A new Meno would say: it is knowledge that is nothing more than an empirical figure, a simple result which continually falls back into experience; whereas learning is the true transcendental structure which unites difference to difference, dissimilarity to dissimilarity, without mediating between them—not in the form of a mythical past or former present, but in the pure form of an empty time in general.1In Difference and Repetition (1968), Gilles Deleuze calls for a new Meno. The Meno is (...) one of the Platonic dialogues in which Socrates asserts that learning is recollection. While Deleuze’s central philosophical writing has not been interpreted as a text on learning, his treatment of Plato’s Meno cannot be reduced .. (shrink)

We live in turbulent times, our world is changing at accelerating speed. Information is everywhere, but wisdom appears in short supply when trying to address key inter-related challenges of our time such as; runaway climate change, the loss of biodiversity, the depletion of natural resources, the on-going homogenization of culture, and rising inequity. Living in such times has implications for education and learning. This book explores the possibilities of designing and facilitating learning-based change and transitions towards sustainability. (...) In 31 chapters contributors from across the world discuss (re)emerging forms of learning that not only assist in breaking down unsustainable routines, forms of governance, production and consumption, but also can help create ones that are more sustainable. The book has been divided into three parts: re-orienting science and society, re-connecting people and planet and re-imagining education and learning. This is essential reading for educators, educational designers, change agents, researchers, students, policymakers and entrepreneurs alike, who are concerned about the well-being of the planet and convinced of our ability to do better. The content and related issues can be discussed on the blog by editor Arjen Wals: Transformative learning. 'We are living in times of incertitude, complexity, and contestation, but also of connectivity, responsibility, and new opportunities. This book analyses the consequences of these times for learning in formal, non-formal, and informal education. It explores the possibilities offered by the concept of sustainability as a central category of a holistic paradigm which harmonizes human beings with Earth. To change people and to change the world are interdependent processes - this book contributes to both.' Moacir Gadotti, Director of Paulo Freire Institute, São Paulo, Brazil 'I hope you share my excitement about the innovations for sustainability that this book catalogues and analyses. While the ecological news is grim, the human news is not. Even in a time of accelerating change, people are showing their enormous capacities to learn, adapt, restore and protect.' From the Foreword by Juliet Schor, author of ‘True Wealth: how and why millions of Americans are creating a time-rich, ecologically-light, small-scale high-satisfaction economy’ 'This book implies a ‘culture of critical commitment’ in educational thinking and practice - engaged enough to make a real difference to social-ecological resilience and sustainability but reflexively critical enough to learn constantly from experience and to keep options open in working for a sustainability transformation.' From the Afterword by Stephen Sterling, Professor of Sustainability Education, Centre for Sustainable Futures, Plymouth University, United Kingdom. (shrink)

From the beginning of history sounds have played a fundamentally important role in humanity’s development as ways of expression and of communication. However in contemporary western society, and indeed globally, we are experiencing an excess of speech and a relentless encouragement to expression. Such excess indicates a misunderstanding about what expression and dialogue should be. This condition encourages us to think about silence, solitude and contemplation and the role they might play in restoring the realm of personal understanding of the (...) Self and of one’s authentic experience of the Other. The purpose of this article is to explore the potency of a silence that arises from our participation in the world. We present first some ideas about silence as a human phenomenon. This is followed by an examination of silence and language, an investigation of silence in dialogue, and of its educational implications. The article concludes by emphasising the value of silence as potency in itself, assisting in recovering the expressive powers of language. We argue that it is important to understand the positive status of silence in order to recognise and avoid repressive speech and to introduce its potential for reflective learning. (shrink)

Even if one can experiment on relevant factors, learning the causal structure of a dynamical system can be quite difficult if the relevant measurement processes occur at a much slower sampling rate than the “true” underlying dynamics. This problem is exacerbated if the degree of mismatch is unknown. This paper gives a formal characterization of this learning problem, and then provides two sets of results. First, we prove a set of theorems characterizing how causal structures change under undersampling. (...) Second, we develop an algorithm for inferring aspects of the causal structure at the “true” timescale from the causal structure learned from the undersampled data. Research on causal learning in dynamical contexts has largely ignored the challenges of undersampling, but this paper provides a framework and foundation for learning causal structure from this type of complex time series data. (shrink)

