Experts from wine tasters to radiologists to bird watchers have all undergone perceptual learning-long-term changes in perception that result from practice or experience. Philosophers have been discussing such cases for centuries, from the 14th-century Indian philosopher Vedanta Desika to the 18th-century Scottish philosopher Thomas Reid, and into contemporary times. -/- This book uses recent evidence from psychology and neuroscience to show that perceptual learning is genuinely perceptual, rather than post-perceptual. It also offers a taxonomy for classifying cases in (...) the philosophical literature. In some cases, perceptual learning involves changes in how one attends; in other cases, it involves a learned ability to differentiate two properties, or to perceive two properties as unified. Connolly uses this taxonomy to rethink several domains of perception in terms of perceptual learning, including multisensory perception, color perception, and speech perception. -/- As a whole, the book offers a theory of the function of perceptual learning. Perceptual learning embeds into our quick perceptual systems what would be a slower task were it to be done in a controlled, cognitive manner. A novice wine taster drinking a Cabernet Sauvignon might have to think about its features first and then infer the type of wine, while an expert can identify it immediately. This learned ability to immediately identify the wine enables the expert to think about other things like the vineyard or the vintage of the wine. More generally, perceptual learning serves to free up cognitive resources for other tasks. This book offers a comprehensive empirically-informed account, and explores the nature, scope, and theoretical implications of perceptual learning. (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)

Two great problems of learning confront humanity: learning about the nature of the universe and our place in it, and learning how to become civilized. The first problem was solved, in essence, in the 17th century, with the creation of modern science. But the second problem has not yet been solved. Solving the first problem without also solving the second puts us in a situation of great danger. All our current global problems have arisen as a result. (...) What we need to do, in response to this unprecedented crisis, is learn from our solution to the first problem how to solve the second. This was the basic idea of the 18th century Enlightenment. Unfortunately, in carrying out this programme, the Enlightenment made three blunders, and it is this defective version of the Enlightenment programme that we have institutionalized in 20th century academic inquiry. In order to solve the second great problem of learning we need to correct the three blunders of the traditional Enlightenment. This involves changing the nature of social inquiry, so that social science becomes social methodology or social philosophy, concerned to help us build into social life the progress-achieving methods of aim-oriented rationality, arrived at by generalizing the progress-achieving methods of science. It also involves, more generally, bringing about a revolution in the nature of academic inquiry as a whole, so that it takes up its proper task of helping humanity learn how to become wiser by increasingly cooperatively rational means. The scientific task of improving knowledge and understanding of nature becomes a part of the broader task of improving global wisdom. (shrink)

Using an observational sample of players of a simple online game, we are able to trace the development of skill in that game. Information on playing time, and player location, allows us to estimate time of day during which practice took place. We compare those whose breaks in practice probably contained a night's sleep and those whose breaks in practice probably did not contain a night's sleep. Our analysis confirms experimental evidence showing a benefit of spacing for skill learning, (...) but it fails to find any additional benefit of sleeping during a break from practice. We discuss reasons why the well-established phenomenon of sleep consolidation might not manifest in an observational study of skill development. We put the spacing effect into the context of the other known influences on skill learning: improvement with practice, and individual differences in initial performance. Analysis of performance data from games allows experimental results to be demonstrated outside of the lab and for experimental phenomenon to be put in the context of the performance of the whole task. (shrink)

Using an observational sample of players of a simple online game, we are able to trace the development of skill in that game. Information on playing time, and player location, allows us to estimate time of day during which practice took place. We compare those whose breaks in practice probably contained a night's sleep and those whose breaks in practice probably did not contain a night's sleep. Our analysis confirms experimental evidence showing a benefit of spacing for skill learning, (...) but it fails to find any additional benefit of sleeping during a break from practice. We discuss reasons why the well-established phenomenon of sleep consolidation might not manifest in an observational study of skill development. We put the spacing effect into the context of the other known influences on skill learning: improvement with practice, and individual differences in initial performance. Analysis of performance data from games allows experimental results to be demonstrated outside of the lab and for experimental phenomenon to be put in the context of the performance of the whole task. (shrink)

