Noncognitive factors in high-road/low-road learning: I. Modes of abstraction in adulthood

Since the termscognition andcognitive are broadly used but not clearly defined, it may be helpful to clarify what is meant bynoncognitive factors. In cognitive science, the termscognition andcognitive generally describe mental processes that are informational insofar as they carry information about the organism's own body and the material world. Thus defined, there are three sorts of noncognitive organismic factors important in adult learning:affective processes, self-developmental processes, andhardware factors (i.e., noninformational, purely organismic constraints such as mental capacity/working memory limitations, gestaltist field factors, etc.). In this series of papers, we attempt to show how these noncognitive factors interact with cognitive factors to facilitate adult learning. We outline and give reference to a dialectical constructivist (neoPiagetian) model of the psychological organism that integrates noncognitive with cognitive factors and that can serve to explicate the findings of the literature and to process/task analyze adult learning. An important aim is the integration of the findings of decline and regression from the cognitive literature with the findings regarding the increase in self-directedness reported by adult education theorists. This is explicated through a process-analytic account of the will, particularly as it pertains to noncognitive factors. In Part II, we continue our explication of a dialectical model of the ego and conclude with a discussion of modes of learning/instruction in adulthood.     

In search of abstraction: The varying abstraction model of categorization

A longstanding debate in the categorization literature concerns representational abstraction. Generally, when exemplar models, which assume no abstraction, have been contrasted with prototype models, which assume total abstraction, the former models have been found to be superior to the latter. Although these findings may rule out the idea that total abstraction takes place during category learning and instead suggest that no abstraction is involved, the idea of abstraction retains considerable intuitive appeal. In this article, we propose the varying abstraction model of categorization (VAM), which investigates the possibility that partial abstraction may play a role in category learning. We apply the VAM to four previously published data sets that have been used to argue that no abstraction is involved. Contrary to the previous findings, our results provide support for the idea that some form of partial abstraction can be used in people's category representations.     

Granularity and the acquisition of grammatical gender: how order-of-acquisition affects what gets learned

Why do adult language learners typically fail to acquire second languages with native proficiency? Does prior linguistic experience influence the size of the “units” adults attend to in learning, and if so, how does this influence what gets learned? Here, we examine these questions in relation to grammatical gender, which adult learners almost invariably struggle to master. We present a model of learning that predicts that exposure to smaller units (such as nouns) before exposure to larger linguistic units (such as sentences) can critically impair learning about predictive relations between units: such as that between a noun and its article. This prediction is then confirmed by a study of adult participants learning grammatical gender in an artificial language. Adults learned both nouns and their articles better when they were first heard nouns used in context with their articles prior to hearing the nouns individually, compared with learners who first heard the nouns in isolation, prior to hearing them used in context. In the light of these results, we discuss the role gender appears to play in language, the importance of meaning in artificial grammar learning, and the implications of this work for the structure of L2-training.     

The role of the basal ganglia in learning and memory: insight from Parkinson's disease

It has long been known that memory is not a single process. Rather, there are different kinds of memory that are supported by distinct neural systems. This idea stemmed from early findings of dissociable patterns of memory impairments in patients with selective damage to different brain regions. These studies highlighted the role of the basal ganglia in non-declarative memory, such as procedural or habit learning, contrasting it with the known role of the medial temporal lobes in declarative memory. In recent years, major advances across multiple areas of neuroscience have revealed an important role for the basal ganglia in motivation and decision making. These findings have led to new discoveries about the role of the basal ganglia in learning and highlighted the essential role of dopamine in specific forms of learning. Here we review these recent advances with an emphasis on novel discoveries from studies of learning in patients with Parkinson's disease. We discuss how these findings promote the development of current theories away from accounts that emphasize the verbalizability of the contents of memory and towards a focus on the specific computations carried out by distinct brain regions. Finally, we discuss new challenges that arise in the face of accumulating evidence for dynamic and interconnected memory systems that jointly contribute to learning.     

