternative to the fixed-model conception without radical anti-representationlism. Substantial evidence suggests that such feature development adaptation actually occurs in the perceptual learning that accompanies category learning. Given the existence of robust methods for novel feature creation, the assumption of a fixed basis set of primitives as psychologically necessary is at best premature. Methods of primitive construction include (a) perceptual sensitization to physical stimuli, (b) unitization and differentiation of existing (non-psychological) stimulus elements into novel psychological primitives, guided by the current set of features, and (c) the intelligent selection of novel inputs, which in turn guides the automatic construction of new primitive concepts. Modeling the grounding of concepts as sensitivity to physical properties reframes the question of concept construction from the generation of an appropriate composition of sensations, to the tuning of detectors to appropriate circumstances.
Goldstone, R. L., Rogosky, B. J., Pevtzow, R., & Blair, M. (2005). Perceptual and semantic reorganization during category learning. In H. Cohen & C. Lefebvre (Eds.)Handbook of Categorization in Cognitive Science. (pp. 651-678). Amsterdam: Elsevier.
Category learning not only depends upon perceptual and semantic representations; it also leads to the generation of these representations. We describe two series of experiments that demonstrate how categorization experience alters, rather than simply uses, descriptions of objects. In the first series, participants first learned to categorize objects on the basis of particular sets of line segments. Subsequently, they were given a perceptual part-whole judgment task. Categorization training influenced participants’ partwhole judgments, indicating that whole objects were more likely to be broken down into parts that were relevant during categorization. In the second series, correlations were created or broken between semantic features of word concepts (e.g., ferocious vs. timid, and group-oriented vs. solitary animals). The best transfer was found between category learning tasks that shared the same semantic organization of concepts. Together, the experiments support models of category learning that simultaneously create the elements of categorized objects’ descriptions and associate those elements with categories.
Feng, Y., Goldstone, R. L., & Menkov, V. (2005). A Graph Matching Algorithm and its Application to Conceptual System Translation. International Journal on Artificial Intelligence Tools, 14, 77-100.
ABSURDIST II, an extension to ABSURDIST, is an algorithm using attributed graph matching to find translations between conceptual systems. It uses information about the internal structure of systems by itself, or in combination with external information about concept similarities across systems. It supports systems with multiple types of weighted or unweighted, directed or undirected relations between concepts. The algorithm exploits graph sparsity to improve computational efficiency.We present the results of experiments with a number of conceptual systems, including artificially constructed random graphs with introduced distortions.
Goldstone, R. L., Feng, Y., & Rogosky, B. (2005). Connecting concepts to the world and each other. In D. Pecher & R. Zwaan (Eds.) Grounding cognition: The role of perception and action in memory, language, and thinking. Cambridge: Cambridge University Press. (pp. 292-314)
How can well tell that two people both have a concept of dog, gold, or car despite differences in their conceptual knowledge? Two kinds of information can be used to translate between the concepts in two persons’ minds: the internal relations between concepts within each person’s mind, and external grounding of the concepts. We present a neural network model called ABSURDIST (Aligning Between Systems Using Relations Derived Inside Systems Themselves) that integrates internal and external determinants of conceptual meaning to find translations across people or other systems. The model shows that appropriate translations can be found by considering only similarity relations among concepts within a person. However, simulations also indicate synergistic interactions between internal and external sources of information. ABSURDIST is then applied to analogical reasoning, dictionary translation, translating between web-based ontologies, subgraph matching, and object recognition. The performance of ABSURDIST suggests the utility of concepts that are simultaneously externally grounded and enmeshed within a conceptual system.
Rogosky, B. J., & Goldstone, R. L. (2005). Adaptation of perceptual and semantic features. In L. A. Carlson & E. van der Zee (Eds.), Functional features in language and space: Insights from perception, categorization and development. (pp. 257-273). Oxford, England: Oxford University Press.
This chapter examines the role of feature in theories of concepts, perception, and language. The authors define features as psychological representations of properties in the world that can be processed independently of other properties and that are relevant to a task, such as categorization. They discuss the classic view of features as entities that do not change over time. They argue for an alternative view in which features are created and adapted according to the immediate goals and context of tasks, and over longer time periods in terms of perceptual and conceptual learning and development. The authors also distinguish pairs of dimensions in terms of whether the dimensions can be processed separately (i.e. either dimension can be attended independently of the other) or integrally (i.e. the dimensions cannot be processed independently). They present a study of the classification of linguistic stimuli according to rules based on semantic features (e.g. ferocity and socialness of animals). The results indicate that changes in the integral processing of the dimensions can be induced by tasks that favor the separate processing of one dimenion. The findings support the authors’ claim that, like perceptual features, semantic features can be adapted during learning.
