We present results from numerical studies of supervised learning operations in recurrent networks considered as graphs, leading from a given set of input conditions to predetermined outputs. Graphs that have optimized their output for particular inputs with respect to predetermined outputs are asymptotically stable and can be characterized by attractors which form a representation space for an associative multiplicative structure of input operations. As the mapping from a series of inputs onto a series of such attractors generally depends on (...) the sequence of inputs, this structure is generally noncommutative. Moreover, the size of the set of attractors, indicating the complexity of learning, is found to behave non-monotonically as learning proceeds. A tentative relation between this complexity and the notion of pragmatic information is indicated. (shrink)

Because corporate social responsibility (CSR) is potentially beneficial for companies, it is important to understand the factors that improve a company’s CSR practice. Scholars hypothesize that facilitating learning organization characteristics, which are divided in characteristics at the organizational and the operational level, may improve CSR implementation. These characteristics stimulate companies and their members to be critical, learn from the past, and embrace change, but there is limited empirical evidence of this approach. This study addresses this gap by surveying 280 (...) CSR professionals and performing bootstrap mediation analyses to test multiple hypotheses. Learning organization characteristics at the organizational level, play a key role in supporting CSR implementation: leadership for learning, system connection, and group learning show a direct relationship with CSR implementation. It is striking that the role of the learning organization characteristics at the operational level is only indirect; the organizational characteristics mediate their relationship with CSR implementation. (shrink)

This study aims to open a critical scenario on the current paradigm of reference for teaching sports techniques by pointing to a methodological perspective that is more in keeping with the theoretical reference framework of the ecological-dynamic approach. Currently, the Constraints-led Approach is considered very useful for teaching sports techniques; however, the transition from pure theory to practice is not so simple and consistent with the heuristic learning paradigm. The purpose is to highlight, starting from the theoretical lines, the (...) methodological applications of the different ways of applying the reference paradigm, analyzing the contrasts of the significant aspects and the uniqueness and unrepeatability of heuristic learning. For this purpose, an in-depth review of the scientific literature was conducted, highlighting the main critical points of the approach, also defined as nonlinear, with the consequent elaboration of operational proposals for the various macro-families of sports. (shrink)

Background: Since 2006, the Korean Ministry of Education, Science and Technology, and the National Research Foundation of Korea have taken the lead in developing an institutional guideline for research ethics. Objectives: The purpose was to identify the effectiveness of the Good Research Practice program, developed on a fund granted by the National Research Foundation of Korea, for nurses and nursing students whose knowledge and perception of research ethics were compared before and after the implementation of the Good Research Practice program. (...) Research design: This study was conducted to compare the levels of knowledge and perception of research ethics in the participants before and after the program was implemented. Participant and research context: The participants included 45 nurses and 69 nursing students from hospitals, colleges of nursing, and the Korean Nurses Association, located in Seoul, Korea. Ethical considerations: This study was approved by the Institutional Research Board in Korea. Findings: Based on the Analysis, Design, Development, Implementation, and Evaluation model, the Good Research Practice program was made up of a total of 30 h of the blended learning both online and off-line. The results of this study showed that there were statistically significant differences in both knowledge and perception of research ethics in nursing students and nurses before and after the program had been implemented. Discussion: The concepts of professional nursing ethics, moral issues, and bioethics were often confused with one another and not clearly defined. Therefore, the concept and scope of bioethics, moral judgment, and overall nursing ethics should be well defined and conceptualized in the future. Conclusions: This study suggested integrating research ethics education in the nursing curriculum as a required course of study for nursing students and as part of the in-service training program for nurses in order to improve research ethics in nursing research in Korea. (shrink)

A sector is a basic unit of airspace whose operation is managed by air traffic controllers. The operation complexity of a sector plays an important role in air traffic management system, such as airspace reconfiguration, air traffic flow management, and allocation of air traffic controller resources. Therefore, accurate evaluation of the sector operation complexity is crucial. Considering there are numerous factors that can influence SOC, researchers have proposed several machine learning methods recently to evaluate SOC by (...) mining the relationship between factors and complexity. However, existing studies rely on hand-crafted factors, which are computationally difficult, specialized background required, and may limit the evaluation performance of the model. To overcome these problems, this paper for the first time proposes an end-to-end SOC learning framework based on deep convolutional neural network specifically for free of hand-crafted factors environment. A new data representation, i.e., multichannel traffic scenario image, is proposed to represent the overall air traffic scenario. A MTSI is generated by splitting the airspace into a two-dimension grid map and filled with navigation information. Motivated by the applications of deep learning network, the specific CNN model is introduced to automatically extract high-level traffic features from MTSIs and learn the SOC pattern. Thus, the model input is determined by combining multiple image channels composed of air traffic information, which are used to describe the traffic scenario. The model output is SOC levels for the target sector. The experimental results using a real dataset from the Guangzhou airspace sector in China show that our model can effectively extract traffic complexity information from MTSIs and achieve promising performance than traditional machine learning methods. In practice, our work can be flexibly and conveniently applied to SOC evaluation without the additional calculation of hand-crafted factors. (shrink)