Order Matters! Influences of Linear Order on Linguistic Category Learning

Linguistic category learning has been shown to be highly sensitive to linear order, and depending on the task, differentially sensitive to the information provided by preceding category markers (premarkers, e.g., gendered articles) or succeeding category markers (postmarkers, e.g., gendered suffixes). Given that numerous systems for marking grammatical categories exist in natural languages, it follows that a better understanding of these findings can shed light on the factors underlying this diversity. In two discriminative learning simulations and an artificial language learning experiment, we identify two factors that modulate linear order effects in linguistic category learning: category structure and the level of abstraction in a category hierarchy. Regarding category structure, we find that postmarking brings an advantage for learning category diagnostic stimulus dimensions, an effect not present when categories are non-confusable. Regarding levels of abstraction, we find that premarking of super-ordinate categories (e.g., noun class) facilitates learning of subordinate categories (e.g., nouns). We present detailed simulations using a plausible candidate mechanism for the observed effects, along with a comprehensive analysis of linear order effects within an expectation-based account of learning. Our findings indicate that linguistic category learning is differentially guided by pre- and postmarking, and that the influence of each is modulated by the specific characteristics of a given category system.     

A Theory of Blame

We introduce a theory of blame in five parts. Part 1 addresses what blame is: a unique moral judgment that is both cognitive and social, regulates social behavior, fundamentally relies on social cognition, and requires warrant. Using these properties, we distinguish blame from such phenomena as anger, event evaluation, and wrongness judgments. Part 2 offers the heart of the theory: the Path Model of Blame, which identifies the conceptual structure in which blame judgments are embedded and the information processing that generates such judgments. After reviewing evidence for the Path Model, we contrast it with alternative models of blame and moral judgment (Part 3) and use it to account for a number of challenging findings in the literature (Part 4). Part 5 moves from blame as a cognitive judgment to blame as a social act. We situate social blame in the larger family of moral criticism, highlight its communicative nature, and discuss the darker sides of moral criticism. Finally, we show how the Path Model of Blame can bring order to numerous tools of blame management, including denial, justification, and excuse.     

The timing and mechanisms of children's use of morphological information in spelling: A review of evidence from English and French

We present a review of the research on English and French children's learning of the place of morphemes in spelling. Traditional models suggest that children use morphology relatively late in their spelling careers and that the end-point of development lies in rule-based performance. In contrast, we show that (a) children are sensitive to the role of morphemes in determining spelling at a young age and (b) they do not rely (at least exclusively) on rules. We discuss the features that may account for discrepancies between studies demonstrating late versus early use of morphology and we examine the processes that children might rely on in their learning, specifically statistical learning of intra- and inter-word regularities and retrieval of item-specific representations. This proposal provides a potential explanation for how children learn about the representation of morphology in print.     

On the generality and limits of abstraction in rats and humans

In this review, we address the question, central to cognition, of whether nonhuman animals such as rats are capable of extracting and extending information from a given learning situation to a new learning situation without generalizing through a physical dimension of the stimuli. This capacity underlies abstraction, which is a hallmark of human cognition and necessary for complex information processing such as language acquisition. We selectively review recent experiments with rats in which systematic changes in information processing of new stimuli are observed after training with different stimuli. These results strongly suggest that this capacity is present in rats. We also review two articles in which clear limitations to this capacity are detected. We conclude that, within specified limits, rats are capable of using prior experience when faced with a learning situation that involves new stimuli. We interpret this ability as a rudimentary form of abstraction. In the face of these provocative results, new theories of learning should be designed to account for these findings.     