‘Believing Is Seeing’ article (June, 2004)
ABSURDIST II, an extension to ABSURDIST, is an algorithm using attributed graph matching to find translations between conceptual systems. It uses information about the internal structure of systems by itself, or in combination with external information about concept similarities across systems. It supports systems with multiple types of weighted or unweighted, directed or undirected relations between concepts. The algorithm exploits graph sparsity to improve computational efficiency. We present the results of experiments with a number of conceptual systems, including artificially constructed random graphs with introduced distortions.
The external world must be filtered through our perceptual systems before it can have an impact upon us. That is, the world we experience is formed by our perceptual processing. However, it is not viciously circular to argue that our perceptual systems are reciprocally formed by our experiences. In fact, it is because our experiences are necessarily based on our perceptual systems that these perceptual systems must be shaped so that our experiences are appropriate and useful for dealing with our world.
In what follows, I will argue that the “building blocks” an observer uses for construing their world depends on the observer’s history, training, and acculturation. These factors, together with psychophysical constraints, mold one’s set of building blocks. Researchers who have proposed fixed sets of hard-wired primitives are exactly right in one sense — the combinatorics of objects, words, scenes, and scenarios strongly favor componential representations. However, this does not necessitate that the components be hard-wired. By developing new components to subserve particular tasks and environments, a newly important discrimination can generate building blocks that are tailored for the discrimination. Adaptive building blocks are likely to be efficient because they can be optimized for idiosyncratic needs and environments.
Goldstone, R. L., Steyvers, M., & Rogosky, B. J. (2003). Conceptual interrelatedness and caricatures. Memory & Cognition, 31, 169-180.
Concepts are interrelated to the extent that the characterization each concept is influenced by the other concepts, and isolated to the extent that the characterization of one concept is independent of other concepts. The relative categorization accuracy of the prototype and caricature of a concept can be used as a measure of concept interrelatedness. The prototype is the central tendency of a concept, whereas a caricature deviates from the concept’s central tendency in the direction opposite to the central tendency of other acquired concepts. The prototype is predicted to be relatively well categorized when a concept is relatively independent of other concepts, but the caricature is predicted to be relatively well categorized when a concept is highly related to other concepts. Support for these predictions comes from manipulations of the labels given to simultaneously acquired concepts (Experiment 1) and the order of categories during learning (Experiment 2).
Goldstone, R. L., & Johansen, M. K. (2003). Conceptual development from origins to asymptotes. In D. Rakison & L. Oakes (Eds.) Categories and concepts in early development. (pp. 403-418). Oxford, England: Oxford University Press.
Scientists studying adult concept learning are typically careful to analyze the entire pattern of responses given across all of the trials of an experiment. Often times, the early trials are the most diagnostic because categorization accuracy quickly reaches an asymptote. We take some pride in tackling the hard problem of accounting for adaptive processes that account for category learning, unlike many psychophysicists, who simply throw out the first 1000 trials because steady-state performance has not yet been reached. However, lest we grow too smug, the chapters of this book provide a great service by reminding us that even though we analyze the very first trial of our experiment, we are still studying conceptual change that occurs almost imperceptibly close to the asymptote. By the time that our 20-year-old subjects come to our laboratories, they have learned the majority of the concepts that they will ever learn and virtually all of their truly foundational concepts. Relatively brief laboratory training suffices to teach students the rule “Circle Above Square” (Bruner, Goodnow, & Austin, 1956), a particular configuration of 9 dots (Posner & Keele, 1968), or a new fact such as that grebes are birds, but this rapid learning is only possible because it builds upon a longer and more profound process by which concepts such as Above (Quinn, this volume), Bird (Mervis, Pani & Pani, this volume), Animal (Mareschal, this volume; Mandler, this volume), and Animacy (Gelman & Koenig, this volume; Rakison, this volume) are learned.