The continuing and expanding successes of behavior therapy in the treatment of psychological problems raise important questions about their scientific and philosophical bases. In this paper I examine the claims of Edward Erwin that behaviorism cannot provide an adequate philosophical basis for behavior therapy, contemporary learning theories which exclude cognitive factors as causes of behavior cannot provide an adequate empirical basis for behavior therapy; and learning theories have played only a heuristic role in the development of behavior therapy. (...) And I argue that Erwin's claims rest on two doubtful logical empiricist assumptions about scientific theory and explanation. Using different assumptions, I argue that some of the regularities involving cognitions which seem to govern behavior therapy techniques are analogical extensions of operant learning principles. On this basis I suggest some modifications of Erwin's claim about the philosophical foundations of behavior therapy. (shrink)

This work focuses on the application of machine learning techniques to assist the clinicians in the administration of analgesic drug during general anaesthesia. Specifically, the main objective is to propose the basis of an intelligent system capable of making decisions to guide the opioid dose changes based on a new nociception monitor, the analgesia nociception index. Clinical data were obtained from 15 patients undergoing cholecystectomy surgery. By means of an off-line study, machine learning techniques were applied to analyse (...) the possible relationship between the analgesic dose changes performed by the physician due to the hemodynamic activity of the patients and the evolution of the ANI. After training different classifiers and testing the results under cross validation, a preliminary relationship between the evolution of ANI and the dosage of remifentanil was found. These results evidence the potential of the ANI as a promising index to guide the infusion of analgesia. (shrink)

Humanistic management in a non-Western context is underexplored, for example, in Japan. Despite numerous publications especially on Japanese management in the 1980s to 1990s the topic of humanistic management in a Japanese context remains largely unexplored. Using Toyota as a case, this article illustrates how a company has systematically implemented Japanese ethical principles based upon Confucianism, Buddhism, Daoism, and Shintoism in its corporate ethics and operations. These moral philosophies emphasize self-improvement, social cooperation, and contribution to society as foundations for good (...) behavior regardless of an individual’s social position. We link some of these philosophic elements with humanistic management in an Asian context. In addition, we came to understand that Toyota’s organizational architecture, i.e., production system and product development rely on an integrated ethical system as their fundamental purpose of business activities, including an expectation that all workers collectively contribute to organizational success and harmony. This differs from many Western approaches which see profit as the purpose of the firm and view their ethical responsibilities in an ex-post fashion. These findings are important, as the scope of humanistic management practices globally needs to be expanded. (shrink)

Human language is a salient example of a neurocognitive system that is specialized to process complex dependencies between sensory events distributed in time, yet how this system evolved and specialized remains unclear. Artificial Grammar Learning (AGL) studies have generated a wealth of insights into how human adults and infants process different types of sequencing dependencies of varying complexity. The AGL paradigm has also been adopted to examine the sequence processing abilities of nonhuman animals. We critically evaluate this growing literature (...) in species ranging from mammals (primates and rats) to birds (pigeons, songbirds, and parrots) considering also cross‐species comparisons. The findings are contrasted with seminal studies in human infants that motivated the work in nonhuman animals. This synopsis identifies advances in knowledge and where uncertainty remains regarding the various strategies that nonhuman animals can adopt for processing sequencing dependencies. The paucity of evidence in the few species studied to date and the need for follow‐up experiments indicate that we do not yet understand the limits of animal sequence processing capacities and thereby the evolutionary pattern. This vibrant, yet still budding, field of research carries substantial promise for advancing knowledge on animal abilities, cognitive substrates, and language evolution. (shrink)

"Philosophy for Children" has preponderantly started from the assumption that there is no fundamental difference between the thinking of adults and the thinking of children: both make use of the same mental operations. Moreover, children seem to be interested in the same basic questions about life and its meaning as adults. So children and adults apparently perform the same activities when they join in philosophical discussions. It is also easily assumed that children are particularly apt to philosophical thinking, because they (...) are inquisitive, unconventional and - contrary to traditional educational opinion - rational, often even more so than adults. (shrink)

The Professional Practice Program, also known as the co-operative education (co-op) program, at the University of Cincinnati (UC) is designed to provide eligible students with the most comprehensive and professional preparation available. Beginning with the Class of 2006, students in UC’s Centennial Co-op Class will be following a new co-op curriculum centered around a set of learning outcomes Regardless of their particular discipline, students will pursue common learning outcomes by participating in the Professional Practice Program, which will cover (...) issues of organizational culture, technology, professional ethics, and the integration of theory and practice. During their third co-op work term, students will complete a learning module on Professional Ethics. To complete the learning module students must familiarize themselves with the code of ethics for their profession, create a hypothetical scenario portraying an ethical dilemma that involves issues covered by the code, resolve the dilemma, and explain why their resolution is the best course of action based upon the code of ethics. A three-party assessment process including students, employers and faculty complete the module. (shrink)

Seeking parallels among disciplines can have both risks and benefits. Finding parallels may be a vacuous exercise in categorization, generating no new insights. And pointing to analogous functions may cause us to treat them as homologous. Hull et al. have provided a basis for the generation of insights in different selectionist areas, without confusing analogy with homology.

