A hitherto unexamined problem for the ‘‘Kantian ideal’’ that one should always treat patients as ends in themselves, and never only as a means to other ends, is explored in this paper. The problem consists of a prima facie conflict between this Kantian ideal and the reality of medical practice. This conflict arises because, at least presently, medical practitioners can only acquire certain skills and abilities by practising on live, human patients, and given the inevitability and ubiquity of learning (...) curves, this learning requires some patients to be treated only as a means to this end. A number of ways of attempting to establish the compatibility of the Kantian Ideal with the reality of medical practice are considered. Each attempt is found to be unsuccessful. Accordingly, until a way is found to reconcile them, we conclude that the Kantian ideal is inconsistent with the reality of medical practice. (shrink)

Beyond the Learning Curve reviews and considers the psychology of skill acquisition. In so doing the authors propose a whole new theory of mental function - demonstrating that the mind is subject to the same natural laws as the physical world. Accessibly written, 'Beyond the learning curve' is a thought provoking and challenging new text for students and researchers in the cognitive sciences.

In Language and the Learning Curve, a leading researcher in the field offers a radical new view of language development, unusual in its combination of Chomskian linguistics and learning theory. Stimulating and accessible, it is an important new work that challenges many of our usual assumptions about syntactic development.

For years now, learning has been at the heart of research within cognitive psychology. How do we acquire new knowledge and new skills? Are the principles underlying skill acquisition unique to learning, or similar to those underlying other behaviours? Is the mental system essentially modular, or is the mental system a simple product of experience, a product that, inevitably, reflects the shape of the external world with all of its specialisms and similarities? This new book takes the view (...) that learning is a major influence on the nature of the processes and representations that fill our minds. Throughout, the authors review and consider the areas of skill acquisition and lexical representation to illustrate the effects that practice can have on cognitive processes. They also draw parallels between theories in physical and biological domains to propose not only a new theory of mental function but also demonstrate that the mind is essentially subject to the same natural laws as the physical world. In so doing Speelman and Kirsner present a new perspective on psychology - one that identifies universal principles underlying all behaviours and one which contrasts markedly from our current focus on highly specific behaviours. Accessibly written, Beyond the Learning Curve is a thought provoking and challenging new text for students and researchers in the cognitive sciences. (shrink)

This article explores the limits of introductory social justice education and the ways in which a social foundations course could expand and deepen the social justice lens of current and future educators. The authors, members of an introductory graduate-level Social Foundations course, discuss the limitations they realized in their previous social justice education courses, and the importance of courses that further student's understandings of the ever-evolving ways people enact and experience identity, power, and privilege. The authors identify three main pedagogical (...) and theoretical elements that advanced their social justice knowledge: examining theories for their potential to uncover or obscure lived experience; unpacking binary constructions of identity; and exploring the limits and possibilities of intersectional thinking. This article offers implications and suggestions for educators who seek to challenge and expand the social justice knowledge of future educators and administrators. (shrink)

The ‘Kantian ideal’ is often misunderstood as invoking individual autonomy rather than rational self-legislation. Le Morvan and Stock’s otherwise insightful discussion of ‘Medical learning curves and the Kantian ideal’, for example, draws the mistaken inference that that ideal is inconsistent with the realities of medical practice. But it is not. Rationally to be a patient entails accepting its necessary conditions, one of which is the ineliminable existence of medical learning curves. Their rational necessity, therefore, offers no (...) grounds against a Kantian understanding of how morality might function in the practgice of medicine. (shrink)

We analyze naturally occurring datasets from student use of educational technologies to explore a long-standing question of the scope of transfer of learning. We contrast a faculty theory of broad transfer with a component theory of more constrained transfer. To test these theories, we develop statistical models of them. These models use latent variables to represent mental functions that are changed while learning to cause a reduction in error rates for new tasks. Strong versions of these models provide (...) a common explanation for the variance in task difficulty and transfer. Weak versions decouple difficulty and transfer explanations by describing task difficulty with parameters for each unique task. We evaluate these models in terms of both their prediction accuracy on held-out data and their power in explaining task difficulty and learning transfer. In comparisons across eight datasets, we find that the component models provide both better predictions and better explanations than the faculty models. Weak model variations tend to improve generalization across students, but hurt generalization across items and make a sacrifice to explanatory power. More generally, the approach could be used to identify malleable components of cognitive functions, such as spatial reasoning or executive functions. (shrink)

This article is a review of the 2010 book Collateral Damage by Dan Walter.