Two great problems of learning confront humanity: learning about the nature of the universe and about ourselves and other living things as a part of the universe, and learning how to become civilized or enlightened. The first problem was solved, in essence, in the 17th century, with the creation of modern science. But the second problem has not yet been solved. Solving the first problem without also solving the second puts us in a situation of great danger. (...) All our current global problems have arisen as a result. What we need to do, in response to this unprecedented crisis, is learn from our solution to the first problem how to solve the second one. This was the basic idea of the 18th century Enlightenment. Unfortunately, in carrying out this programme, the Enlightenment made three blunders, and it is this defective version of the Enlightenment programme, inherited from the past, that is still built into the institutional/intellectual structure of academic inquiry in the 21st century. In order to solve the second great problem of learning we need to correct the three blunders of the traditional Enlightenment. This involves changing the nature of social inquiry, so that social science becomes social methodology or social philosophy, concerned to help us build into social life the progress-achieving methods of aim-oriented rationality, arrived at by generalizing the progress-achieving methods of science. It also involves, more generally, bringing about a revolution in the nature of academic inquiry as a whole, so that it takes up its proper task of helping humanity learn how to become wiser by increasingly cooperatively rational means. The scientific task of improving knowledge and understanding of nature becomes a part of the broader task of improving global wisdom. The outcome would be what we so urgently need: a kind of inquiry rationally designed and devoted to helping us make progress towards a genuinely civilized world. We would succeed in doing what the Enlightenment tried but failed to do: learn from scientific progress how to go about making social progress towards as good a world as possible. (shrink)

Improvement in performance after the end of the training session, termed “Offline improvement,” has been shown in procedural learning tasks. We examined whether Offline improvement in learning a novel orthography depends on the type of reading instruction. Forty-eight adults received multisession training in reading nonsense words, written in an artificial script. Participants were trained in one of three conditions: alphabetical words preceded by direct letter instruction (Letter-Alph); alphabetical words with whole-word instruction (Word-Alph); and nonalphabetical (arbitrary) words with (...) whole-word instruction (Word-Arb). Offline improvement was found only for the Letter-Alph group. Moreover, correlation with a standardized measure of word reading ability showed that good readers trained in the Letter-Alph group exhibit greater Offline improvement, whereas good readers trained in the Word-Arb group showed greater Within-session improvement during training. These results suggest that different consolidation processes and learning mechanisms were involved in each group. We argue that providing a short block of direct letter instruction prior to training resulted in increased involvement of procedural learning mechanisms during training. (shrink)

Naturalistic stimuli, including movie, music, and speech, have been increasingly applied in the research of neuroimaging. Relative to a resting-state or single-task state, naturalistic stimuli can evoke more intense brain activities and have been proved to possess higher test–retest reliability, suggesting greater potential to study adaptive human brain function. In the current research, naturalistic functional magnetic resonance imaging (N-fMRI) has been a powerful tool to record brain states under naturalistic stimuli, and many efforts have been devoted to study the (...) high-level semantic features from spatial or temporal representations via N-fMRI. However, integrating both spatial and temporal characteristics of brain activities for better interpreting the patterns under naturalistic stimuli is still underexplored. In this work, a novel hybrid learning framework that comprehensively investigates both the spatial (via Predictive Model) and the temporal [via convolutional neural network (CNN) model] characteristics of the brain is proposed. Specifically, to focus on certain relevant regions from the whole brain, regions of significance (ROS), which contain common spatial activation characteristics across individuals, are selected via the Predictive Model. Further, voxels of significance (VOS), whose signals contain significant temporal characteristics under naturalistic stimuli, are interpreted via one-dimensional CNN (1D-CNN) model. In this article, our proposed framework is applied onto the N-fMRI data during naturalistic classical/pop/speech audios stimuli. The promising performance is achieved via the Predictive Model to differentiate the different audio categories. Especially for distinguishing the classic and speech audios, the accuracy of classification is up to 92%. Moreover, spatial ROS and VOS are effectively obtained. Besides, temporal characteristics of the high-level semantic features are investigated on the frequency domain via convolution kernels of 1D-CNN model, and we effectively bridge the “semantic gap” between high-level semantic features of N-fMRI and low-level acoustic features of naturalistic audios in the frequency domain. Our results provide novel insights on characterizing spatiotemporal patterns of brain activities via N-fMRI and effectively explore the high-level semantic features under naturalistic stimuli, which will further benefit the understanding of the brain working mechanism and the advance of naturalistic stimuli clinical application. (shrink)