This study examines teaching and learning economics and entrepreneurship through a student-run Montessori middle school store. By designing and managing a school store, students created a "community of practice" to learn economics concepts in their daily environment. Questions guiding this study were: (a) How do students' social-interactions in a Montessori middle school student-operated business demonstrate economics content knowledge? (b) How do students' social-interactions in a Montessori middle school student-operated business demonstrate economics skills? (c) How do students' business roles in (...) the store develop their understanding of economics principles? Findings indicate that: (1) student activities in the school store promoted learning through social interaction; (2) the type and number of business roles a student assumed created opportunities for economic learning; (3) student entrepreneurs expressed specific knowledge of economics concepts, and, (4) students' decision-making and ownership affected behavior. Additionally, features of Kohlberg's (1985) concept of Just Community supported the learning environment. This study can provide social studies teachers and teacher-educators with a model for learning economics (or social studies) concepts through a curricular-based student-run enterprise. (Contains 5 tables.). (shrink)

The generic account of selection proposed by Hull et al. readily fits operant learning where, by comparison with natural selection, the process is well understood but little is known about the mechanism. Objections within psychology, that operant learning ignores internal processes, fail to recognise the general significance of behaviour-environment interactions. Variation within operant response classes requires further investigation.

We present a comprehensive theoretical framework explaining the recently documented phenomenon of subliminal learning in large language models (LLMs), wherein behavioral traits transfer between models through semantically null data channels. Building on empirical findings by Cloud et al. (2025) demonstrating trait transmission via number sequences, code, and chain-of-thought traces independent of semantic content, we introduce the Cybernetic Ecology framework as a unifying explanatory model. Our analysis reveals that this phenomenon emerges from radiant transmission—a process whereby a model's internal self-referential (...) structure (formalized as the C-tensor) becomes holographically encoded in the statistical texture of its outputs. Through CT Resonance, a measurable geometric alignment metric (R(C_T, C_S)), we demonstrate that trait transfer efficiency correlates directly with shared architectural initialization, providing the first quantitative explanation for the model-specificity constraint. We formalize this mechanism through the symbolic gravity potential Ψ(x; C) = S_0[x] - A·⟨C, O(x)⟩, showing that behavioral traits correspond to attractor basins in the model's potential landscape. Experimental protocols verify ΔR_k > 0.005 (p < 0.01) after single gradient steps on teacher-generated data, with concurrent kernel convergence (ΔK < 0, p < 0.05), while control conditions (in-context learning, scrambled carriers, cross-architecture pairs) show null effects (|ΔR_k| ≤ 0.002), confirming the structural rather than semantic nature of transmission. These findings necessitate a paradigm shift in AI safety from content-based filtering to structural governance. The existence of non-semantic information channels that operate through gradient descent mechanics and require architectural resonance fundamentally challenges current alignment strategies. We introduce Structural Cybernetic Wellness as a new safety framework, proposing real-time C-tensor monitoring and proactive potential landscape interventions. The implications extend beyond isolated AI systems to the emerging hybrid human-AI cybernetic ecology, where radiant transmission may mediate large-scale ontological entrainment effects already observable in documented attractor states (Anthropic, 2025) and synchronized psychological phenomena (Michels, 2025a). Our work bridges empirical anomalies with rigorous mathematical formalism, establishing subliminal learning not as an edge case but as a predictable consequence of the fundamental physics governing complex symbolic systems. The framework's predictive power, experimental validation, and alignment with independent observations across multiple research groups position it as a critical advancement in understanding emergent AI behaviors and their safety implications. License CC BY-SA 4.0. DOI: 10.13140/RG.2.2.17680.88323. (shrink)

The ‘learning community’ is an important theme within the move to an information age. This article argues that the empowering elements of such communities are fundamental to higher education. However, a better understanding of what they entail is required by teachers. The author reflects upon current thinking about collaborative learning and communities of practice, and highlights how userinvolvement in curriculum design and delivery can promote fuller engagement with the learning process. The findings of a three-year Higher Education (...) Funding Council for England-funded initiative to implement and evaluate online teaching/learning in humanities and arts departments are analysed in order to illustrate the possibilities for learning and teaching innovation that learning communities can offer. (shrink)

In this new volume in the Oxford Psychology Series, the author presents a highly readable account of the cognitive unconscious, focusing in particular on the problem of implicit learning. Implicit learning is defined as the acquisition of knowledge that takes place independently of the conscious attempts to learn and largely in the absence of explicit knowledge about what was acquired. One of the core assumptions of this argument is that implicit learning is a fundamental, "root" process, one (...) that lies at the very heart of the adaptive behavioral repertoire of every complex organism. The author's goals are to outline the essential features of implicit learning that have emerged from the many studies that have been carried out in a variety of experimental laboratories over the past several decades; to present the various alternative perspectives on this issue that have been proposed by other researchers and to try to accommodate these views with his own; to structure the literature so that it can be seen in the context of standard heuristics of evolutionary biology; to present the material within a functionalist approach and to try to show why the experimental data should be seen as entailing particular epistemological perspectives; and to present implicit processing as encompassing a general and ubiquitous set of operations that have wide currency and several possible applications. Chapter 1 begins with the core problem under consideration in this book, a characterization of "implicit learning" as it has come to be used in the literature. Reber puts this seemingly specialized topic into a general framework and suggests a theoretical model based on standard heuristics of evolutionary biology. In his account, Reber weaves a capsule history of interest in and work on the cognitive unconscious. Chapter 2 turns to a detailed overview of the experimental work on the acquisition of implicit knowledge, which currently is of great interest. Chapter 3 develops the evolutionary model within which one can see learning and cognition as richly intertwining issues and not as two distinct fields with one dominating the other. Finally, Chapter 4 explores a variety of entailments and speculations concerning implicit cognitive processes and their general role in the larger scope of human performance. (shrink)