In a recent paper published in the Journal of Medical Ethics, Le Morvan and Stock claim that the kantian ideal of treating people always as ends in themselves and never merely as a means is in direct and insurmountable conflict with the current medical practice of allowing practitioners at the bottom of their “learning curve” to “practise their skills” on patients. In this response, I take up the challenge they issue is and try to reconcile this conflict. The kantian (...) ideal offered in the paper is an incomplete characterisation of Kant’s moral philosophy, and the formula of humanity is considered in isolation without taking into account other salient kantian principles. I also suggest that their argument based on “necessary for the patient” assumes too narrow a reading of “necessary”. This reply is intended as an extension to, rather than a criticism of, their work. (shrink)

An intelligent model of the incremental capacity curve of an automotive lithium-ferrophosphate battery is presented. The relative heights of the two major peaks of the IC curve can be acquired from high-current discharges, thus enabling the state of health estimation of the battery while the vehicle is being operated and in certain cases, aging mechanisms can be suggested. Our model has been validated using a large dataset representing different degradation scenarios, obtained from a recently available open-source database.

According to general relativity, we live in a four-dimensional curved universe. Since the human mind cannot visualize those four dimensions, a popular analogy compares the universe to a two-dimensional rubber sheet distorted by massive objects. This analogy is often used when teaching GR to upper secondary and undergraduate physics students. However, physicists and physics educators criticize the analogy for being inaccurate and for introducing conceptual conflicts. Addressing these criticisms, we analyze the rubber sheet analogy through systematic metaphor analysis of textbooks (...) and research literature, and present an empirical analysis of upper secondary school students’ use and understanding of the analogy. Taking a theoretical perspective of embodied cognition allows us to account for the relationship between the experiential and sensory aspects of the metaphor in relation to the abstract nature of spacetime. We employ methods of metaphor and thematic analysis to study written accounts of small groups of 97 students who worked with a collaborative online learning environment as part of their regular physics lessons in five classes in Norway. Students generated conceptual metaphors found in the literature as well as novel ones that led to different conceptions of gravity than those held by experts in the field. Even though most students showed awareness of some limitations of the analogy, we observed a conflict between students’ embodied understanding of gravity and the abstract description of GR. This conflict might add to the common perception of GR being counterintuitive. In making explicit strengths and weaknesses of the rubber sheet analogy and learners’ conceptual difficulties, our results offer guidance for teaching GR. More generally, these findings contribute to the epistemological implications of employing specific scientific metaphors in classrooms. (shrink)

I discuss the ubiquity of power law distributions in language organisation (and elsewhere), and argue against Miller’s (The mating mind: How sexual choice shaped the evolution of human nature, William Heinemann, London, 2000) argument that large vocabulary size is a consequence of sexual selection. Instead I argue that power law distributions are evidence that languages are best modelled as dynamical systems but raise some issues for models of iterated language learning.

The notion of optimality is often invoked informally in the literature on metacognitive control. We provide a precise formulation of the optimization problem and show that optimal time allocation strategies depend critically on certain characteristics of the learning environment, such as the extent of time pressure, and the nature of the uptake function. When the learning curve is concave, optimality requires that items at lower levels of initial competence be allocated greater time. On the other hand, with logistic (...) learning curves, optimal allocations vary with time availability in complex and surprising ways. Hence there are conditions under which optimal strategies will be relatively easy to uncover, and others in which suboptimal time allocation might be expected. The model can therefore be used to address the question of whether and when learners should be able to exercise good metacognitive control in practice. (shrink)