In typical development, word learning goes from slow and laborious to fast and seemingly effortless. Typically developing 2-year-olds seem to intuit the whole range of things in a category from hearing a single instance named—they have word-learning biases. This is not the case for children with relatively small vocabularies. We present a computational model that accounts for the emergence of word-learning biases in children at both ends of the vocabulary spectrum based solely on vocabulary structure. The (...) results of Experiment 1 show that late-talkers' and early-talkers' noun vocabularies have different structures and that neural networks trained on the vocabularies of individual late talkers acquire different word-learning biases than those trained on early-talker vocabularies. These models make novel predictions about the word-learning biases in these two populations. Experiment 2 tests these predictions on late- and early-talking toddlers in a novel noun generalization task. (shrink)

An increasing number of learning goals refer to the acquisition of cognitive skills that can be described as ‘resource-based,’ as they require the availability, coordination, and integration of multiple underlying resources such as skills and knowledge facets. However, research on the support of cognitive skills rarely takes this resource-based nature explicitly into account. This is mirrored in prior research on mathematical argumentation and proof skills: Although repeatedly highlighted as resource-based, for example relying on mathematical topic knowledge, methodological knowledge, mathematical (...) strategic knowledge, and problem-solving skills, little evidence exists on how to support mathematical argumentation and proof skills based on its resources. To address this gap, a quasi-experimental intervention study with undergraduate mathematics students examined the effectiveness of different approaches to support both mathematical argumentation and proof skills and four of its resources. Based on the part-/whole-task debate from instructional design, two approaches were implemented during students’ work on proof construction tasks: (i) asequential approachfocusing and supporting each resource of mathematical argumentation and proof skills sequentially after each other and (ii) aconcurrent approachfocusing and supporting multiple resources concurrently. Empirical analyses show pronounced effects of both approaches regarding the resources underlying mathematical argumentation and proof skills. However, the effects of both approaches are mostly comparable, and only mathematical strategic knowledge benefits significantly more from the concurrent approach. Regarding mathematical argumentation and proof skills, short-term effects of both approaches are at best mixed and show differing effects based on prior attainment, possibly indicating an expertise reversal effect of the relatively short intervention. Data suggests that students with low prior attainment benefited most from the intervention, specifically from the concurrent approach. A supplementary qualitative analysis showcases how supporting multiple resources concurrently alongside mathematical argumentation and proof skills can lead to a synergistic integration of these during proof construction and can be beneficial yet demanding for students. Although results require further empirical underpinning, both approaches appear promising to support the resources underlying mathematical argumentation and proof skills and likely also show positive long-term effects on mathematical argumentation and proof skills, especially for initially weaker students. (shrink)

In the past years motor imagery turned out to be also an innovative and effective tool for motor learning and improvement of sports performance. Whereas many studies investigating sports MI focusing on upper or lower limbs involvement, knowledge about involved neural structures during whole-body movements is still limited. In the present study we investigated brain activity of climbers during a kinesthetic motor imagery climbing task with different difficulties by means of functional near infrared spectroscopy. Twenty healthy participants (...) were split into two groups according to their climbing skill level. The aim of the current study is investigating neural correlates of a whole-body sports MI task with an additional focus on skill level dependency. Climbing experts and non-experts imagined bouldering an “easy” and “difficult” route from a first-person perspective while hemodynamic responses were recorded simultaneously. We found significant differences between the two climbing routes, easy and difficult within participants as well as between the two groups of different climbing skill levels. Overall beginners showed increased hemodynamic responses compared to experts in all defined regions of interest supporting the claim of the neural efficiency hypothesis. Even though climbing is a complex, coordinated movement of upper and lower limbs we found a stronger activation focus of the upper limbs, especially of the dominant hand-area, while the foot area seems to be deactivated or inhibited simultaneously. Summarizing, these findings provide novel insights into brain activation during the imagery of a whole-body movement and its relation to climbing expertise. (shrink)