Humor, abstraction, and disbelief

We investigated humor as a context for learning about abstraction and disbelief. More specifically, we investigated how parents support humor understanding during book sharing with their toddlers. In Study 1, a corpus analysis revealed that in books aimed at 1-to 2-year-olds, humor is found more often than other forms of doing the wrong thing including mistakes, pretense, lying, false beliefs, and metaphors. In Study 2, 20 parents read a book containing humorous and non-humorous pages to their 19-to 26-month-olds. Parents used a significantly higher percentage of high abstraction extra-textual utterances (ETUs) when reading the humorous pages. In Study 3, 41 parents read either a humorous or non-humorous book to their 18-to 24-month-olds. Parents reading the humorous book made significantly more ETUs coded for a specific form of high abstraction: those encouraging disbelief of prior utterances. Sharing humorous books thus increases toddlers' exposure to high abstraction and belief-based language.     

Frames of reference in spatial language acquisition

Languages differ in how they encode spatial frames of reference. It is unknown how children acquire the particular frame-of-reference terms in their language (e.g., left/right, north/south). The present paper uses a word-learning paradigm to investigate 4-year-old English-speaking children’s acquisition of such terms. In Part I, with five experiments, we contrasted children’s acquisition of novel word pairs meaning left-right and north-south to examine their initial hypotheses and the relative ease of learning the meanings of these terms. Children interpreted ambiguous spatial terms as having environment-based meanings akin to north and south, and they readily learned and generalized north-south meanings. These studies provide the first direct evidence that children invoke geocentric representations in spatial language acquisition. However, the studies leave unanswered how children ultimately acquire “left” and “right.” In Part II, with three more experiments, we investigated why children struggle to master body-based frame-of-reference words. Children successfully learned “left” and “right” when the novel words were systematically introduced on their own bodies and extended these words to novel (intrinsic and relative) uses; however, they had difficulty learning to talk about the left and right sides of a doll. This difficulty was paralleled in identifying the left and right sides of the doll in a non-linguistic memory task. In contrast, children had no difficulties learning to label the front and back sides of a doll. These studies begin to paint a detailed account of the acquisition of spatial terms in English, and provide insights into the origins of diverse spatial reference frames in the world’s languages.     

Incrementality and Prediction in Human Sentence Processing

We identify a number of principles with respect to prediction that, we argue, underpin adult language comprehension: (a) comprehension consists in realizing a mapping between the unfolding sentence and the event representation corresponding to the real-world event being described; (b) the realization of this mapping manifests as the ability to predict both how the language will unfold, and how the real-world event would unfold if it were being experienced directly; (c) concurrent linguistic and nonlinguistic inputs, and the prior internal states of the system, each drive the predictive process; (d) the representation of prior internal states across a representational substrate common to the linguistic and nonlinguistic domains enables the predictive process to operate over variable time frames and variable levels of representational abstraction. We review empirical data exemplifying the operation of these principles and discuss the relationship between prediction, event structure, thematic role assignment, and incrementality.     

We are what we eat: How food is represented in our mind/brain

Despite the essential role of food in our lives, we have little understanding of the way our knowledge about food is organized in the brain. At birth, human infants exhibit very few food preferences, and do not yet know much about what is edible and what is not. A multisensory learning development will eventually turn young infants into omnivore adults, for whom deciding what to eat becomes an effortful task. Recognizing food constitutes an essential step in this decisional process. In this paper we examine how concepts about food are represented in the human brain. More specifically, we first analyze how brain-damaged patients recognize natural and manufactured food, and then examine these patterns in the light of the sensory-functional hypothesis and the domain-specific hypothesis. Secondly, we discuss how concepts of food are represented depending on whether we embrace the embodied view or the disembodied view. We conclude that research on food recognition and on the organization of knowledge about food must also take into account some aspects specific to food category, the relevance of which has not been sufficiently recognized and investigated to date.     