While issues of efficacy and specificity are crucial for the future of neurofeedback training, there may be alternative designs and control analyses to circumvent the methodological and ethical problems associated with double-blind placebo studies. Surprisingly, most NF studies do not report the most immediate result of their NF training, i.e. whether or not children with ADHD gain control over their brain activity during the training sessions. For the investigation of specificity, however, it seems essential to analyze the learning and (...) adaptation processes that take place in the course of the training and to relate improvements in self-regulated brain activity across training sessions to behavioral, neuropsychological and electrophysiological outcomes. To this aim, a review of studies on neurofeedback training with ADHD patients, which include the analysis of learning across training sessions or relate training performance to outcome, is presented. Methods on how to evaluate and quantify learning of EEG regulation over time are discussed. “Non-learning” has been reported in a small number of ADHD-studies, but has not been a focus of general methodological discussion so far. For this reason, selected results from the brain-computer interface (BCI) research on the so-called “brain-computer illiteracy”, the inability to gain control over one’s brain activity, are also included. It is concluded that in the discussion on specificity, more attention should be devoted to the analysis of EEG regulation performance in the course of the training and its impact on clinical outcome. It is necessary to improve the knowledge on characteristic cross-session and within-session learning trajectories in ADHD and to provide the best conditions for learning. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Learning to BreatheFive Fragments Against RacismB. Venkat Mani (bio)For Dr. JLW, for all Black academics and students1. Air HungerI know you, Derek Chauvin. You may think that we first met on May 25, 2020, in Minneapolis. I was called George Perry Floyd. For you, I was just another Black man, a potential criminal. For me, you were not a police officer, but the knee that stands for racism. (...) You kneeled on my windpipe for 9 minutes and 29 seconds. Those were neither my first nor my last memories.You may choose not to recognize me, as you always have. But I do. I recognize every bone, muscle, tendon, pointy curve of the cap, every contour of your strong, heavy, determined, calculating, conniving knee that presses on my windpipe with a false sense of racist superiority. 9 minutes and 29 seconds. As often as you can.We have a history. You have never missed the opportunity of kneeling on my windpipe. You hauled me into your slave ships from various African ports along the Atlantic, then you kneeled on my windpipe all over your cotton and tobacco plantations in the Americas. We met again on schooners from Indian shores journeying across the Indian and Pacific oceans. With slavery banned in the British empire, you turned me into an indentured laborer. You made me put my thumb imprint on a document you created, in a script I could not read, of a language I could not speak. Then you threw me thousands of miles away in Mauritius, Fiji, and numerous Caribbean islands, pressing on my windpipe on sugarcane plantations. My wife, children, sisters, mothers, aunts, brothers, uncles, nephews, nieces, grandparents, great grandparents, we all have lived through those fatal 9 minutes and 29 seconds: on water and land. Repeatedly. Consistently. Incessantly.You want specific dates? April 8, 1857, Barrackpore, Northern India. My name was Mangal Pandey, you called me a Sepoy. You hanged me for standing up against my subjugation by your British East India Company. Against your rule over my land and my people. With your many titles [End Page 41] and names: Major-General Sir Henry Havelock, Lieutenant-General Sir Colin Campbell, Brigadier-General Charles Windham, you rampaged through the streets of Delhi, Meerut, Lucknow, killing anyone in your way so I could be a jewel in Victoria's crown. January 29, 1863, Bear River, Idaho. I was one among the Shoshone of Bia Ogoi, you were Colonel Patrick Connor. You came to us on a frigid morning and killed us by the hundreds. November 15, 1884, the Congo Conference, Berlin. You were called Chancellor Otto von Bismarck and were acting at the behest of sharecropping interests of King Leopold the Second. Your name for me was a "savage." You set up a society to civilize me while you plundered my bounty. You started drawing lines through land, rivers, mountains, deserts. For you, it was the Scramble for Africa. For me, bloody murder. You knelt on my windpipe, smoking a pipe with tobacco my people had grown. April 13, 1919, Jallianwala Bagh, Amritsar. You were called Brigadier General Reginald Edward Harry Dyer. For you, I was just a troublemaking native disrupting the civilized business of the Empire. You surrounded our peaceful gathering in Amritsar and opened fire. Your Nobel Laureate Rudyard Kipling claimed that "you did your duty as you saw fit." By killing us in thousands until the bullets ran out. Rikki Tikki Tavi. May 31, 1921, Tulsa, Oklahoma. Inspired by Jim Crow, your knees came running to us in mobs to massacre us. October 19, 1926, Imperial Conference, London. Your name was Field Marshall the Right Honorable Jan Christian Smuts. For you, I was one among the many "colored" subjects from the Cape Colony. You spoke vehemently against mixing my people with your people. Eloquently, I was told, in favor of apartheid.You know very well, Chauvin, that our acquaintance neither begins in 1857 nor ends in 1926. I could take you on a grand tour of the world and give you all the dates when you appeared in different forms. Your self-induced conviction of racial supremacy over me remained the same... (shrink)