Ability to recall the timing of events is a crucial aspect of associative learning. Yet, traditional theories of associative learning have often overlooked the role of time in learning association and shaping the behavioral outcome. They address temporal learning as an independent and parallel process. Temporal Coding Hypothesis is an attempt to bringing together the associative and non-associative aspects of learning. This account proposes temporal maps, a representation that encodes several aspects of a learned (...) association, but attach considerable importance to the temporal aspect. A temporal map helps an agent to make inferences about missing information by applying an integration mechanism over a common element present in independently acquired temporal maps. We review the empirical evidence demonstrating the construct of temporal maps and discuss the importance of this concept in clinical and behavioral interventions. (shrink)

This paper focuses on the theme of the application of deep learning in the field of basketball sports, using research methods such as literature research, video analysis, comparative research, and mathematical statistics to explore deep learning in real-time analysis of basketball sports data. The basketball posture action recognition and analysis system proposed for basketball movement is composed of two parts serially. The first part is based on the bottom-up posture estimation method to locate the joint points and (...) is used to extract the posture sequence of the target in the video. The second part is the analysis and research of the action recognition algorithm based on the convolution of the space-time graph. According to the extracted posture sequence, the basketball action of the set classification is recognized. In order to obtain more accurate and three-dimensional information, a multitraining target method can be used in training; that is, multiple indicators can be detected and feedback is provided at the same time to correct player errors in time; the other is an auxiliary method, which is compared with ordinary training. The method can actively correct technical movements, train players to form muscle memory, and improve their abilities. Through the research of this article, it provides a theoretical basis for promoting the application of deep learning in the field of basketball and also provides a theoretical reference for the wider application of deep learning in the field of sports. At the same time, the designed real-time analysis system of basketball data also provides more actual reference values for coaches and athletes. (shrink)

The production of good sound generation in the violin is a complex task that requires coordination and spatiotemporal control of bowing gestures. The use of motion-capture technologies to improve performance or reduce injury risks in the area of kinesiology is becoming widespread. The combination of motion accuracy and sound quality feedback has the potential of becoming an important aid in violin learning. In this study, we evaluate motion-capture and sound-quality analysis technologies developed inside the context of the TELMI, a (...) technology-enhanced music learning project. We analyzed the sound and bow motion of 50 participants with no prior violin experience while learning to produce a stable sound in the violin. Participants were divided into two groups: the experimental group received real-time visual feedback both on kinematics and sound quality, while participants in the control group practiced without any type of external help. An additional third group of violin experts performed the same task for comparative purposes. After the practice session, all groups were evaluated in a transfer phase without feedback. At the practice phase, the experimental group improved their bowing kinematics in comparison to the control group, but this was at the expense of impairing the sound quality of their performance. At the retention phase, the experimental group showed better results in sound quality, especially concerning control of sound dynamics. Besides, we found that the expert group improved the stability of their sound while using the technology. All in all, these results emphasize the importance of feedback technologies in learning complex tasks, such as musical instrument learning. (shrink)

View of future time orientation is a cognitive construct about future time. This view has its unique work of motivation and effect on academic performance. Previous studies have only explored the influence that future time orientation brings to the learning process at a single time, and most of them focus on cross-sectional studies. To further explore the cross-lagged relationship for freshmen between future time orientation and learning engagement during different periods, AMOS 23.0 was (...) performed for cross-lagged analysis in this study to explore the influence and effect among variables of different periods. This research was based on the theory of self-determination to discover the relationship between future time and learning involvement for freshmen in enrollment and the first summer vacation. In this research, there were 1,000 valid samples in the first stage and 840 valid samples in the second stage for the conduction of descriptive statistics, pair t-test, and cross-lagged analysis. The results show that: for learning engagement, freshmen at the end of the first year have a higher average score than at the beginning of the first year. View of students of future time orientation can affect their learning engagement of the future through self-determination of students. At last, we provide some suggestions as references for institutional research and future research. (shrink)

People become addicted in different ways, and they respond differently to different interventions. There may nevertheless be a core neural pathology responsible for all distinctively addictive suboptimal behavioral habits. In particular, timing models of reward learning suggest a hypothesis according to which all addiction involves neuroadaptation that attenuates serotonergic inhibition of a mesolimbic dopamine system that has learned that cues for consumption of the addictive target are signals of a high-reward-rate environment.

