This essay introduces this special issue on virtue ethics in relation to military AI. It describes the current situation of military AI ethics as following that of AI ethics in general, caught between consequentialism and deontology. Virtue ethics serves as an alternative that can address some of the weaknesses of these dominant forms of ethics. The essay describes how the articles in the issue exemplify the value of virtue-related approaches for these questions, before ending with thoughts for further research.

Objective: Mindfulness-based intervention has been proposed to alleviate loneliness and improve social connectedness. Several randomized controlled trials have been conducted to evaluate the effectiveness of MBI. This study aimed to critically evaluate and determine the effectiveness and safety of MBI in alleviating the feeling of loneliness.Methods: We searched Medline, Embase, PsycInfo, Cochrane CENTRAL, and AMED for publications from inception to May 2020. We included RCTs with human subjects who were enrolled in MBI with loneliness as an outcome. The quality of (...) evidence was assessed using Cochrane's Risk of Bias tool and Grading of Recommendations Assessment, Development, and Evaluation. A random-effects model was used for meta-analysis.Results: Out of 92 articles identified, eight studies involving 815 participants were included in this study. Most trials conducted a minimum of 8 weeks of MBI. Most of the trials used UCLA-Loneliness Scale. A pooled analysis combining three trials and compared with wait-list showed significant improvement in loneliness score reduction using the UCLA-R scale with MD of −6.33 [95% confidence interval : −9.39, −3.26]. Subgroup analysis with only two Cognitively-Based Compassion Training trials also showed similar MD of −6.05. The overall quality of evidence was low.Conclusions: Mindfulness intervention with an average length of 8-week duration significantly improved the population's loneliness level with no mental health issue. However, this evidence had a low GRADE level. (shrink)

Collaborative learning with cases characteristically involves discussing and developing shared explanations. We investigated the argumentation scheme which learners use in constructing shared explanations over evidence. We observed medical students attempting to explain how a judge had arrived at his verdict in a case of medical negligence. The students were learning within a virtual learning environment and their communication was computer mediated. We identify the dialogue type that these learners construct and show that their argumentation conforms with an (...) abductive form of argumentation scheme (‘inference to the best explanation’). We also assessed the students’ learning and propose that it is related to particular features of this argumentation scheme. (shrink)

This is a response to the nine commentaries on our target article “Unlimited Associative Learning: A primer and some predictions”. Our responses are organized by theme rather than by author. We present a minimal functional architecture for Unlimited Associative Learning that aims to tie to together the list of capacities presented in the target article. We explain why we discount higher-order thought theories of consciousness. We respond to the criticism that we have overplayed the importance of learning (...) and underplayed the importance of spatial modelling. We decline the invitation to add a negative marker to our proposed positive marker so as to rule out consciousness in plants, but we nonetheless maintain that there is no positive evidence of consciousness in plants. We close by discussing how UAL relates to development and to its material substrate. (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)

Birch, Ginsburg, and Jablonka suggest that Unlimited Associative Learning is a “transition marker” in the evolutionary process that produced consciousness, and organizes research by tying together a range of “hallmarks” of consciousness. I argue that the features they recognize as “hallmarks” are indeed important in the evolution of consciousness, but UAL may have a more limited role.

How can imitation lead to free musical expression? This article explores the role of auditory imitation in jazz. Even though many renowned jazz musicians have assessed the method of imitating recorded music, no systematic study has hitherto explored how the method prepares for aural jazz improvisation. The article picks up an assumption presented by Berliner (1994), suggesting that learning jazz by aural imitation is “just like” learning a mother tongue. The article studies three potential stages in the method, (...) comparing with imitative, rhythmic, multimodal, and protosymbolic behavior of infant perception (building on the works of Stern, Trevarthen, and Merleau-Ponty). The demonstrations of the aural-imitation method draw on pedagogic experiences accumulated since 1979 in the Jazz Program at the Norwegian University of Science and Technology. By analyzing structures of behavior suggested by the method, the article indicates key traits that render aural jazz improvisation possible, such as a fundamental sense of rhythm, formation of symbolic behavior, joint musical attention, and the facility to “hear via the other.” In conclusion, we critically address a frequent theoretical model describing musical improvisation as a synthesis of discrete elements or building blocks. (shrink)