Those of us who want to develop theories of the learning and representation of adult concepts cannot afford to remain blind to the conceptual development that makes possible adult concept use. This life-long learning provides us with the fundamental representations that we subsequently combine and tweak. In assessing the contribution of developmental research on concepts and categories to our general understanding of human concepts, we will ask four questions: what are concepts; what is the relation between perception and concepts; what are the constraints on concept learning; and what are promising future directions for research on concepts?
Goldstone, R. L., & Kersten, A. (2003). Concepts and Categories. In A. F. Healy & R. W. Proctor (Eds.) Comprehensive handbook of psychology, Volume 4: Experimental psychology. (pp. 591-621). New York: Wiley.
Issues related to concepts and categorization are nearly ubiquitous in psychology because of peoples natural tendency to perceive a thing AS something. Zen meditation practices may or may not succeed in allowing a person to grasp the object itself rather than the labels and associations it evokes. In either case, the difficulty of this pursuit affirms the powerful impulse that we have to interpret our world. This act of interpretation, an act of seeing something as X rather than simply seeing it (Wittgenstein, 1953), is fundamentally an act of categorization.
The attraction of research on concepts is that an extremely wide variety of cognitive acts can be understood as categorizations. Identifying the person sitting across from you at the breakfast table involves categorizing something as your spouse. Diagnosing the cause of someones illness involves a disease categorization. Interpreting a painting as a Picasso, an artifact as Mayan, a geometry as Non-Euclidean, a fugue as baroque, a conversationalist as charming, a wine as a Bordeaux, and a government as socialist are categorizations at various levels of abstraction. The typically unspoken assumption of research on concepts is that these cognitive acts have something in common. That is, there are principles that explain many or all acts of categorization. This assumption is controversial (see Medin, Lynch, & Solomon, 2000), but is perhaps justified by its potential pay-off. If there are common principles governing concepts in their diverse manifestations, then discovering these principles would have a tremendous benefit, for we would not only acquire an understanding of how people identify faces, recognize letters, treat diseases, or form categories in a specialized domain. We would also have a unified understanding of all of these phenomena as examples of a generic process of concept formation.
Goldstone, R. L., & Rogosky, B. J. (2002). Using relations within conceptual systems to translate across conceptual systems, Cognition, 84, 295-320.
We explore one aspect of meaning, the identification of matching concepts across systems (e.g. people, theories, or cultures). We present a computational algorithm called ABSURDIST (Aligning Between Systems Using Relations Derived Inside Systems for Translation) that uses only within-system similarity relations to find between-system translations. While illustrating the sufficiency of within-system relations to account for translating between systems, simulations of ABSURDIST also indicate synergistic interactions between intrinsic, within-system information and extrinsic information.
Here is a brief description and commentary on ABSURDIST:
Dietrich, E. (2003). An ABSURDIST model vindicates a venerable theory. Trends in Cognitive Science, 7, 57-59.
Goldstone, R. L., & Rogosky, B. J. (2002). The role of roles in translating across conceptual systems, Proceedings of the Twenty-fourth Annual Conference of the Cognitive Science Society. Hillsdale, New Jersey: Lawrence Erlbaum Associates. (pp. 369-374).
According to an “external grounding” theory of meaning, a concept’s meaning depends on its connection to the external world. By a “conceptual web” account, a concept’s meaning depends on its relations to other concepts within the same system. We explore one aspect of meaning, the identification of matching concepts across systems (e.g. people, theories, or cultures). We present a computational algorithm called ABSURDIST (Aligning Between Systems Using Relations Derived Inside Systems for Translation) that uses only within-system similarity relations to find between-system translations. While illustrating the sufficiency of a conceptual web account for translating between systems, simulations of ABSURDIST also indicate powerful synergistic interactions between intrinsic, within-system information and extrinsic information. Applications of the algorithm to issues in object recognition, shape analysis, automatic translation, human analogy and comparison making, pattern matching, neural network interpretation, and statistical analysis are described.
Goldstone, R. L, Lippa, Y., & Shiffrin, R. M. (2001). Altering object representations through category learning. Cognition, 78, 27-43.