The development and deployment of artificial intelligence (AI) is and will profoundly reshape human society, the culture and the composition of civilisations which make up human kind. All technological triggers tend to drive a hype curve which over time is realised by an output which is often unexpected, taking both pessimistic and optimistic perspectives and actions of drivers, contributors and enablers on a journey where the ultimate destination may be unclear. In this paper we hypothesise that this journey is not (...) dissimilar to the personal journey described by the Kubler-Ross change curve and illustrate this by commentary on the potential of AI for drug discovery, development and healthcare and as an enabler for deep space exploration and colonisation. Recent advances in the call for regulation to ensure development of safety measures associated with machine-based learning are presented which, together with regulation of the rapidly emerging digital after-life industry, should provide a platform for realising the full potential benefit of AI for the human species. (shrink)

The hypothesis was tested that transfer and facilitation of learning in early syntactic development does not rely on semantic analogy among the items. The study focused on the verb-indirect object (VI) construction. Longitudinal naturalistic speech corpora of 14 Hebrew-speaking children (1;04–2;08) were analyzed, 9 females and 5 males, White and predominantly middle class. There was facilitation of learning among the first 10 verbs in the VI pattern, as evidenced by the accelerating growth curves. However, there was much (...) semantic variability among the 10 indirect objects, and most had no semantically similar antecedents in the same construction. The results indicate that facilitation of learning of early syntax is most probably not mediated by semantic similarity. (shrink)

A U-shaped curve in a cognitive-developmental trajectory refers to a three-step process: good performance followed by bad performance followed by good performance once again. U-shaped curves have been observed in a wide variety of cognitive-developmental and learning contexts. U-shaped learning seems to contradict the idea that learning is a monotonic, cumulative process and thus constitutes a challenge for competing theories of cognitive development and learning. U-shaped behavior in language learning (in particular in learning (...) English past tense) has become a central topic in the Cognitive Science debate about learning models. Antagonist models (e.g., connectionism versus nativism) are often judged on their ability of modeling or accounting for U-shaped behavior. The prior literature is mostly occupied with explaining how U-shaped behavior occurs. Instead, we are interested in the necessity of this kind of apparently inefficient strategy. We present and discuss a body of results in the abstract mathematical setting of (extensions of) Gold-style computational learning theory addressing a mathematically precise version of the following question: Are there learning tasks that require U-shaped behavior? All notions considered are learning in the limit from positive data. We present results about the necessity of U-shaped learning in classical models of learning as well as in models with bounds on the memory of the learner. The pattern emerges that, for parameterized, cognitively relevant learning criteria, beyond very few initial parameter values, U-shapes are necessary for full learning power! We discuss the possible relevance of the above results for the Cognitive Science debate about learning models as well as directions for future research. (shrink)

Supporters of eliminative connectionism have argued for a pattern association-based explanation of language learning and language processing. They deny that explicit rules and symbolic representations play any role in language processing and cognition in general. Their argument is based to a large extent on two artificial neural network (ANN) models that are claimed to be able to learn the past tenses of English verbs (Rumelhart & McClelland, 1986, Parallel distributed processing, Vol. 2, Cambridge, MA: MIT Press; MacWhinney & Leinbach, (...) 1991, Cognition, 40, 121-157). In this article we critically review Rumelhart and McClelland's as well as MacWhinney and Leinbach's ANN models and conclude that they do not succeed in the assigned task of learning the past tenses of English verbs. In order to answer their challenge to the symbolic processing approach, we present our symbolic pattern associator (SPA)-a general-purpose pattern associator that can learn to associate arbitrary discrete patterns. We carried out several experiments with the SPA using the same set of verbs that was used in MacWhinney and Leinbach's simulation with more realistic training and testing procedures. The SPA outperformed the connectionist models by a wide margin in the accuracy of learning, and successful inductive generalizations to unseen verbs. Our SPA has very natural and psychologically realistic explanations to many psychological effects such as U-shaped learning curve, and is much closer to human subjects in predicting past tense of the pseudo-verbs. In contrast to ANNs, whose internal representations are entirely opaque, the SPA can represent the acquired knowledge in the form of production rules that allow for further higher-level processing and integration, resulting in linguistically realistic associative templates for irregular verbs and production rules for regular verbs. In the light of these findings, we conclude that eliminative connectionists' vision of cognition as simple pattern association and pattern recognition without symbolic representation is inadequate. Pattern association as such does not imply rule-less or cue-based models of language acquisition or of human learning in general. (shrink)