Meta-learning is learning to learn, which includes the development of capacities to transfer what people learned in one specific domain to other domains. It facilitates finetuning learning parameters and setting priors for effective and optimal learning in novel contexts and situations. Recent advances in research on artificial intelligence have reported meta-learning is essential in improving and optimizing the performance of trained models across different domains. In this paper, I suggest that meta-learning plays fundamental roles (...) in practical wisdom and its cultivation within moral domains. I support my argument with findings from studies in psychology, neuroscience, and computer science. Moreover, I suggested concrete ideas for moral education to foster wisdom cultivation along with meta-learning with evidence from studies across various fields. Particularly, I underscored that exemplars, including role models and mentors, play fundamental roles in education. Finally, I discussed the potential implications of the introduction of the concept, meta-learning, to moral education addressing concerns and issues related to socio-cultural diversity. (shrink)

Learning Beyond the Objective in Primary Education explores an existential perspective for pedagogy in response to the current technocratic paradigm of education prevalent in many countries worldwide. This new perspective is termed 'Bildung's repetition.' The book seeks to encourage policy makers and educational practitioners to consider the impact of education on children, over and above the meeting of set targets and objectives.

Deep learning algorithms are rapidly changing the way in which audiovisual media can be produced. Synthetic audiovisual media generated with deep learning—often subsumed colloquially under the label “deepfakes”—have a number of impressive characteristics; they are increasingly trivial to produce, and can be indistinguishable from real sounds and images recorded with a sensor. Much attention has been dedicated to ethical concerns raised by this technological development. Here, I focus instead on a set of issues related to the notion of (...) synthetic audiovisual media, its place within a broader taxonomy of audiovisual media, and how deep learning techniques differ from more traditional approaches to media synthesis. After reviewing important etiological features of deep learning pipelines for media manipulation and generation, I argue that “deepfakes” and related synthetic media produced with such pipelines do not merely offer incremental improvements over previous methods, but challenge traditional taxonomical distinctions, and pave the way for genuinely novel kinds of audiovisual media. (shrink)

Over the last decades, consistent research showed that voluntary work could be considered as a tool for professional development and concrete employment: volunteering could be either experienced as a desire to improve career opportunities or to acquire new skills. The study aimed to investigate voluntary work as a context of informal and non-formal workplace learning and vocational guidance, useful to develop skills and abilities, namely the capital of personal and social resources, that could promote future employability. Participants were 38 (...) young volunteers who experienced the Universal Civil Service, a national Italian program addressed to young people aged up to 28 years, giving them both the opportunity to engage in social activities useful for the community and have the first contact with a working context. In line with the objectives of the study, participants were invited to describe their volunteering experience in a diary, highlighting if and to what extent this context contributed to enhancing their employability capital, namely the asset of skills, knowledge, and networks acquired, that they could transfer to a future professional domain. The narrative data collected were examined through diatextual analysis, a specific address of discourse analysis designed to catch the relationship between enunciators, text, and context of the talk. This qualitative analysis allowed us to investigate the meanings young people attributed to these activities. In light of these results, the paper contributed to investigate volunteers’ perceptions about the conditions that could best foster this specific kind of workplace informal and non-formal learning and at proposing a qualitative perspective on the analysis of the employability capital they developed. (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)

In LOT 2: The Language of Thought Revisited, Jerry Fodor argues that concept learning of any kind—even for complex concepts—is simply impossible. In order to avoid the conclusion that all concepts, primitive and complex, are innate, he argues that concept acquisition depends on purely noncognitive biological processes. In this paper, we show (1) that Fodor fails to establish that concept learning is impossible, (2) that his own biological account of concept acquisition is unworkable, and (3) that there are (...) in fact many promising general models for explaining how concepts are learned. (shrink)

Artificial intelligence research connected with learning theory ("deep learning," “machine learning,” analysis of the quality of learning, etc.) has existed for many years; however, there have been few investigations in that area conducted from a robust philosophical methodological basis.