Previous research has shown that objects that are grouped together in the same category become more similar to each other and that objects that are grouped in different categories become increasingly dissimilar, as measured by similarity ratings and psychophysical discriminations. These findings are consistent with two theories of the influence of concept learning on similarity. By a strategic judgment bias account, the categories associated with objects are explicitly used as cues for determining similarity, and objects that are categorized together are judged to be more similar because similarity is not only a function of the objects themselves, but also the objectsí category labels. By a representational change account, category learning alters the description of the objects themselves, emphasizing properties that are relevant for categorization. A new method for distinguishing between these accounts is introduced which measures the difference between the similarity ratings of categorized objects to a neutral object. The results indicate both strategic biases based on category labels and genuine representational change, with the strategic bias affecting mostly objects belonging to different categories and the representational change affecting mostly objects belonging to the same category.
Goldstone, R. L, & Steyvers, M. (2001). The Sensitization and Differentiation of Dimensions During Category Learning. Journal of Experimental Psychology: General, 130,116-139.
The reported experiments explore two mechanisms by which object descriptions are flexibly adapted to support concept learning: selective attention and dimension differentiation. Arbitrary dimensions were created by blending photographs of faces in different proportions, and mixing these blends together. Consistent with learned selective attention, positive transfer was found when initial and final categorizations shared either relevant or irrelevant dimensions, and negative transfer was found when previously relevant dimensions became irrelevant. Unexpectedly good transfer was observed when both irrelevant dimensions became relevant and relevant dimensions became irrelevant, and was explained in terms of participants learning to isolate one dimension from another. This account was further supported by experiments indicating that conditions expected to produce positive transfer via dimension differentiation produced better transfer than conditions expected to produce positive transfer via selective attention, but only when stimuli were composed of highly integral and overlapping dimensions. We discuss the relation between dimension differentiation and selective attention, mechanisms that may underlie these processes, and implications for category learning research.
Lippa, Y., & Goldstone, R. L. (2001). The Acquisition of Automatic Response Biases through Stimulus-Response Mapping and Categorization Determined by a Compatibility Task. Memory & Cognition, 29, 1051-1060
Experiments explored whether spatially neutral stimuli acquire the ability to automatically elicit spatial responses. In Experiment 1, participants associated line-drawings with either left or right key presses. Subsequently, the pictures were used in a Simon task wherein participants made left and right key presses based on the color of the picture, ignoring its shape. Participants responded more quickly when the key press previously associated with the picture matched, rather than mismatched, the response required by the picture’s color. In Experiment 2, participants learned response categories that grouped spatially ambiguous line-drawings together with pictures of left- and right-pointing arrows and fingers. A subsequent Simon task again yielded compatibility effects, indicating that the spatially ambiguous pictures inherited the response biases of the other objects in their category. Thus, responses directly associated with shapes, and indirectly associated with shapes by category membership, are both automatically triggered even when the responses are irrelevant and inappropriate.
Goldstone, R. L. (2000). Unitization during Category Learning. Journal of Experimental Psychology: Human Perception and Performance, 26, 86-112
Five experiments explored the question of whether new perceptual units can be developed if they are diagnostic for a category learning task, and if so, what are the constraints on this unitization process? During category learning, participants were required to attend either a single component or a conjunction of five components in order to correctly categorize an object. In Experiments 1-4, some evidence for unitization was found in that the conjunctive task becomes much easier with practice, and this improvement was not found for the single component task, or for conjunctive tasks where the components cannot be unitized. Influences of component order (Experiment 1), component contiguity (Experiment 2), component proximity (Experiment 3), and number of components (Experiment 4) on practice effects were found. Using a Fourier Transformation method for deconvolving response times (Experiment 5), prolonged practice effects yielded responses that were faster than expected by analytic model that integrate evidence from independently perceived components.
Goldstone, R. L., Steyvers, M., Spencer-Smith, J., & Kersten, A. (2000). Interactions between perceptual and conceptual learning. in E. Diettrich & A. B. Markman (eds.) Cognitive Dynamics: Conceptual Change in Humans and Machines. Mahwah, New Jersey: Lawrence Erlbaum Associates. (pp. 191-228).