This paper considers the consensus control problem of nonlinear spatial-temporal hyperbolic partial difference multiagent systems and parabolic partial difference multiagent systems with time delay. Based on the system’s own fixed topology and the method of generating the desired trajectory by introducing virtual leader, using the consensus tracking error between the agent and the virtual leader agent and neighbor agents in the last iteration, an iterative learning algorithm is proposed. The sufficient condition for the system consensus error to converge (...) along the iterative axis is given. When the iterative learning number k approaches infinity, the consensus error in the sense of the L 2 norm between all agents in the system will converge to zero. Furthermore, simulation results illustrate the effectiveness of the algorithm. (shrink)

Globalized workplace is increasingly moving into complex jobs requiring their employees to exhibit complex knowledge and complex skills. Though acquiring such complex skills or knowledge requires longer time, the pace of business puts pressure on organizations to accelerate the time it takes for their employees to become proficient in their jobs. This shift has challenged the conventional training and learning strategies, structure, methods, instructional design and delivery methodologies generally used by training providers and by the organizations. This (...) paper presents the preliminary research findings of a Doctorate research carried out using Grounded theory approach with over 71 in-depth interviews with leading experts in over 40 industries. Preliminary findings suggest that certain e-learning strategies and platforms hold better potential over others to successfully accelerate time-to-proficiency of individuals in leading organizations. This paper provides first look at 10 e-learning strategies and how those could be orchestrated before, during and after a formal training program to develop job-ready learners in shorter time. (shrink)

This book deals with solving a pressing organizational challenge of bringing employees up to speed faster. In the fast-paced business world, organizations need faster readiness of employees to handle the complex responsibilities of their jobs. The author conducted an extensive doctoral research study with 85 global experts across 66 project cases to explore the practices and strategies that were proven to reduce time to proficiency of employees in a range of organizations worldwide. This book provides the readers with a (...) first-hand account of findings exclusively related to training and learning strategies, instructional methods, and curriculum design. This book delivers over 21 training and learning strategies across online learning, classroom instructions, and on-the-job learning. These strategies will allow training designers and learning specialists to design workplace training programs that hold the potential to shorten time to proficiency of employees. The book not only describes findings of the study and theoretical underpinnings, but it also provides practical guidance for implementation to equip corporate learning specialists, HR professionals, training leaders, performance consultants, and direct managers. (shrink)

It's Game Time!: Games to Enhance Classroom Learning enables the teacher to decide when and how to use games to effectively complement their teaching philosophy and style to meet the needs of their students by providing over 40 games that can be used in any class at any level.

Tetris provides a difficult, dynamic task environment within which some people are novices and others, after years of work and practice, become extreme experts. Here we study two core skills; namely, choosing the goal or objective function that will maximize performance and a feature-based analysis of the current game board to determine where to place the currently falling zoid so as to maximize the goal. In Study 1, we build cross-entropy reinforcement learning models to determine whether different goals result (...) in different feature weights. Two of these optimization strategies quickly rise to performance plateaus, whereas two others continue toward higher but more jagged heights. In Study 2, we compare the zoid placement decisions made by our best CERL models with those made by 67 human players. Across 370,131 human game episodes, two CERL models picked the same zoid placements as our lowest scoring human for 43% of the placements and as our three best scoring experts for 65% of the placements. Our findings suggest that people focus on maximizing points, not number of lines cleared or number of levels reached. They also show that goal choice influences the choice of zoid placements for CERLs and suggest that the same is true of humans. Tetris has a repetitive task structure that makes Tetris more tractable and more like a traditional experimental psychology paradigm than many more complex games or tasks. Hence, although complex, Tetris is not overwhelmingly complex and presents a right-sized challenge to cognitive theories, especially those of integrated cognitive systems. (shrink)

1. Abundance. This is a word I took time to contemplate and then as many of us would do, I began to Google the word. So, before I even opened this book by Dave Cormier I found myself seeking inform...