This target article presents a theory of human cultural learning. Cultural learning is identified with those instances of social learning in which intersubjectivity or perspective-taking plays a vital role, both in the original learning process and in the resulting cognitive product. Cultural learning manifests itself in three forms during human ontogeny: imitative learning, instructed learning, and collaborative learning – in that order. Evidence is provided that this progression arises from the developmental ordering (...) of the underlying social-cognitive concepts and processes involved. Imitative learning relies on a concept of intentional agent and involves simple perspective-taking. Instructed learning relies on a concept of mental agent and involves alternating/coordinated perspective-taking (intersubjectivity). Collaborative learning relies on a concept of reflective agent and involves integrated perspective-taking (reflective intersubjectivity). A comparison of normal children, autistic children and wild and enculturated chimpanzees provides further evidence for these correlations between social cognition and cultural learning. Cultural learning is a uniquely human form of social learning that allows for a fidelity of transmission of behaviors and information among conspecifics not possible in other forms of social learning, thereby providing the psychological basis for cultural evolution. (shrink)

This article argues that personal meaning should be considered important when addressing issues of learning. It is claimed that meaningful learning is not primarily intra-psychological, as suggested by humanistic psychologists and parts of cognitive psychology, but is an integrated part of the person’s participation in various social practices. Inspired by critical psychology and situated learning, it is suggested that in order to comprehend what people in everyday life experience as meaningful, we have to understand the concerns subjects (...) pursue across different contextual settings and the kind of conduct of everyday life they try to realise. A case example from an ongoing research project about how baker apprentices learn their trade is outlined in order to exemplify some of the theoretical considerations. Two baker apprentices, Peter and Charlotte, are presented to illustrate how they orientate their learning activities in the bakeries according to their future participation in the baking trade and in relation to the conduct of everyday life they wish to pursue. (shrink)

This paper considers the complex relation between migrants’ interest in their host country and their consequent civic or social engagement in the framework of processes of transition following the rupture of international migration (cf. Zittoun 2006). In phases of transition, migrants live processes of identity definition, sense-making of the situation and learning new knowledge and social, cognitive and practical skills. I argue that learning may be considered a precondition for a migrant’s interest and engagement with the host country (...) culture and institutions. In this connection, I use Eade’s (2007) notion of migration strategy to describe migrant profiles based on learning. My case is supported by a qualitative analysis of two paradigmatic case studies. (shrink)

Perceptual grouping is fundamental to many auditory processes. The Iambic–Trochaic Law (ITL) is a default grouping strategy, where rhythmic alternations of duration are perceived iambically (weak‐strong), while alternations of intensity are perceived trochaically (strong‐weak). Some argue that the ITL is experience dependent. For instance, French speakers follow the ITL, but not as consistently as German speakers. We hypothesized that learning about prosodic patterns, like word stress, modulates this rhythmic grouping. We tested this idea by training French adults on a (...) German‐like stress contrast. Individuals who showed better phonological learning had more ITL‐like grouping, particularly over duration cues. In a non‐phonological condition, French adults were trained using identical stimuli, but they learned to attend to acoustic variation that was not linguistic. Here, no learning effects were observed. Results thus suggest that phonological learning can modulate low‐level auditory grouping phenomena, but it is constrained by the ability of individuals to learn from short‐term training. (shrink)

Violations of expected utility theory are sometimes attributed to imprecise preferences interacting with a lack of learning opportunity in the experimental laboratory. This paper reports an experimental test of whether a learning opportunity which engenders accurate probability assessments, by enhancing understanding of the meaning of stated probability information, causes anomalous behaviour to diminish. The data show that whilst in some cases expected utility maximising behaviour increases with the learning opportunity, so too do systematic violations. Therefore, there should (...) be no presumption that anomalous behaviour under risk is transient and that discovered preferences will be appropriately described by expected utility theory. (shrink)