One of the main challenges for computational legal research is drawing up innovative heuristics to derive actionable knowledge from legal documents. While a large part of the research has been so far devoted to the extraction of purely legal information, less attention has been paid to seeking out in the texts the clues of more complex entities: legally relevant facts whose detection requires to link and interpret, as a unified whole, legal information and results of empirical analyses. This paper (...) presents an ongoing research that points in this direction, trying to devise new ways to support public prosecutors in assessing the dangerousness of individuals and groups under investigation, an activity that precisely relies on the cross-sectional evaluation of legal and empirical data. A knowledge mining strategy will be outlined that lines up, into a single metaheuristic model, information extraction, network-based inference, machine learning and visual analytics. We will focus, in particular, on the integration of graph-based inference and machine learning methods used both to support classification tasks and to explore new forms of man-machine cooperation. Experiments made involving public prosecutors from the Italian Anti-Mafia Investigation Directorate and using data from real investigations have not only shown the potentialities of our approach but also offered an opportunity to reflect on the role we could assign to AI when thinking about the future of legal science and practice. (shrink)

Maud Boyer Arnaud Destrebecqz Axel Cleeremans.

PurposeThis study aimed to investigate whether oxygenated hemoglobin generated during a motor imagery task is associated with the motor learning level of the task.MethodsWe included 16 right-handed healthy participants who were trained to perform a ball rotation task. Hemodynamic brain activity was measured using near-infrared spectroscopy to monitor changes in oxy-Hb concentration during the BR MI task. The experimental protocol used a block design, and measurements were performed three times before and after the initial training (...) of the BR task as well as after the final training. The BR count during training was also measured. Furthermore, subjective vividness of MI was evaluated three times after NIRS measurement using the Visual Analog Scale.ResultsThe results showed that the number of BRs increased significantly with training. VAS scores also improved with training. Furthermore, oxy-Hb concentration and the region of interest showed a main effect. An interaction was confirmed, and it was ascertained that the change in oxy-Hb concentrations due to training was different for each ROI. The most significant predictor of subjective MI vividness was supplementary motor area oxy-Hb concentration.DiscussionHemodynamic brain activity during MI tasks may be correlated with task motor learning levels, since significant changes in oxy-Hb concentrations were observed following initial and final training in the SMA. In particular, hemodynamic brain activity in the SMA was suggested to reflect the MI vividness of participants. (shrink)

This paper presents a novel learning model Clarion , which is a hybrid model based on the two-level approach proposed in Sun (1995). The model integrates neural, reinforcement, and symbolic learning methods to perform on-line, bottom-up learning (i.e., learning that goes from neural to symbolic representations). The model utilizes both procedural and declarative knowledge (in neural and symbolic representations respectively), tapping into the synergy of the two types of processes. It was applied to deal with sequential (...) decision tasks. Experiments and analyses in various ways are reported that shed light on the advantages of the model. (shrink)

The prefrontal cortex is widely believed to play an important role in facilitating people's ability to switch performance between different tasks. We present a biologically‐based computational model of prefrontal cortex (PFC) that explains its role in task switching in terms of the greater flexibility conferred by activation‐based working memory representations in PFC, as compared with more slowly adapting weight‐based memory mechanisms. Specifically we show that PFC representations can be rapidly updated when a task switches via a dynamic gating (...) mechanism based on a temporal‐differences reward‐prediction learning mechanism. Unlike prior models of this type, the present model develops all of its internal representations via learning mechanisms as shaped by the demands of continuous periodic task switching. This advance opens up a new domain of research into the interactions between working memory task demands and the representations that develop to meet them. Results on a version of the Wisconsin card sorting task are presented for the full model and a number of comparison networks that test the importance of various model features. Furthermore, we show that a lesioned model produces perseverative errors like those seen in frontal patients. (shrink)

We demonstrated unconscious learning of task-irrelevant perceptual regularities in a Serial Reaction Time task in both visual and auditory domains. Participants were required to respond to different letters or syllables which occurred in random order. Unbeknownst to participants, the color of the two letters or the tone of the syllables varied according to certain rules. Reaction times indicated that people indeed learnt both the color and tonal regularities indicating that task-irrelevant sequence structure can be learned perceptually. (...) In a subsequent prediction test of knowledge of the color or tonal cues using subjective measures, we showed that people could acquire task irrelevant knowledge unconsciously. (shrink)