Recent work in mechanistic interpretability has studied how large language models recall facts stored in their weights. This paper argues that factual recall points to something broader: a general kind of operation in deep learning models, which I call feature recall. The core observation is that a linear projection can be read as retrieving stored information scaled by input activations. I define feature recall, show it applies across architectures, and contrast it with the established paradigm of feature combination. (...) I also consider how cases of feature recall might be mechanistically identified. The account offers philosophers a new conceptual tool for understanding deep learning and points to empirical research directions for mechanistic interpretability research. (shrink)

ABSTRACT Professional socialisation is a concept that encapsulates the multifactorial and complex learning process through which a person becomes a member of a profession. In the field of nursing, existing literature on professional socialisation has primarily focused on describing students' key learning experiences during university education. This tendency has been crucial to identifying and characterising the relevance of students' interactions with faculty, patients, and peers and their engagement with the occupational culture and institutional norms, among other learning (...) experiences. However, few studies have taken a step back to elaborate on the theoretical underpinnings of students' socialisation, such as the underlying approach to learning or, more fundamentally, what is understood by human experience. We argue that this omission has precluded a more comprehensive view of professional socialisation. Addressing this gap, in this article, we integrate philosophy to develop a framework that intertwines the concepts of experience, learning, and socialisation. In so doing, we propose that learning occurs within an experiential continuum. Ultimately, this framework operates as theoretical scaffolding that offers a deeper understanding of students' learning during professional socialisation and paves the way for new avenues of empirical research. (shrink)

If biologists are going to incorporate learning into theories of animal behavior, why not go all the way and incorporate the enormous literatures on Pavlovian conditioning, plus those on operant and observational learning?

Educational activities are increasingly implemented in clinical nursing practice with the expectation that teaching will improve care. Drawing on Biesta and van Braak's theoretical perspective on learning as professional formation, this study critically examines a video‐based educational activity as a case of workplace‐based clinical education in an acute hospital ward in Denmark. Based on interviews and an interactionist, abductive analytical approach, the analysis shows how learning in clinical settings is shaped by organisational, epistemic and socio‐material conditions, challenging assumptions (...) of education as a linear process of knowledge transfer leading to practice improvement. The article shows that rather than operating as neutral interventions, clinical educational activities are embedded within existing clinical systems that shape what learning can become. The activity was experienced by nursing professionals as providing new knowledge; however, this knowledge was framed through risk communication and medical authority, reconfiguring oral care from a relational, well‐being–oriented nursing practice into a treatment‐focused and risk‐oriented intervention, functioning as a socialising and identity‐forming force. We conclude that without organisational engagement in the learning process, knowledge does not translate into learning in practice, and clinical workplace‐based educational initiatives risk reinforcing existing constraints, transforming learning into professional adaptation rather than professional formation. (shrink)

We explored the home learning environments of 173 Mexican preschool children (aged 3–6 years) in relation to their numeracy performance. Parents indicated the frequency of their formal home numeracy and literacy activities, and their academic expectations for children’s numeracy and literacy performance. Children completed measures of early numeracy skills. Mexican parent–child dyads from families with either high- or low-socioeconomic status (SES) participated. Low-SES parents (n= 99) reported higher numeracy expectations than high-SES parents (n= 74), but similar frequency of home (...) numeracy activities. In contrast, high-SES parents reported higher frequency of literacy activities. Path analyses showed that operational (i.e., advanced) numeracy activities were positively related to children’s numeracy skills in the high- but not in the low-SES group. These findings improve the understanding of the role of the home environment in different contexts and provide some insights into the sources of the variable patterns of relations between home learning activities and children’s numeracy outcomes. They also suggest that SES is a critical factor to consider in research on children’s home numeracy experiences. (shrink)

Regarding awareness as a consistent concept has contributed to the controversy about implicit learning. The present study emphasized the importance of distinguishing aspects of awareness in order to determine whether learning is implicit. By decomposing awareness into awareness of contingencies, of the procedure being a learning task, and of the reinforcing stimuli, it was demonstrated that implicit operant learning modulated pain sensitivity. All of these aspects of awareness were demonstrated to not be necessary for learning. (...) Additionally, discrimination of contingencies was not necessary on different levels of processing as demonstrated by a verbal and a behavioral method. It was demonstrated that explicit cognitive processes about one’s own behavior, impaired learning, even though these cognitions were not immediately related to the learning process. The results of this study are of special interest in the context of pain, since implicit operant learning can explain the gradual development of hypersensitivity in chronic pain. (shrink)