A Computational Model for the Item‐Based Induction of Construction Networks

According to usage‐based approaches to language acquisition, linguistic knowledge is represented in the form of constructions—form‐meaning pairings—at multiple levels of abstraction and complexity. The emergence of syntactic knowledge is assumed to be a result of the gradual abstraction of lexically specific and item‐based linguistic knowledge. In this article, we explore how the gradual emergence of a network consisting of constructions at varying degrees of complexity can be modeled computationally. Linguistic knowledge is learned by observing natural language utterances in an ambiguous context. To determine meanings of constructions starting from ambiguous contexts, we rely on the principle of cross‐situational learning. While this mechanism has been implemented in several computational models, these models typically focus on learning mappings between words and referents. In contrast, in our model, we show how cross‐situational learning can be applied consistently to learn correspondences between form and meaning beyond such simple correspondences.     

Using relational reflexivity as a resource in teaching family therapy

In this paper we talk about creating coherence and transparency in the relationships between teacher, model of adult learning and subject taught. We describe how we have made connections between adult learning theory and family therapy to generate resources for action in teaching on the qualifying level course at Northumbria University. Using a recent teaching session and the voices of trainees, we illustrate these connections with an example of teaching about relational reflexivity, using methods which enabled us to generate reflexive ‘flow’ in the learning context.     

Bayesian theories of conditioning in a changing world

The recent flowering of Bayesian approaches invites the re-examination of classic issues in behavior, even in areas as venerable as Pavlovian conditioning. A statistical account can offer a new, principled interpretation of behavior, and previous experiments and theories can inform many unexplored aspects of the Bayesian enterprise. Here we consider one such issue: the finding that surprising events provoke animals to learn faster. We suggest that, in a statistical account of conditioning, surprise signals change and therefore uncertainty and the need for new learning. We discuss inference in a world that changes and show how experimental results involving surprise can be interpreted from this perspective, and also how, thus understood, these phenomena help constrain statistical theories of animal and human learning.     

A Bayesian Theory of Sequential Causal Learning and Abstract Transfer

Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause‐effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre‐training (or even post‐training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue‐outcome co‐occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge.     

Is speech perception modular or interactive?

Norris et al. recently reported experimental evidence that listeners learn phoneme categories in response to lexical feedback. To reconcile these findings with their modular account of speech perception, the authors argue that top-down feedback can be used to support phoneme learning, but not to influence on-line phonemic processing. We suggest that these findings have broader implications than the authors assume, and we discuss potential challenges for integrating a modular theory with top-down learning.     

The simplicity principle in human concept learning

How do we learn concepts and categories from examples? Part of the answer might be that we induce the simplest category consistent with a given set of example objects. This seemingly obvious idea, akin to simplicity principles in many fields, plays surprisingly little role in contemporary theories of concept learning, which are mostly based on the storage of exemplars, and avoid summarization or overt abstraction of any kind. This article reviews some evidence that complexity minimization does indeed play a central role in human concept learning. The chief finding is that subjects' ability to learn concepts depends heavily on the concepts' intrinsic complexity; more complex concepts are more difficult to learn. This pervasive effect suggests, contrary to exemplar theories, that concept learning critically involves the extraction of a simplified or abstracted generalization from examples.     

Visuomotor Adaptation and Proprioceptive Recalibration

ABSTRACT

Motor learning, in particular motor adaptation, is driven by information from multiple senses. For example, when arm control is faulty, vision, touch, and proprioception can all report on the arm's movements and help guide the adjustments necessary for correcting motor error. In recent years we have learned a lot about how the brain integrates information from multiple senses for the purpose of perception. However, less is known about how multisensory data guide motor learning. Most models of, and studies on, motor learning focus almost exclusively on the ensuing changes in motor performance without exploring the implications on sensory plasticity. Nor do they consider how discrepancies in sensory information (e.g., vision and proprioception) related to hand position may affect motor learning. Here, we discuss research from our lab and others that shows how motor learning paradigms affect proprioceptive estimates of hand position, and how even the mere discrepancy between visual and proprioceptive feedback can affect learning and plasticity. Our results suggest that sensorimotor learning mechanisms do not exclusively rely on motor plasticity and motor memory, and that sensory plasticity, in particular proprioceptive recalibration, plays a unique and important role in motor learning.