In this article, I explore plant semiosis with a focus on plant learning. I distinguish between the scales and levels of learning conceivable in phytosemiosis, and identify organism-scale learning as the distinguishing question for plant semiosis. Since organism-scale learning depends on organism-scale semiosis, I critically review the arguments regarding whole-plant functional cycles. I conclude that they have largely relied on Uexküllian biases that have prevented an adequate interpretation of modern plant neurobiology. Through an examination of (...) trophic growth in plant roots, I expose some conceptual difficulties in attributing functional cycles to whole-plants. I conclude that the mapping of resource areas in the root system is a learning activity requiring higher-scale sign activity than is possible at the cellular scale, strongly suggesting the presence of organism-scale functional cycles. I do, however, question whether all perception-action cycles in organisms are accompanied with organism-scale semiosis. (shrink)

This article presents a computational model of the learning of diagnostic knowledge, based on observations of human operators engaged in real-world troubleshooting tasks. We present a model of problem solving and learning in which the reasoner introspects about its own performance on the problem-solving task, identifies what it needs to learn to improve its performance, formulates learning goals to acquire the required knowledge, and pursues its learning goals using multiple learning strategies. The model is (...) implemented in a computer system which provides a case study based on observations of troubleshooting operators and protocol analysis of the data gathered in the test area of an operational electronics manufacturing plant. The model not only addresses issues in human learning, but, in addition, is computationally justified as a uniform, extensible framework for multistrategy learning. (shrink)

This paper presents an experimental study investigating artificial grammar learning (AGL) in monolingual and bilingual children, with and without dyslexia, using an original methodology. We administered a serial reaction time (SRT) task, in the form of a modified Simon task, in which the sequence of the stimuli was manipulated according to the rules of a simple Lindenmayer grammar (more specifically, a Fibonacci grammar). By ensuring that the subjects focused on the correct response execution at the motor stage (...) in presence of congruent or incongruent visual stimuli, we could meet the two fundamental criteria for implicit learning: the absence of an intention to learn and the lack of awareness at the level of resulting knowledge. The participants of our studies were four groups of 10-year-old children: 30 Italian monolingual typically developing children, 30 bilingual typically developing children with Italian L2, 24 Italian monolingual dyslexic children and 24 bilingual dyslexic children with Italian L2. Participants were administered the modified Simon task developed according to the rules of the Fibonacci grammar and tested with respect to the implicit learning of three regularities: (i) a red is followed by a blue; (ii) a sequence of two blues is followed by a red and (iii) a blue can be followed either by a red or by a blue. Results clearly support the hypothesis that implicit learning took place, since participants of all groups became increasingly sensitive to the structure of the input, implicitly learning the sequence of the trials and thus appropriately predicting the occurrence of the relevant items, as manifested by faster reaction times in predictable trials. Moreover, group differences were found, with bilinguals being overall faster than monolinguals and dyslexics less accurate than controls. Finally, an advantage of bilingualism in dyslexia was found, with bilingual dyslexics performing consistently better than monolingual dyslexics and, in some conditions, at the level of the two control groups. These results are taken to suggest that bilingualism should be supported also among linguistically impaired individuals. (shrink)

Within the field of human‐computer interaction, the study of the interaction between people and computers has revealed many phenomena. For example, highly interactive devices, such as the Apple Macintosh, are often easier to learn and use than keyboard‐based devices such as Unix. Similarly, consistent interfaces are easier to learn and use than inconsistent ones. This article describes an integrated cognitive model designed to exhibit a range of these phenomena while learning task‐action mappings: action sequences for achieving simple goals, (...) such as opening a file in a word processor. The model, called TAL, is of a user who is familiar with the basic operations of a keyboard and mouse, but unfamiliar with the particular menu structures, words, and actions required to use the device. The model is constructed in Soar and employs a single set of architectural mechanisms. It exhibits behavior that captures human preference for consistent, interactive, and meaningful task‐action mappings. (shrink)

This book offers a rich collection of voices from diverse settings and illustrates ways in which lectio divina as a contemplative practice can transform teaching and learning. Drawing on holistic education and embodied learning, lectio divina empowers teachers and roots students in their own meaning making.