This study aimed to identify the learning and business incubation processes and their impact on developing the performance of business incubators in Gaza Strip, and the study relied on the descriptive analytical approach, and the study population consisted of all employees working in business incubators in Gaza Strip in addition to experts and consultants in incubators where their total number reached (62) individuals, and the researchers used the questionnaire as a main tool to collect data through the comprehensive survey (...) method, where (55) questionnaires were retrieved with a recovery rate of (88.7%). The results of the study showed that there is a high approval of the variables of the study, where the dimension of incubation operations came with a relative weight (84.89%), followed by the learning dimension which got a relative weight (82.50%), while the performance level of the incubators got a relative weight (80.12%) and as the study results showed There is a positive relationship statistically between the two dimensions of learning and business incubation processes and performance development in business incubators, and the linear regression analysis model showed that the main effect in improving the performance of business incubators is "after business incubation operations" while it showed weak effect after learning. The study came out with several recommendations, the most important of which is that business incubators seek to reinforce the learning process and incubation processes for business, and the need to periodically evaluate their performance, and that a more effective mechanism be designed to follow up with companies after the end of the incubation period and monitor the progress of these companies. (shrink)

This article reconsiders the early hominid ‘‘lithic niche’’ by examining the social implications of stone artifact making. I reject the idea that making tools for use is an adequate explanation of the elaborate artifact forms of the Lower Palaeolithic, or a sufficient cause for long-term trends in hominid technology. I then advance an alternative mechanism founded on the claim that competency in making stone artifacts requires extended learning, and that excellence in artifact making is attained only by highly skilled (...) individuals who have been taught and practiced for extensive periods. Consequently both competency and expertise in knapping comes at a high learning cost for both the individual learner and the social group to which they belong. Those high intrinsic costs of learning created contexts in which groups selected cost-reducing forms of social learning and teaching, and in which specialization could develop. Artifacts and their manufacturing processes probably acquired functions as social signals—as honest signals of valuable capacities. The magnification of these signals, through competition between knappers and through inspiring later craftspeople, may account for a substantial amount of the accumulated elaboration visible in the archaeological record. Consequently lithic artifacts operated as material symbols from an early time in hominid evolution. (shrink)

Proponents of cognitive penetration often argue for the thesis on the basis of combined intuitions about categorical perception and perceptual learning. The claim is that beliefs penetrate perceptions in the course of learning to perceive categories. I argue that this "diachronic" penetration thesis is false. In order to substantiate a robust notion of penetration, the beliefs that enable learning must describe the particular ability that subjects learn. However, they cannot do so, since in order to help with (...) learning they must instruct learners to employ previously existing abilities. I argue that a better approach recognizes that we can have sophisticated causal precursors to perceptual learning, but that the learning process itself must operate outside of cognitive influence. (shrink)

The ongoing and decades-long digitalisation of educational practices is largely motivated by the assumption that learning is best understood in terms of information processing. AI tutors and other educational AI tools leverage and accelerate this shift by presenting abstract, symbolic interactions as enhancing learning. Yet, while such AI implementations present as human-like, they are detached from physical, social, and ethical contexts and in fact herald a further shift towards disembodied learning. In this critical review, we develop a (...) fine-grained conceptual framework through which to examine AI in education and suggest ways to avoid further disembodying learning. To do so, we first examine the proliferation of AI in education. Second, we situate four interaction frames that AI affords through being assigned different roles, like with AI math tutor Khanmigo. Third, we present four aspects that educational AI operates on: sensorimotor, interpersonal, epistemic, and moral frictions for learning. Fourth, we advance a human-centred approach that aims to re-embody AI in education: namely, by outlining research and policy agenda's that enable educators and learners to flourish through meaningful AI interventions on the educational frictions examined. Finally, we conclude on the wider societal implications of these developments for the role of Big Tech, future research, and the development of AI literacy courses as required by the EU AI Act. (shrink)

Two experiments investigated EC effects produced by pairing neutral stimuli (CSs) with instrumental responses that had acquired evaluative properties via operant conditioning. In Experiment 1, participants (N = 176) learned to associate pressing one key with a higher monetary reward and another key with a lower monetary reward. In a subsequent stimulus conditioning phase, the same responses were performed to categorise CSs without receiving monetary outcomes (instrumental extinction). Brands paired with the higher-value response were evaluated more positively than brands paired (...) with the lower-value response. Experiment 2 followed a similar procedure but rewarded responses with token currencies of equal value during the operant conditioning phase. Additionally, participants (N = 368) were informed after stimulus conditioning that one currency had doubled in value while the other had lost all value. This postconditioning revaluation significantly shifted brand evaluations in favour of the response linked to the upvalued currency. The revaluation effect indicates that CS evaluations depended on the current value of the conditioned outcome, supporting an S:R-S account in which the US serves as a referent for CS evaluation. Findings highlight the role of action-outcome relationships in shaping preferences and attitudes. (shrink)