Machine learning researchers distinguish between reinforcement learning and supervised learning and refer to reinforcement learning systems as “agents”. This paper vindicates the claim that systems trained by reinforcement learning are agents while those trained by supervised learning are not. Systems of both kinds satisfy Dretske’s criteria for agency, because they both learn to produce outputs selectively in response to inputs. However, reinforcement learning is sensitive to the instrumental value of outputs, giving rise to (...) systems which exploit the effects of outputs on subsequent inputs to achieve good performance over episodes of interaction with their environments. Supervised learning systems, in contrast, merely learn to produce better outputs in response to individual inputs. (shrink)

This paper addresses two methodological paths in Artificial Intelligence: the paths of Babbage and anti-Cartesianism. While those researchers who have followed the latter have attempted to reverse the Cartesian dictum according to which machines cannot think in principle, Babbage’s path, which has been partially neglected, implies that the replacement of humans—and not the creation of minds—should provide the foundation of AI. In view of the examined paths, the claim that we support here is this: in line with Babbage, AI researchers (...) have recently concentrated upon the replacement of human labour, and thus upon the creation of Machine Learning systems. After presenting and analysing the paths, we characterise Machine Learning via its developments and an illustrative example. Then, we put forward an argument that shows that total replacement of human labour will not be feasible for practical and conceptual reasons despite the successful developments in recent AI systems. Our discussion finally leads to optimism and awareness: AI’s advances allow humans to dedicate themselves to higher level tasks, but these advances also require that we be vigilant about the responsibilities granted to ML-based systems. (shrink)

This essay describes my progress bringing the core ideas of economics into conversations with noneconomists about important public policy issues within my faith community, through local politics, and through interdisciplinary conversations in academia. Thinking like an economist is essential to conducting research and performing careful analysis of public policy issues. However, it can reduce the economists’ effectiveness in teaching and interacting with neighbors and political leaders. Effective pedagogy requires that faculty be present as good economists to their neighbors, their fellow (...) citizens, in daily conversations and public policy debates. Our continuing education as teachers of economics requires that we enter those conversations as committed students as well--committed to learning how our neighbors process economic facts and principles and how their insights into public policy debates might alter our own understanding. (shrink)

The research aims to identify the learning organizations and their role in achieving organizational excellence in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) workers from the Palestinian universities was selected and the recovery (...) rate was (69.2%). Statistical analysis (SPSS) program was used for analysis and processing the data. The research found the following results: there is a fair degree of approval on "cognitive dimension", there is a high approval about the importance of "organizational dimension", there is moderately consent of the importance of "Community dimension", there is a large degree of consent about the importance of axis of the "leadership excellence", there is a large degree of consent about the importance of axis of the "service-excellence", there is a fair degree approval about the importance of the axis of "cognitive excellence", and there is a moderately consent of the importance of "Organizational Excellence". The research found a group of recommendations including: the need to develop appropriate strategies for the University, employ modern technology in information systems, in addition to provide appropriate environment that achieve learning organizations, develop technological infrastructure, adopt universities for knowledge management in the academic and administrative departments because knowledge is the core of the work of these departments, create technological incubators in universities to adopt excellence academic research projects, and protected them, support them, and market them. Establishing of centers of excellence for scientific research in the university.The need for cooperation and coordination between local, Arab and international universities for the exchange of knowledge, information, and participation programs and training courses, as it provides an opportunity to develop the capabilities and skills of personnel and expertise. (shrink)

Suppose you have recently gained a disposition for recognizing a high-level kind property, like the property of being a wren. Wrens might look different to you now. According to the Phenomenal Contrast Argument, such cases of perceptual learning show that the contents of perception can include high-level kind properties such as the property of being a wren. I detail an alternative explanation for the different look of the wren: a shift in one’s attentional pattern onto other low-level properties. Philosophers (...) have alluded to this alternative before, but I provide a comprehensive account of the view, show how my account significantly differs from past claims, and offer a novel argument for the view. Finally, I show that my account puts us in a position to provide a new objection to the Phenomenal Contrast Argument. (shrink)