Learning from demonstration is one of the promising approaches for fast robot programming. Most learning systems learn both movements and stiffness profiles from human demonstrations. However, they rarely consider the unknown environment interaction. In this paper, a robot human-like learning framework is proposed, where it can learn human skills through demonstration and complete the interaction task with an unknown environment. Firstly, the desired trajectory was generated by dynamic movement primitive based on human demonstration. Then, an adaptive optimal (...) admittance control scheme was employed to interact with environments with the reference adaptation method. Finally, the experimental study was conducted, and the effectiveness of the framework proposed in this paper was verified via a group of curved surface wiping experiments on a balloon with unknown model parameters. (shrink)

Two classic learning situations are critically reviewed and interpreted from a synergetic point of view: human learning of complex skills, and animal discrimination learning. Both show typical characteristics of nonlinear phase transitions: instability, fluctuations, critical slowing down and reorganisation. Plateaus in the acquisition curves of complex skills can be viewed as phases of arrested progress in which a reorganisation of simple skills is necessary before their integration into complex units is possible. Fluctuations and critical slowing down (...) are expressed in instances of "vicarious trial-and-error," which describe the oscillating behavior of rats at a choice point that is shown only just before discrimination learning is completed. It is concluded that education might pay more attention to the role of individual learning rhythms. (shrink)

This study explored pedestrians’ understanding of Fully Autonomous Vehicles intention to stop and what influences pedestrians’ decision to cross the road over time, i.e., learnability. Twenty participants saw fixed simulated urban road crossing scenes with a single FAV on the road as if they were pedestrians intending to cross. Scenes differed from one another in the FAV’s, distance from the crossing place, its physical size, and external Human-Machine Interfaces message by background color, message type, and presentation modality. Eye-tracking data and (...) decision measurements were collected. Results revealed that pedestrians tend to look at the e-HMI before making their decision. However, they did not necessarily decide according to the e-HMIs’ color or message type. Moreover, when they complied with the e-HMI proposition, they tended to hesitate before making the decision. Overall, a learning effect over time was observed in all conditions regardless of e- HMI features and crossing context. Findings suggest that pedestrians’ decision making depends on a combination of the e-HMI implementation and the car distance. Moreover, since the learning curve exists in all conditions and has the same proportion, it is critical to design an interaction that would encourage higher probability of compatible decisions from the first phase. However, to extend all these findings, it is necessary to further examine dynamic situations. (shrink)

Deep learning techniques, which use a massive technology known as convolutional neural networks, have shown excellent results in a variety of areas, including image processing and interpretation. However, as the depth of these networks grows, so does the demand for a large amount of labeled data required to train these networks. In particular, the medical field suffers from a lack of images because the procedure for obtaining labeled medical images in the healthcare field is difficult, expensive, and requires specialized (...) expertise to add labels to images. Moreover, the process may be prone to errors and time-consuming. Current research has revealed transfer learning as a viable solution to this problem. Transfer learning allows us to transfer knowledge gained from a previous process to improve and tackle a new problem. This study aims to conduct a comprehensive survey of recent studies that dealt with solving this problem and the most important metrics used to evaluate these methods. In addition, this study identifies problems in transfer learning techniques and highlights the problems of the medical dataset and potential problems that can be addressed in future research. According to our review, many researchers use pre-trained models on the Imagenet dataset in many applications such as skin cancer, breast cancer, and diabetic retinopathy classification tasks. These techniques require further investigation of these models, due to training them on natural, non-medical images. In addition, many researchers use data augmentation techniques to expand their dataset and avoid overfitting. However, not enough studies have shown the effect of performance with or without data augmentation. Accuracy, recall, precision, F1 score, receiver operator characteristic curve, and area under the curve were the most widely used measures in these studies. Furthermore, we identified problems in the datasets for melanoma and breast cancer and suggested corresponding solutions. (shrink)