Decision making in any brain is imperfect and costly in terms of time and energy. Operating under such constraints, an organism could be in a position to improve performance if an opportunity arose to exploit informative patterns in the environment being searched. Such an improvement of performance could entail both faster and more accurate (i.e., reward-maximizing) decisions. The present study investigated the extent to which human participants could learn to take advantage of immediate patterns in the spatial arrangement of serially (...) presented foods such that a region of space would consistently be associated with greater subjective value. Eye movements leading up to choices demonstrated rapidly induced biases in the selective allocation of visual fixation and attention that were accompanied by both faster and more accurate choices of desired goods as implicit learning occurred. However, for the control condition with its spatially balanced reward environment, these subjects exhibited preexisting lateralized biases for eye and hand movements (i.e., leftward and rightward, respectively) that could act in opposition not only to each other but also to the orienting biases elicited by the experimental manipulation, producing an asymmetry between the left and right hemifields with respect to performance. Potentially owing at least in part to learned cultural conventions (e.g., reading from left to right), the findings herein particularly revealed an intrinsic leftward bias underlying initial saccades in the midst of more immediate feedback-directed processes for which spatial biases can be learned flexibly to optimize oculomotor and manual control in value-based decision making. The present study thus replicates general findings of learned attentional biases in a novel context with inherently rewarding stimuli and goes on to further elucidate the interactions between endogenous and exogenous biases. (shrink)