Perceptual experiences are not immediately responsive to reasons. You see a stick submerged in a glass of water as bent no matter how much you know about light refraction. Due to this isolation from reasons, perception is traditionally considered outside the scope of epistemic evaluability as justified or unjustified. Is perception really as independent from reasons as visual illusions make it out to be? I argue no, drawing on psychological evidence from perceptual learning. The flexibility of perceptual learning (...) is a way of responding to new epistemic reasons. The resulting perceptual experiences are epistemically evaluable as justified or unjustified. (shrink)

Perception provides us with access to the external world, but that access is shaped by our own experiential histories. Through perceptual learning, we can enhance our capacities for perceptual discrimination, categorization, and attention to salient properties. We can also encode harmful biases and stereotypes. This article reviews interdisciplinary research on perceptual learning, with an emphasis on the implications for our rational and normative theorizing. Perceptual learning raises the possibility that our inquiries into topics such as epistemic justification, (...) aesthetic criticism, and moral knowledge should include not only an examination of cognition but also of perception. (shrink)

The years 2020 and 2021 brought new challenges to teaching and learning in the institutions of tertiary education due to the global COVID-19 Pandemic. They have been the devastating years for many teachers. Innumerable difficulties in professional and personal life increased the stress - striving to survive with the least losses. Temporary measures for remote teaching/learning in spring of 2020 extended until summer of 2021 worldwide and seem unlikely to stop in the nearest future. New challenge of novel (...) online activities made teachers reconsider their teaching philosophy due to an overall lack of students engagement in spite of the usual and familiar learning procedures. The current crisis outlines the following framework to teaching philosophy: capability, reliability, inability, suitability, ingenuity, and sustainability. This article aims at researching University students attitudes to remote and traditional learning of English for Specific Purposes. A specially designed survey was administered to 180 full-time students (9 groups, 20 students in each group). Their responses were statistically processed by a means of the SPSS software to compute the Means and Standard Variations and compare the estimates of the between-group and within-group variances. Statistical processing of multiple samples reveals whether observed differences in responses occur at random, i. e. are due to chance, or they are significant, real and meaningful. The scientific analysis of computation data might allow drawing conclusions about students preferences: which mode of learning - remote or traditional - is beneficial and how much is each of them supportive. (shrink)

Philosophers have recently focused on critical, epistemological challenges that arise from the opacity of deep neural networks. One might conclude from this literature that doing good science with opaque models is exceptionally challenging, if not impossible. Yet, this is hard to square with the recent boom in optimism for AI in science alongside a flood of recent scientific breakthroughs driven by AI methods. In this paper, I argue that the disconnect between philosophical pessimism and scientific optimism is driven by a (...) failure to examine how AI is actually used in science. I show that, in order to understand the epistemic justification for AI-powered breakthroughs, philosophers must examine the role played by deep learning as part of a wider process of discovery. The philosophical distinction between the 'context of discovery' and the 'context of justification' is helpful in this regard. I demonstrate the importance of attending to this distinction with two cases drawn from the scientific literature, and show that epistemic opacity need not diminish AI's capacity to lead scientists to significant and justifiable breakthroughs. (shrink)

We are living in an era of development and innovation through research and learning. The nation that has achieved its development goals, has done through education reforms and a keen focus on strengthening its National Innovation System. In Pakistan, this role has fallen to the Higher Education Commission, commonly known as HEC. The Higher Education Commission has attempted various activities for ceaseless improvement of the nature of advanced education as per the worldwide norms and to patch up post-auxiliary instruction (...) to improve the instructive guidelines at the alumni level. Public Academy for Higher Education has been built up with the mean to plan and convey nonexclusive and need-based limit building and preparing programs in instructing and exploration for personnel just as a spotlight on scholastic administration and authority for the workforce and the board. Education Testing Council has additionally been modified to normalize passage tests for the universities of Pakistan. The study focuses on the different programs run by HEC to develop the country’s formal learning program and education sector. Since its commencement, we investigate various projects created by HEC to encourage Higher Education Institutions and build up a superior staff for this reason. (shrink)