Confusions arise when ‘stable’ is equated with ‘foundational.’ Spurred on by the image of a house`s foundation, it is tempting to think that something provides effective support to the extent that it is rigid and stable. We will argue that when considering the role of perception in grounding our concepts, exactly the opposite is true. Our perceptual system supports our ability to acquire new concepts by being flexibly tuned to these concepts. Whereas the concepts that we learn are certainly influenced by our perceptual representations, we will argue that these perceptual representations are also influenced by the learned concepts. In keeping with one of the central themes of this book, behavioral adaptability is completely consistent with representationalism. In fact, the most straightforward account of our experimental results is that concept learning can produce changes in perceptual representations, the ‘vocabulary’ of perceptual features, that are used by subsequent tasks.
This chapter reviews theoretical and empirical evidence that perceptual vocabularies used to describe visual objects are flexibly adapted to the demands of their user. We will extend arguments made elsewhere for adaptive perceptual representations (Goldstone, Schyns, & Medin, in press; Schyns, Goldstone, & Thibaut, in press), and discuss research from our laboratory illustrating specific interactions between perceptual and conceptual learning. We will describe computer simulations that provide accounts of these interactions using neural network models. These models have detectors that become increasingly tuned to the set of perceptual features that support concept learning. The bulk of the chapter will be organized around mechanisms of human perceptual learning, and computer simulations of these mechanisms.
(reprinted as: Goldstone, R. L., & Barsalou, L. (1998). Reuniting perception and conception. In S. A. Sloman and L. J. Rips (Eds.) Similarity and symbols in human thinking. (pp. 145-176). Cambridge, MA: MIT Press)
Work in philosophy and psychology has argued for a dissociation between perceptually-based similarity and higher-level rules in conceptual thought. Although such a dissociation may be justified at times, our goal is to illustrate ways in which conceptual processing is grounded in perception, both for perceptual similarity and abstract rules. We discuss the advantages, power, and influences of perceptually-based representations. First, many of the properties associated with amodal symbol systems (e.g. productivity and generativity) can be achieved with perceptually-based systems as well. Second, relatively raw perceptual representations are powerful because they can implicitly represent properties in an analog fashion. Third, perception naturally provides impressions of overall similarity, exactly the type of similarity useful for establishing many common categories. Fourth, perceptual similarity is not static but becomes tuned over time to conceptual demands. Fifth, the original motivation or basis for sophisticated cognition is often less sophisticated perceptual similarity. Sixth, perceptual simulation occurs even in conceptual tasks that have no explicit perceptual demands. Parallels between perceptual and conceptual processes suggest that many mechanisms typically associated with abstract thought are also present in perception, and that perceptual processes provide useful mechanisms that may be coopted by abstract thought.
This research provides evidence for two competing attentional mechanisms. Attentional persistence directs attention to attributes previously found to be predictive, whereas contrast directs attention to stimuli that have not already been associated with a category. Three experiments provide evidence for these mechanisms. Experiments 1 and 2 revealed increased attention to an attribute following training in which that attribute was relevant, providing evidence for persistence. These experiments also revealed increased attention to an attribute following training in which another, more salient attribute was relevant, providing evidence for contrast. Experiment 3 used a subtractive method to determine the contributions of persistence and contrast to changes in attention to an attribute. The results suggest that persistence operates primarily at the level of dimensions, whereas contrast operates at the level of dimension values.
According to an influential approach to cognition, our perceptual systems provide us with a repertoire of fixed features as input to higher-level cognitive processes. We present a theory of category learning and representation in which features, instead of being components of a fixed repertoire, are created under the influence of higher-level cognitive processes. When new categories need to be learned, fixed features face one of two problems: (1) High-level features that are directly useful for categorization may not be flexible enough to represent all relevant objects. (2) Low-level features consisting of unstructured fragments (such as pixels) may not capture the regularities required for successful categorization. We report evidence that feature creation occurs in category learning and we describe the conditions that promote it. Feature creation can adapt flexibly to changing environmental demands and may be the origin of fixed feature repertoires. Implications for object categorization, conceptual development, chunking, constructive induction and formal models of dimensionality reduction are discussed.