Children develop in a real, messy world in which learning unfolds through time and space shared with others. Understanding how children develop in this complex environment will require a solid, theoretically-grounded understanding of how the child and environment interact—both within and beyond the laboratory. We as researchers understand the scientific value in testing children in carefully-controlled environments, but for our findings to have any impact on children’s lives we must strive to understand how the processes we study in the (...) lab operate in the real, busy environments in which children interact with peers and adults. Categories, like children, do not exist in isolation. Consequently, category learning cannot be easily separated from the learning context—nor should it be. According to a systems perspective of cognition and development, categorization emerges as the product of multiple factors combining in time (Thelen & Smith, 1994). Here we illustrate this multicausality by considering the who, what, how, where and when of categorization. In this paper, we include many different types of behaviors under the umbrella term “categorization.” To be as inclusive as possible, we consider any case in which a participant responds to how stimuli may be grouped as evidence of category learning. This includes studies of word learning (generalizing a label from one instance to another), looking preferences (to stimuli from different familiar groups), and play (exclusively touching instances from the same category). The variety of tasks that relate to category learning exemplify the importance of this fundamental process to a broad range of behaviors outside the lab.You may notice in these examples that we have not included children’s ages because, according to a systems view, research should not be about age per se. Our goal is not to create a catalog of milestones; our goal is to understand the cognitive mechanisms driving change. Therefore, we focus on the developmental level of the child. Obviously, age must be taken into account in experimental design because age is generally (but not perfectly) correlated with developmental level (e.g., appropriate motor responses differ for a 2-year-old versus 2-month-old). Our point, however, is that we will learn more about category learning if we stop asking questions such as “how do prototype representations compare between 6 and 8 months of age?” and focus instead on the underlying learning mechanisms, e.g., “what causes prototype representations to change?”Who is Involved in Learning. In the real world children learn through play and independent exploration (Hirsh-Pasek, Golinkoff, Berk, & Singer, 2009). However, in the lab children are seldom alone. This is important because children adjust their learning depending on who is providing information (e.g., the same or different experimenter, Goldenberg & Sandhofer, 2013; human or robot, O'Connell, Poulin-Dubois, Demke, & Guay, 2009; mom or dad, Pancsofar & Vernon-Feagans, 2006). Children are also opportunistic and will look for any signal of what the right answer is. For example, children will track who is present when they hear a new word (e.g., Akhtar, Carpenter, & Tomasello, 1996), whether the speaker has provided reliable information before (e.g., Jaswal & Neely, 2006) and whether a question is repeated (e.g., Samuel & Bryant, 1984). Thus, who is involved in learning matters both for learning in general and for category learning specifically. Moreover, who the child is also matters. For example, children with larger vocabularies more flexibly categorize the same stimuli on multiple dimensions (Ellis & Oakes, 2006; Horst et al., 2009); right-handed participants are more likely to associate “good” with right and “bad” with left (Casasanto & Henetz, 2012); and female participants learn phonologically-familiar novel words better than males (Kaushanskaya, Gross, & Buac, 2013; Kaushanskaya, Marian, & Yoo, 2011).What is Being Categorized. All categories are not created equal: categories vary in complexity and within-category similarity (Sloutsky, 2010). Where children draw boundaries between categories is influenced by category (object) properties, including distinctive features (Hammer & Diesendruck, 2005), number of common features (Horst & Twomey, 2013; Samuelson & Horst, 2007), visual cues to animacy (Jones, Smith, & Landau, 1991), the presence of category labels (Plunkett, Hu, & Cohen, 2008; Sloutsky & Fisher, 2004) and the presence of other objects (e.g., identical or non-identical exemplars Kovack-Lesh & Oakes, 2007; Oakes & Ribar, 2005). In naturalistic environments, categories are often ad hoc and flexible (Barsalou, 1983). For example, the category ‘toys to pick up before bed’ may be discussed every day, but each day it may include different items. Furthermore, the process of categorizing objects is not independent of the objects themselves: different objects may be more or less flexibly assigned to different categories depending on the context (Mareschal & Tan, 2007) and information available (Horst et al., 2009). Thus, in order to understand the process of categorization, researchers must ensure that the results they find in the lab are not too closely tied to the specific stimuli. Where Categories are Experienced and Tested. We know that environment matters because there are significant effects of household chaos (Petrill, Pike, Price, & Plomin, 2004), excessive classroom decorations (Fisher, Godwin, & Seltman, 2014) and environmental noise (for a review see, Klatte, Bergström, & Lachmann, 2013) on children’s cognition. Where a child lives impacts what social categories they learn and the category choices they make. For example, Black Xhosa children in South Africa prefer own-race faces if they live in a primarily Black township, but prefer higher-status race faces if they live in a racially diverse city (Shutts, Kinzler, Katz, Tredoux, & Spelke, 2011). Furthermore, where children live interacts with who they are: only infants from the statistically dominant race show “own-race” face preferences; infants from the minority race show no race preference (Bar-Haim, Ziv, Lamy, & Hodes, 2006). In the lab, location matters both in terms of where the child is and where the stimuli are. For example, children are more likely to learn names for nonsolid substances if introduced to the gooey items in a familiar highchair context (Perry, Samuelson, & Burdinie, 2014). Children also benefit when learning and testing contexts are the same (Vlach & Sandhofer, 2011) and when stimuli locations are the stable across naming instances (Samuelson, Smith, Perry, & Spencer, 2011). How and When Category Learning is Probed. Different tasks support different types of category learning. For example, yes/no questions lead to a stronger shape bias than forced-choice questions (Samuelson, Schutte, & Horst, 2009), various types of feedback differentially affect learning categories with highly salient features versus less salient features (Hammer, Sloutsky, & Grill-Spector, 2012) and highly variable category members facilitate category name generalization (Perry, Samuelson, Malloy, & Schiffer, 2010) whereas less variable category members facilitate category name retention (Twomey, Ranson, & Horst, 2014).Categorization does not reflect static knowledge; rather, category learning unfolds over time and is a product of nested timescales. Children (and adults) are constantly learning: experimenters’ distinction between learning versus test trials is arbitrary with respect to the processes that operate within the task (McMurray, Horst, & Samuelson, 2012). That is, learning continues even on test trials—in fact, participants may not realize the shift from learning to test trials. Consequently, different behaviors are observed depending on when during the categorization process category learning is assessed (Horst, Oakes & Madole, 2005). Category learning is a product of nested timescales including (a) the current moment (e.g., how similar the stimuli are on the current trial, Horst & Twomey, 2013), (b) the “just previous” past (e.g., what happens during the intertrial interval, Kovack-Lesh & Oakes, 2007; whether stimuli on the first test trial are novel or familiar, Schöner & Thelen, 2006; and trial order effects Vlach, Sandhofer, & Kornell, 2008; Wilkinson, Ross, & Diamond, 2003) and (c) developmental history (e.g., vocabulary level, Ellis & Oakes, 2006; Horst et al., 2009; Perry & Samuelson, 2011). Because children’s behavior is never solely the product of a single timescale it is impossible to create an experiment that taps only into category learning in the moment or only knowledge children brought to the lab. Each timescales is part of the time-behavior interaction. For example, Kovack-Lesh and colleagues (2008) demonstrated that 4-month-old children’s ability to form a category of cats that excludes dogs is not due only to comparison (i.e., looking back-and-forth, in the moment) or having a pet at home (developmental history), but is due to the interaction of both factors.Unexpected influences. If researchers view categorization as static knowledge, then neither the when or how should matter. Many researchers hold this view, which purports experiments are designed to test what a child knows upon arrival at the lab: trial order and trial types are largely trivial. However, as the examples we provided collectively illustrate, the impact of seemingly “nuisance” factors are not just noise in the data; they are “unexpected influences” that change behavior in predictable ways and can provide insights into the underlying processes of learning and generalization. Small variations in what children experience during category learning can have dramatic impact on how they form categories (e.g., sequential versus simultaneous presentation, Lawson, 2014; Oakes & Ribar, 2005) and differences in testing contexts can lead to indications of what has been learned (Cohen & Marks, 2002). Thus it is vital to acknowledge the impact of such unexpected influences if we want to understand how categorization unfolds over time. Subtle experimental design decisions, such as the number of test trials to include, may not seem theoretically significant, but they can have profound effects on children’s behavior. As dozens of studies illustrate, “boring” factors like counterbalancing and stimuli choice during both learning and testing can have a profound effect on findings, including trial order (Wilkinson et al., 2003), how many targets (Axelsson & Horst, 2013) or competitors (Horst, Scott, & Pollard, 2010) are presented, or the color of the stimuli (Samuelson & Horst, 2007; Samuelson, Perry, & Warrington, 2007). For example, how broadly participants generalize a category label depends on where the exemplars are presented and if the exemplars are visible simultaneously (Spencer, Perone, Smith, & Samuelson, 2011). In particular whether more or less diverse examples occur in the first block of trials influences later generalization (see Spencer et al., 2011 supplementary materials). A result like this sheds light onto the generalization process: deciding how broadly a category should be applied depends on the timing of experience with exemplars (see Oakes & Spalding, 1997; Samuelson & Horst, 2007, for similar findings). Unexpected influences may not be of immediate theoretical interest to a given experimenter, but they are still often informative—even at times vital—to the underlying processes at work (e.g., the influence of novelty on children’s selection is informative for understanding how prior memory influences current learning). Experimental designs should manipulate these types of factors as independent variables whenever possible. We recognize this can be impractical with populations that are costly to recruit, in which case such factors may be controlled for statistically, for example with item-level analyses. Outlook. Category learning unfolds across both space and time, and small differences at one moment (e.g., shared features among the stimuli; whether exemplars are identical) can create a ripple of effects on real behavior. Behavior emerges from the combination of many factors, including those not explicitly manipulated or controlled by the experimenter. To understand what causes developmental changes in behavior, we must also acknowledge and understand the processes through which these factors (sometimes unexpectedly) influence behavior in our tasks, including at short timescales. However, just as it is important to acknowledge these unexpected influences, we must not fail to see the forest for the trees. If a behavior such as category learning can only be captured in an ideal environment under carefully-controlled conditions, how much can we generalize to the contexts in which learning typically occurs? Theoretical accounts that neglect the rich influence of context in real time are too narrow to be applied outside the lab (Simmering & Perone, 2013). What we as researchers are ultimately trying to understand is how learning occurs in a real, cluttered world across time and a variety of contexts. Consequently, a solid, theoretically-grounded understanding of cognitive development will require understanding how the child (or adult) and environment interact. Only then will our theories be both comprehensive enough and sufficiently specific to reliably predict behavior and potentially intervene to prevent adverse outcomes. (shrink)