Deep learning is currently the most prominent and widely successful method in artificial intelligence. Despite having played an active role in earlier artificial intelligence and neural network research, philosophers have been largely silent on this technology so far. This is remarkable, given that deep learning neural networks have blown past predicted upper limits on artificial intelligence performance—recognizing complex objects in natural photographs and defeating world champions in strategy games as complex as Go and chess—yet there remains no universally (...) accepted explanation as to why they work so well. This article provides an introduction to these networks as well as an opinionated guidebook on the philosophical significance of their structure and achievements. It argues that deep learning neural networks differ importantly in their structure and mathematical properties from the shallower neural networks that were the subject of so much philosophical reflection in the 1980s and 1990s. The article then explores several different explanations for their success and ends by proposing three areas of inquiry that would benefit from future engagement by philosophers of mind and science. (shrink)

The research question addressed in this paper is: How do the activities of writing mediate knowledge of writing, disciplinary knowledge, and professional knowledge as intertwined sites of learning? To conceptualise the role that writing can take in these complex processes, we apply an analytical framework comprising two core concepts; mediation and learning trajectories. We draw on an empirical study from the context of initial teacher education in Norway. From our analysis, we identify three qualities of writing as important. (...) First, the writing process should in- clude responding to and sharing drafts. Other important qualities include high teacher expectations and continuous reflection. From the perspective adopted here, learning is understood to be distributed and situated. In particular, in situated cultural contexts, collaborative writing can become a significant mediational tool for learning. Initial teacher education seeks to prepare the student teacher for a highly complex professional competency, developing both professionally and in individual subjects. To do so, students must transform social structures and the tools embedded in practices into psychological tools. We contend that writing is one significant tool in moving through complex trajectories of learning towards becoming professional teachers. (shrink)

Agnostic analyses of unique video material from a Mother and Baby Unit were carried out to investigate the usefulness of such analyses to the unit. The goal was to improve outcomes: the health of mothers and their babies. The method was to implement a learning machine that becomes more useful over time and over task. A feasible set-up is here described, with the purpose of producing intelligible and useful results to healthcare professionals at the unit by means of a (...) vision processing pipeline, grouped together with multi-modal capabilities of handling annotations and audio. Algorithmic bias turned out to be an obstacle that could only partly be handled by modern pipelines for automated feature analysis. The professional use of complex quantitative scoring for various mental health-related assessments further complicated the automation of laborious tasks. Activities during the MBU stay had previously been shown to decrease psychiatric symptoms across diagnostic groups. The implementation and first set of experiments on a learning machine for the unit produced the first steps toward explaining why this is so, in turn enabling decision support to staff about what to do more and what to do less of. (shrink)

Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The (...) schema organizes the objects into categories and specifies the causal powers and characteristic features of these categories and the characteristic causal interactions between categories. A schema of this kind allows causal models for subsequent objects to be rapidly learned, and we explore this accelerated learning in four experiments. Our results confirm that humans learn rapidly about the causal powers of novel objects, and we show that our framework accounts better for our data than alternative models of causal learning. (shrink)

Learning to recognize visual objects from examples requires the ability to find meaningful patterns in spaces of very high dimensionality. We present a method for dimensionality reduction which effectively biases the learning system by combining multiple constraints via the use of class labels. The use of extensive class labels steers the resulting lowdimensional representation to become invariant to those directions of variation in the input space that are irrelevant to classification; this is done merely by making class labels (...) independent of these directions. We also show that prior knowledge of the proper dimensionality of the target representation can be imposed by training a multi-layer bottleneck network. Computational experiments involving non-trivial categorization of parameterized fractal images and of human faces indicate that the low-dimensional representation extracted by our method leads to improved generalization in the learned tasks and is likely to preserve the topology of the original space. (shrink)