Schyns, P. G., Goldstone, R. L., & Thibaut, J. (1998). Ways of featuring in object categorization. Behavioral and Brain Sciences, 21, 41-49. (response to commentaries)
A continuum between purely isolated and purely interrelated concepts is described. A concept is interrelated to the extent that it is influenced by other concepts. Methods for manipulating and identiying a concept`s degree of interrelatedness are introduced. Relatively isolated concepts are empirically identified by a relatively large use of nondiagnostic features, and by better categorization performance for a concept`s prototype than for a caricature of the concept. Relatively interrelated concepts are identified by minimal use of nondiagnostic features, and by better categorization performance for a caricature than a prototype. A concept is likely to be relatively isolated when: subjects are instructed to create images for their concepts rather than find discriminating features, concepts are given unrelated labels, and the categories that are displayed alternate rarely between trials. The entire set of manipulations and measurements supports a graded distinction between isolated and interrelated concepts. The distinction is applied to current models of category learning, and a connectionist framework for interpreting the empirical results is presented.
Goldstone, R. L., Steyvers, M., Larimer, K. (1996). Categorical perception of novel dimensions. Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society. (pp 243-248). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
Categorical perception is a phenomenon in which people are better able to distinguish between stimuli along a physical continuum when the stimuli come from different categories than when they come from the same category. In a laboratory experiment with human subjects, we find evidence for categorical perception along a novel dimension that is created by interpolating (i.e. morphing) between two randomly selected bezier curves. A neural network qualitatively models the empirical results with the following assumptions: 1) hidden ÒdetectorÓ unit become specialized for particular stimulus regions with a topologically structured competitive learning algorithm, 2) simultaneously, associations between detectors and category units are learned, and 3) feedback from the category units to the detectors causes the detectors to become concentrated near category boundaries. The particular feedback used, implemented in an “S.O.S. network,” operates by increasing the learning rate to detectors that are neighbors to a detector that produces an improper categorization.
Subjects were shown simple objects and were asked to reproduce the colors of the objects. Even though the objects remained on the screen while the subjects reproduced the colors and the objects` shapes were irrelevant to the subjects` task, subjects` color perceptions were influenced by the shape category of an object. For example, objects that belonged to categories with redder objects were judged to be more red than identically colored objects belonging to another category. Further experiments showed thatX the object categories that subjects use, rather than being fixed, depend on the objects to which subjects are exposed.
Goldstone, R. L. (1995). Many categories, few structures. Contemporary Psychology, 40, 147-149.
Four experiments investigated the influence of categorization training on perceptual discriminations. Ss were trained according to 1 of 4 different categorization regimes. Subsequent to category learning, Ss performed a Same-Different judgement task. Ss` sensitivities (d`s) for discriminating between items that varied on a category(ir)relevant dimensions were measured. Evidence for acquired distinctiveness (increased perceptual sensitivity for items that are categorized differently) was obtained. One case of acquired equivalence (decreased perceptual sensitivity for items that are categorized together) was found for separable, but not integral, dimensions. Acquired equivalence within a categorization-relevant dimension was never found for either integral or separable dimensions. The relevance of the results for theories of perceptual learning, dimensional attention, categorical perception, and categorization are discussed.
Goldstone, R. L. (1994). Categorization. Science, 265, 552. [review of Estes` Classification and Cognition]
Goldstone, R. L., & Kruschke, J. K. (1994). Are rules and instances subserved by separate systems? [A commentary on Shanks and St. John]. Behavioral and Brain Sciences, 17, 405.
Pevtzow, R., & Goldstone, R. L. (1994). Categorization and the parsing of objects. Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society. (pp. 717-722). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
Several models of categorization suggest that fixed inputs (features) are combined together to create categorization rules. It is also possible that categorization influences what features are perceived and used. This experiment explored the possibility that categorization training influences how an object is decomposed into parts. In the first part of this experiment, subjects learned to categorize objects based on particular sets of line segments. Following categorization training, subjects were tested in a whole-part decomposition task, making speeded judgements of “does whole X contain probe Y.” All diagnostic and nondiagnostic category parts were used as parts within the whole objects, and as probes. Categorization training in the first part of the experiment affected performance on the second task. In particular, subjects were faster to respond when the whole object contained a part that was diagnostic for categorization than when it contained a nondiagnostic part. When the probe was a diagnostic category part subjects were faster to respond that it was present than absent, and when the probe was a nondiagnostic part, subjects were faster to respond that it was absent than that it was present. These results are discussed in terms of perceptual sensitivity, response bias, and the modulating influence of experience.