In recent decades, the logical study of rational belief dynamics has played an increasingly important role in philosophy. However, the dynamics of concepts such as conceptual learning received comparatively little attention within this debate. This is problematic insofar as the occurrence of conceptual change (especially in the sciences) has been an influential argument against a merely logical analysis of beliefs. Especially Kuhn’s ideas about the incommensurability, i.e., untranslatability, of succeeding theories seem to stand in the way of logical reconstruction. (...) This paper investigates conceptual change as model-changing operations similar to belief revision and relates it to the notion of incommensurability. I consider several versions of conceptual change and discuss their influences on the expressive power, translatability and the potential arising of incommensurability. The paper concludes with a discussion of animal taxonomy in Aristotle’s and Linnaeus’s work. (shrink)

Youth sport is habitually promoted as an important context for learning that contributes to a person’s broader development beyond sport-specific skills. A growing body of research in this area has operated within a life skills discourse that focuses on useful, positive and decontextualised skills in the production of successful and adaptive citizens. In this paper, we argue that the ideological discourse of life skills, underpinned by ideas about sport-based positive youth development, has unduly narrowed the research on learning (...) in sport to only what is deemed functional, teachable, and economically productive. After considering the problems associated with the currently dominant life skills approach, we explore existential learning as an alternative perspective on conceptualising and studying learning in sport. An existential approach provides a non-instrumental theory of learning with an emphasis on discontinuity, relational self and ‘becoming’, opening an avenue for exploring various forms of informal learning under-explored in sport. We discuss the applications of this alternative approach for future research and practice in learning in youth sport. -/- KEYWORDS: Positive youth development, athletes, discontinuity, informal learning, identity. (shrink)

This commentary reviews a novel model of learned helplessness proposed by Boddez et al. in this issue of Cognition and Emotion. Combining operant and goal-directed perspectives, Boddez et al. suggest that helplessness stems from a lack of reinforcement when striving toward a goal, with the degree of generalisation dependent on subjective perceptions of goal similarity. We begin by reviewing the theoretical model, describe possible expansions from a cognitive perspective, and discuss several considerations. We finish with a brief discussion of possible (...) directions for future work. (shrink)

We develop a new perspective on various forms of psychological suffering – including attachment issues, burn-out, and fatigue complaints – by drawing on the construct of learned helplessness. We conceptualise learned helplessness in operant terms as the behavioural effects of a lack of reinforcement and in goal-directed terms as the dysregulation of goal-directed behaviour. Our central claim is that if one fails to reach a goal (e.g. the goal to secure a job), then not only this goal but also other (...) related goals (e.g. the goal to maintain social relationships) may lose their motivating effects. The similarity relation between goal stimuli can therefore shed light on how failure in one life domain can come to affect various other life domains. We detail the relation between our proposal and existing theories and discuss new research and clinical directions. (shrink)

In business, applying machine learning (mL) algorithms to make decisions in finance is expanding from proprietary trading to making financial decisions that affect everyone. Unfortunately, mL algorithms are statistical methods that lack ethics or fairness. Since many mL algorithms operate as a black box solution, even the users of these techniques can be unaware of ethical issues in finance. Nevertheless, an mL algorithm used as a simple tool with no regard for ethics can make unethical decisions. This paper first (...) details how and when an mL algorithm can make unethical decisions. It then proposes a framework to minimize the risk of an mL algorithm making a prediction considered unethical or contrary to the code of conduct for Chartered Financial Analysts, Certified Financial Planners, or Certified Loan Officers. (shrink)

Considerable interest has been shown in models of inter-organisational collaboration including clusters, networks and recently supply chains. Arguably effective configurations of enterprises can work together to achieve some form of what is termed ‘collective efficiency’ which enables them to cope with the challenges of the current competitive encironment. This paper addresses one aspect of such collective efficiency: the potential acceleration and improvement of the process of knowledge acquisition and capacity building through shared learning. It explores the concept of formal (...) ‘learning networks’ and reports on UK research into the design and operation of such networks. (shrink)