With the increasing prevalence of Internet usage, Internet-Delivered Psychological Treatment (IDPT) has become a valuable tool to develop improved treatments of mental disorders. IDPT becomes complicated and labor intensive because of overlapping emotion in mental health. To create a usable learning application for IDPT requires diverse labeled datasets containing an adequate set of linguistic properties to extract word representations and segmentations of emotions. In medical applications, it is challenging to successfully refine such datasets since emotion-aware labeling is time consuming. (...) Other known issues include vocabulary sizes per class, data source, method of creation, and baseline for the human performance level. This paper focuses on the application of personalized mental health interventions using Natural Language Processing (NLP) and attention-based in-depth entropy active learning. The objective of this research is to increase the trainable instances using a semantic clustering mechanism. For this purpose, we propose a method based on synonym expansion by semantic vectors. Semantic vectors based on semantic information derived from the context in which it appears are clustered. The resulting similarity metrics help to select the subset of unlabeled text by using semantic information. The proposed method separates unlabeled text and includes it in the next active learning mechanism cycle. Our method updates model training by using the new training points. The cycle continues until it reaches an optimal solution, and it converts all the unlabeled text into the training set. Our in-depth experimental results show that the synonym expansion semantic vectors help enhance training accuracy while not harming the results. The bidirectional Long Short-Term Memory (LSTM) architecture with an attention mechanism achieved 0.85 Receiver Operating Characteristic (ROC curve) on the blind test set. The learned embedding is then used to visualize the activated word's contribution to each symptom and find the psychiatrist's qualitative agreement. Our method improves the detection rate of depression symptoms from online forum text using the unlabeled forum texts. (shrink)

Seasonal outbreaks have several different periods that occur primarily during winter in temperate regions, while influenza may occur throughout the year in tropical regions, triggering outbreaks more irregularly. Similarly, dengue occurs in the star of the rainy season in early May and reaches its peak in late June. Dengue and flu brought an impact on various countries in the years 2017–2019 and streaming Twitter data reveals the status of dengue and flu outbreaks in the most affected regions. This research work (...) presents that Social Media Analysis can be used as a detector of the epidemic outbreak and to understand the sentiment of social media users regarding various diseases. Providing awareness about seasonal outbreaks through SMA is an effective approach for researchers and healthcare responders to detect the early outbreaks. The proposed model aims to find the sentiment about the disease in tweets, and the seasonal outbreaks-related tweets are classified into two classes as disease positive and disease negative. This work proposes a machine-learning-based approach to detect dengue and flu outbreaks in social media platform Twitter, using four machine learning algorithms: Random Forest, K-Nearest Neighbor, Support Vector Machine, and Decision Tree, with the help of Term Frequency and Inverse Document Frequency. For experimental analysis, two datasets are analyzed individually. The experimental results show that the RF classifier has outperformed the comparison models in terms of improved accuracy, precision, recall, F1-measure, and Receiver Operating Characteristic curve. The proposed work offers favorable performance with total precision, accuracy, recall, and F1-measure ranging from 84% to 88% for conventional machine learning techniques. (shrink)

In economics there are several complex learning themes and tasks connected with them difficult for deeper understanding of the learning subject. These are the reasons originating serious learning problems for students in the form of Virtual Environment because deeper understanding requires high level mathematical skills. Actually the most important feature for discerning this part of economics is the set of qualitative shapes emerging in discrete dynamic systems when they are undergoing iterations and/or experimentation with parameters and initial (...) coordinates of variables. Among such shapes there are: - trajectories in evolving time; - trajectories in R2 of two variables; - cobweb portraits; - one control parameter bifurcation with first and/or with second variables; - two control parameters bifurcation in R2 ; - cycles; - basin of attraction of two variables; - one Lyapunov’s exponent against some of control parameters; - Lyapunov’s exponents with two control parameters in R2; - absorbing area with possibility to create critical curves and/or attractors. The hope is that products of computational intelligence may help them solve such problems. Naturally, the meant complex economic problems and tasks have discrete, qualitative and nonlinear nature resulting in increased level of difficulties. So with the term used in the head of this paper one has to understand narrowly: “qualitative nonlinear computational economics”. For better understanding the very nature of the problem we are using as appropriate example actual simulation of the model of new ICT products monopolies in virtual laboratory built in the routines setting dominantly in the software iDMC. (shrink)