The prefrontal cortex is widely believed to play an important role in facilitating people's ability to switch performance between different tasks. We present a biologically‐based computational model of prefrontal cortex (PFC) that explains its role in task switching in terms of the greater flexibility conferred by activation‐based working memory representations in PFC, as compared with more slowly adapting weight‐based memory mechanisms. Specifically we show that PFC representations can be rapidly updated when a task switches via a dynamic gating (...) mechanism based on a temporal‐differences reward‐prediction learning mechanism. Unlike prior models of this type, the present model develops all of its internal representations via learning mechanisms as shaped by the demands of continuous periodic task switching. This advance opens up a new domain of research into the interactions between working memory task demands and the representations that develop to meet them. Results on a version of the Wisconsin card sorting task are presented for the full model and a number of comparison networks that test the importance of various model features. Furthermore, we show that a lesioned model produces perseverative errors like those seen in frontal patients. (shrink)

This study investigates the performance of 21 monolingual and 56 bilingual children aged 5;6-9;0 on German-LITMUS-sentence-repetition (SRT; Hamann et al., 2013) and nonword-repetition-tasks (NWRT; Grimm et al., 2014), which were constructed according to the LITMUS-principles (Language Impairment Testing in Multilingual Settings; Armon-Lotem et al., 2015). Both tasks incorporate complex structures shown to be cross-linguistically challenging for children with Specific Language Impairment (SLI) and aim at minimizing bias against bilingual children while still being indicative of the presence of language impairment across (...) language combinations. Given the great variability in bilingual language exposure and the potential effect of language experience on language performance in bilingual children, we examined whether background variables related to bilingualism, particularly, the degree language dominance as measured by relative amount of use and exposure, could compromise the diagnostic accuracy of the German-LITMUS-SRT and NWRT. We further investigated whether a combination of the two tasks provides better diagnostic accurracy. To address this, we used an unsupervised machine learning algorithm, the Partitioning-Around-Medoids (PAM), for deriving a clinical category for the children as ±language-impaired based on performance scores on SRT and/or NWRT while withholding information about their clinical status based on standardized assessment in L1/L2. Subsequently, we calculated diagnostic accuracy and investigated which background variables (age of onset, length of exposure, degree of language-dominance, socio-economic-status, and risk factors for SLI) best explained clinical-group-membership yielded from the PAM-analysis based on NWRT and/or SRT scores. Results show that although language-dominance influences the performance of bilingual typically-developing children, especially in the SRT, the diagnostic accuracy of the tools is not compromised by language dominance: while risk factors for SLI were significant predictors for clinical group membership in all models, language dominance did not contribute at all to explaining clinical cluster membership as typically-developing or SLI based on any of the combinations of the SRT and NWRT variables. Additionally, results confirm that a combination of SRT scored by correct target structure and the structurally more complex language-dependent part of the NWRT yields better diagnostic accuracy than single measures and is only sensitive for risk factors for SLI and not to dominance levels or SES. (shrink)

This book declares that lifelong learning teaches values and wholeness and rejects inert ideas or fragmentation. Education plays a vital role in reorganizing and revitalizing the abundant facts from the information explosion. Specialization works at cross-purposes with liberal arts education, which discloses a holistic vision of each person’s being.

Within the field of human‐computer interaction, the study of the interaction between people and computers has revealed many phenomena. For example, highly interactive devices, such as the Apple Macintosh, are often easier to learn and use than keyboard‐based devices such as Unix. Similarly, consistent interfaces are easier to learn and use than inconsistent ones. This article describes an integrated cognitive model designed to exhibit a range of these phenomena while learning task‐action mappings: action sequences for achieving simple goals, (...) such as opening a file in a word processor. The model, called TAL, is of a user who is familiar with the basic operations of a keyboard and mouse, but unfamiliar with the particular menu structures, words, and actions required to use the device. The model is constructed in Soar and employs a single set of architectural mechanisms. It exhibits behavior that captures human preference for consistent, interactive, and meaningful task‐action mappings. (shrink)