The study investigates effects of the implementation of a law authorizing educational leave in Germany on individual participation in adult learning and education (ALE). In 2015, the federal state of Baden-Württemberg introduced the so-calledBildungszeitgesetz, legitimating an exemption for eligible employees of up to 5 days per year with continued payment of salary. Explaining participation in ALE is a central subject of educational research at national and international level. Current theoretical assumptions of rational choice and empirical findings of educational and (...) socio-statistical research suggest that within the general population, individuals’ availability of time affects the decision to participate and therefore lastly determines participation in ALE. However, current academia mainly discusses time as either a prerequisite for learning activities or as an observable outcome of participation and not as an explanatory factor. Furthermore, since recent studies remain on a descriptive level regarding influences of time on participation in ALE, no causal effects of the availability of time on participation are estimated. Hence, our study addresses this research gap by investigating effects of educational policy interventions such as theBildungszeitgesetzon participation in ALE. Policy interventions are ideally suited to examine the significance of time resources for participation, as the implementation of theBildungszeitgesetzprovides a specific timeframe for employees to participate in ALE outside of their working time. Drawing on data from the German National Educational Panel Study, we employ a difference-in-differences estimation strategy with propensity score matching and instrumental variable to identify the direct causal effect of the implementation of theBildungszeitgesetzon participation in ALE (N= 709). This combination toward causal inference controls for observed and unobserved baseline differences as well as heterogeneous treatment effects. The results reveal a non-significant but heterogeneous treatment effect of the implementation of theBildungszeitgesetzon individual participation in ALE. Contrary to our theoretical assumptions derived from rational choice approaches, we cannot confirm the hypothesis that the availability of time resources due to the implementation of theBildungszeitgesetzcauses a positive effect on participation in ALE. Furthermore, the results reveal that the implementation causes decreasing participation rates for younger adults, women and significantly for migrants. (shrink)

The closure of schools as a result of COVID-19 has been a critical global incident from which to rethink how education works in all our countries. Among the many changes generated by this crisis, all teaching became mediated by digital technologies. This paper intends to analyze the activities carried out during this time through digital technologies and the conceptions of teaching and learning that they reflect. We designed a Likert-type online questionnaire to measure the frequency of teaching activities. (...) It was answered by 1,403 teachers from Spain. The proposed activities varied depending on the learning promoted, the learning outcomes, the type of assessment to which the activities were directed, and the presence of cooperative activities. The major result of this study was that teachers used reproductive activities more frequently than constructive ones. We also found that most activities were those favoring verbal and attitudinal learning. The cooperative activities were the least frequent. Finally, through a cluster analysis, we identified four teaching profiles depending on the frequency and type of digital technologies use: Passive, Active, Reproductive, and Interpretative. The variable that produced the most consistent differences was previous digital technologies use These results show that Information and Communication Technologies uses are reproductive rather than constructive, which impedes effective digital technologies integration into the curriculum so that students gain 21st-century competencies. (shrink)

This paper argues that processes in the sensible realm can be in accord with reason in the Timaeus, since rationality is understood here as being based on regularity, which is conferred onto processes by time. Plato uses two different temporal structures in the Timaeus, associated with the contrast there drawn between Greek and Egyptian approaches to history. The linear order of before and after marks natural processes as rational and underlies the Greek treatment of history. By contrast, a bidirectional (...) temporal structure is the basis for the Egyptian approach to historical processes: present actions are not only determined by preceding ones in the past, but can also be influenced by the future (plans, aims). This latter temporal structure is shown to be necessary for learning from history, which makes human actions more regular. (shrink)