Much of our know-how is acquired through practice: we learn how to cook by cooking, how to write by writing, and how to dance by dancing. As Aristotle argues, however, this kind of learning is puzzling, since engaging in it seems to require possession of the very knowledge one seeks to obtain. After showing how a version of the puzzle arises from a set of attractive principles, I argue that the best solution is to hold that knowledge-how comes in (...) degrees, and through practice a person gradually learns how to do something. However, the two standard accounts of know-how in the literature, intellectualism and anti-intellectualism, cannot properly account for the distinctive way in which know-how is gradually acquired by practice, a process in which conceptual representations and practical abilities are intimately interwoven. Drawing on Gareth Evans's work, I outline an account that may do so, and use this account to distinguish between two forms of learning to explain why skill generally cannot be learnt through testimony, and requires practice. (shrink)

__Learning for Careers_ provides a comprehensive account of the Pathways to Prosperity Network, a national initiative focused on helping more young people successfully complete high school, attain a first postsecondary credential with value in the labor market, and get started on a career without foreclosing the opportunity for further education._ It takes as its starting point the influential 2011 _Pathways to Prosperity_ report, which challenged the prevailing idea that the core mission of high schools was to prepare all students for (...) college. In response, the Pathways Network was founded in 2012 to promote cooperative arrangements between educational and business institutions in order to fashion pathways for young people to acquire twenty-first-century skills and achieve professional success. This book traces the evolution of the Pathways Network over the past five years, focusing on the efforts of a diverse set of states and regions to build systems that span high school and the first two years of postsecondary education. States such as Delaware and Tennessee have been highly effective in establishing systems designed to equip students with credentials valued in the contemporary labor market. At the same time, the authors acknowledge the technical, political, and cultural challenges in redesigning career-focused education to produce satisfactory outcomes for young people throughout the country. _Learning for Careers_ offers a way forward for the millions of young people and employers that face a rapidly evolving and ever more competitive globalized workplace. This book will be essential reading for all who have a stake in educational and economic opportunity in the United States. (shrink)

Despite the growth of knowledge on teacher emotional tensions and identities, little research has explored how emotional tensions shape teacher identity development within teacher education courses. This study explored the contributions of a professional learning community (PLC) structured around sharing and discussing emotional tensions to eight Iranian English teachers’ identity (re)construction. In line with our theoretically-grounded proposed model of PLC – as settings in which individuals share ideas to expand their learning, data were collected before, during, and after (...) the PLC using semi-structured interviews and reflective journals over a four-month time span. Data analyses revealed that before the PLC, the teachers had problems in developing the identity of agentic teachers and in their interpersonal relationships with colleagues. During the PLC, they were able to develop collegial identities that facilitated embracing the course contents. After the course, the teachers experienced enhanced collaboration and agency-induced autonomy that enabled them to effectively manage emotional tensions. Collectively, the PLC helped the teachers in agentically exercising praxis in relation to their colleagues, practices, and relationships with students. Based on the findings, we provide implications for teachers to use their current potential to form PLCs and for teacher educators to systematize PLCs at the institutional level. (shrink)

In this paper, I employ the pioneering works of Nussbaum, Sen, Saito, and Walker, in conjunction with the U.S. tradition of academic freedom, to outline a capability-centered vision of undergraduate education. Pace Nussbaum and Walker, I propose a short list of learning capabilities to which every undergraduate student should be entitled. This working definition of undergraduate education offers a starting point for discussion and experimentation. I employ it here to engage the current controversy in U.S. colleges and universities over (...) the nature, value, and legitimacy of undergraduate students’ academic freedoms. In contrast to the anti-indoctrination emphasis of David Horowitz’s Academic Bill of Rights, I argue that students’ academic freedoms can be more effectively secured through the articulation of “essential freedoms for liberal learning” whose principal focus is not the behavior or political affiliations of teachers but the intellectual needs and circumstances of students. (shrink)