Goldstone, R. L. (1993). Evidence for interrelated and isolated concepts from prototype and caricature classifications. Proceedings of the Fifteenth Annual Conference of the Cognitive Science Society. (pp. 498-503). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
Previous research (Goldstone, 1991) has suggested that concepts differ in their degree of dependency on other concepts. While some concepts` characterizations depend on other simultaneously acquired concepts, other concepts are relatively isolated. The current experiments provide a new measure of a concept`s interrelatedness/isolation. It is assumed that if the prototype of a concept is classified with greater accuracy than a caricature, then the concept is relatively independent of the influences of other concepts. If a caricature is more easily categorized than the prototype, then the concept is relatively dependent on other concepts. If these assumptions are made, then the current experiments provide converging support for a interrelated/isolated distinction. Instructing subjects to form images of the concepts to be acquired, or infrequently alternating categories during presentation, yields relatively isolated concepts. Instructing subjects to try to discriminate between concepts, or frequently alternative categories, yields relatively interrelated concepts.
Aha, D. W., and Goldstone, R. L. (1992). Concept learning and flexible weighting. Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society. (pp. 534-539). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
We previously introduced an exemplar model, named GCM-ISW, that exploits a highly flexible weighting scheme. Or simulations showed that it records faster learning rates and higher asymptotic accuracies on several artificial categorization tasks than models with more limited abilities to warp input spaces. This paper extends our previous work; it describes experimental results that suggest human subjects also invoke such highly flexible schemes. In particular, our model provides significantly better fits than models with less flexibility, and we hypothesize that humans selectively weight attributes depending on an item`s location in the input space.
Goldstone, R. L. (1991). Feature diagnosticity as a tool for investigating positively and negatively defined concepts. Proceedings of the Thirteenth Annual Conference of the Cognitive Science Society. (pp. 263-268). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
Two methods of representing concepts are distinguished and empirically investigated. Negatively defined concepts are defined in terms of other concepts at the same level of abstraction. Positively defined concepts do not make recourse to other concepts at the same level of abstraction for their definition. In two experiments, subjects are biased to represent concepts underlying visual patterns in a positive manner by instructing subjects to form an image of the learned concepts and by initially training subjects on minimally distorted concept instances. Positively defined concepts are characterized by a large use of non-diagnostic features in concept representations, relative to negatively defined concepts. The distinction between positively and negatively defined concepts can account for the dual nature of natural concepts – as directly accessed during the recognition of items, and is intricately interconnected to other concepts.
Medin, D. L., Goldstone, R. L. (1991). Concepts. In B. Blackwell (Ed.) Dictionary of Cognitive Psychology (pp 77-83). Oxford: Oxford University Press.
Aha, D. W., and Goldstone, R. L. (1990). Learning attribute relevance in context in instance-based learning algorithms. Proceedings of the Twelfth Annual Conference of the Cognitive Science Society. (pp. 141-148). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
There has been an upsurge of interest, in both artificial intelligence and cognitive psychology, in exemplar-based process models of categorization, which preserve specific instances instead of maintaining abstractions derived from them. Recent exemplar-based models provided accurate fits for subject results in a variety of experiments because, in accordance with Shepard`s (1987) observations, they define similarity to degrade exponentially with the distance between instances in psychological space. Although several researchers have shown that an attribute`s relevance in similarity calculations varies according to its context (i.e., the values of the other attributes in the instance and the target concept,” previous exemplar models define attribute relevance to be invariant across all instances. This paper introduces the GCM-ISW model, an extension of Nosofsky`s GCM model that uses context-specific attribute weights for categorization tasks. Since several researchers have reported that humans make context-sensitive classification decision, our model will fit subject data more accurately when attribute relevance is context-sensitive. We also introduce a process component for GCM-ISW and show that its learning rate is significantly faster than the rates of both previous exemplar-based process models when attribute relevance varies among instances. GCM-ISM is both computationally more efficient and more psychologically plausible than previous exemplar-based models.
Medin, D. L., Ahn, W-K, Bettger J., Florian, F., Goldstone, R., Lassaline, M., Markman, A., Rubinstein, J., Wisniewski, E. (1990). Safe Takeoffs-Soft Landings. Cognitive Science, 14, 169-178.
Matheus, C. J., Rendall, L. R., Medin, D. L., & Goldstone, R. L. (1989). Purpose and conceptual functions: A framework for concept representation and learning in humans and machines. The Seventh Conference of the Society for the Study of Artificial Intelligence and Simulation of Behavior. Sussex, England