This study investigated visual statistical learning (VSL) in 24 deaf signers and 24 hearing non‐signers. Previous research with hearing individuals suggests that SL mechanisms support literacy. Our first goal was to assess whether VSL was associated with reading ability in deaf individuals, and whether this relation was sustained by a link between VSL and sign language skill. Our second goal was to test the Auditory Scaffolding Hypothesis, which makes the prediction that deaf people should be impaired in sequential processing (...) tasks. For the VSL task, we adopted a modified version of the triplet learning paradigm, with stimuli presented sequentially across space and time. Results revealed that measures of sign language skill (sentence comprehension/repetition) did not correlate with VSL scores, possibly due to the sequential nature of our VSL task. Reading comprehension scores (PIAT‐R) were a significant predictor of VSL accuracy in hearing but not deaf people. This finding might be due to the sequential nature of the VSL task and to a less salient role of the sequential orthography‐to‐phonology mapping in deaf readers compared to hearing readers. The two groups did not differ in VSL scores. However, when reading ability was taken into account, VSL scores were higher for the deaf group than the hearing group. Overall, this evidence is inconsistent with the Auditory Scaffolding Hypothesis, suggesting that humans can develop efficient sequencing abilities even in the absence of sound. (shrink)

Low heart rate causes a risk of death, heart disease, and cardiovascular diseases. Therefore, monitoring the heart rate is critical because of the heart’s function to discover its irregularity to detect the health problems early. Rapid technological advancement allows healthcare sectors to consolidate and analyze massive health-based data to discover risks by making more accurate predictions. Therefore, this work proposes a real-time prediction system for heart rate, which helps the medical care providers and patients avoid heart rate risk in (...) real time. The proposed system consists of two phases, namely, an offline phase and an online phase. The offline phase targets developing the model using different forecasting techniques to find the lowest root mean square error. The heart rate time-series dataset is extracted from Medical Information Mart for Intensive Care. Recurrent neural network, long short-term memory, gated recurrent units, and bidirectional long short-term memory are applied to heart rate time series. For the online phase, Apache Kafka and Apache Spark have been used to predict the heart rate in advance based on the best developed model. According to the experimental results, the GRU with three layers has recorded the best performance. Consequently, GRU with three layers has been used to predict heart rate 5 minutes in advance. (shrink)

Studies of implicit learning have shown that individuals exposed to a rule-governed environment often learn to exploit 'rules' which describe the structural relationship between environmental events. While some authors have interpreted such demonstrations as evidence for functionally separate implicit learning systems, others have argued that the observed changes in performance result from explicit knowledge which has been inadequately assessed. In this paper we illustrate this issue by considering one commonly used implicit learning task, the Serial reaction (...) class='Hi'>time task, and outline what we see as an important problem associated with each of the commonly used methods used to assess explicit knowledge. This is that each measure requires a form of response which is dependent on the subjects having some knowledge of the serial-order of the sequence. We argue that such methods, or more specifically their analyses, seriously underestimate other sources of knowledge, which may be available to subjects during their performance of the SRT task. In support of this argument we demonstrate that subjects' serial-order knowledge can, in principle, be independent of subjects' knowledge of the statistical structure of the sequence, and we propose an alternative method for analysing performance on the Generate task which avoids this problem. (shrink)

A major theme of the systems physiologists is the critical timing function of the cerebellum. However, the biophysicists do not appear to directly address the biophysical basis of the adaptive timing competence implicated in the physiological and behavioral data. Thus, the bridge between the macroscopic and microscopic data bases seems to be incomplete in a critical area. We report successful results from an attempt to add the missing part of the bridge. It comes in the form of a model of (...) how the second messenger system activated by parallel fiber inputs - the mGluR channel - can literally bridge the temporal gap between CS and CR, both in standard conditioning tasks and more generally, [CRÉPEL et al.; HOUK et al.; KANO; LINDEN; SIMPSON et al.; SMITH; THACH; VINCENT]. (shrink)

Cognitive Science, Volume 46, Issue 4, April 2022.