The paper develops a semi-formal model of learning which modifies the traditional paradigm of artificial neural networks, implementing deep learning by means of a key insight borrowed from the works of Marvin Minsky: the so-called Principle of Non-Compromise. The principle provides a learning mechanism which states that conflicts in the processing of data to be integrated are a mark of unreliability or irrelevance; hence, lower-level conflicts should lead to higher-level weight-adjustments. This internal mechanism augments the external mechanism (...) of weight adjustment by back-propagation, which is typical for the standard models of machine learning. The text is structured as follows: (§1) opens the discussion by providing an informal overview of real-world decision-making and learning; (§2) sketches a typology of decision architectures: the individualistic approach of classical decision theory, the general aggregation mechanism of social choice theory, the local aggregation mechanism of agent-based modeling, and the intermediate hierarchical model of Marvin Minsky's “Society of Mind”; (§3) sketches the general outline of ANIMA – a new model of decision-making and learning that borrows insights from Minsky's informal exposition; (§4) is the bulk of the paper; it provides a discussion of a toy exemplification of ANIMA which lets us see the Principle of Non-Compromise at work; (§5) lists some possible scenarios for the evolution of a model of this kind; (§6) is the closing section; it discusses some important differences between the way ANIMA was construed here and the typical formal rendering of learning by means of artificial neural networks and deep learning. (shrink)

The cognitive penetrability of perceptual experiences has been a long-standing topic of disagreement among philosophers and psychologists. Although the notion of cognitive penetrability itself has also been under dispute, the debate has mainly focused on the cases in which cognitive states allegedly penetrate perceptual experiences. This paper concerns the plausibility of two prominent cases. The first one originates from Susanna Siegel’s claim that perceptual experiences can represent natural kind properties. If this is true, then the concepts we possess change the (...) way things appear to us. The second candidate for cognitive penetration is Fiona Macpherson’s claim that, in addition to concepts, our beliefs can penetrate perceptual experiences. It is argued that neither candidate is a case of cognitive penetration. In doing so, I provide an explanation to both that is based on perceptual learning, a non-cognitive phenomenon where relatively slow and long-lasting modifications to an organism’s perceptual system bring about changes in perception. This explanation is theoretically more plausible and remains closer to the empirical data than the explanations based on cognitive penetration. (shrink)

Learning to love the reviewer -/- Issue: 43(4) November 2017. Viewpoint Page 83 -/- Quan Hoang Vuong Western University Hanoi, Centre for Interdisciplinary Social Research, Hanoi, Vietnam.

Challenges conventional wisdom and presents the most up-to-date studies to define, quantify and test the predictions of the main models of implicit learning.

Learning Love from a Tiger explores the vibrancy and variety of humans' sacred encounters with the natural world, gathering a range of stories culled from Christian, Muslim, Hindu, Mayan, Himalayan, Buddhist, and Chinese shamanic traditions. Readers will delight in tales of house cats who teach monks how to meditate, rivers that grant salvation, shamans who shape-shift into jaguars, crickets who perform Catholic mass, and many others. More than a collection of wonderful stories, this book introduces important concepts and approaches (...) that underlie much recent work in environmental ethics, religion, and ecology. Capper's light touch prompts readers to engage their own views of humanity's place in the natural world and in particular question longstanding assumptions of human superiority"--Provided by publisher. (shrink)

Conditional learning, where agents learn a conditional sentence ‘If A, then B,’ is difficult to incorporate into existing Bayesian models of learning. This is because conditional learning is not uniform: in some cases, learning a conditional requires decreasing the probability of the antecedent, while in other cases, the antecedent probability stays constant or increases. I argue that how one learns a conditional depends on the causal structure relating the antecedent and the consequent, leading to a causal (...) model of conditional learning. This model extends traditional Bayesian learning by incorporating causal models into agents’ epistemic states. On this theory, conditional learning proceeds in two steps. First, an agent learns a new causal model with the appropriate relationship between the antecedent and the consequent. Then, the agent narrows down the set of possible worlds to include only those which make the conditional proposition true. This model of learning can incorporate both standard cases of Bayesian learning and the non-uniform learning required to learn conditional information. (shrink)

_Learning to Teach Religious Education in the Secondary School_ draws together insights from current educational theory and the best contemporary classroom teaching and learning, and suggests tasks, activities, and further reading designed to enhance the quality of initial school experience for the student teacher. It aims to support teachers in developing levels of religious and theological literacy, both of individual pupils and the society as a whole. Practising teachers and students will appreciate this comprehensive and accessible introduction to the (...) craft of teaching Religious Education in the secondary school. (shrink)