Adaptive Timing, Attention, and Movement Control

Examples of how LTP and LTD can control adaptively timed learning that modulates attention and motor control are given. It is also suggested that LTP/LTD can also play a role in storing memories. The distinction between match-based and mismatch-based learning may help to clarity the difference.Defense Advanced Research Projects Agency; Office of Naval Research (N00014-92-J-1209, N00014-95-1-0409, N00014-95-1-0657

Teaching Fluid Mechanics for Undergraduate Students in Applied Industrial Biology: from Theory to Atypical Experiments

EBI is a further education establishment which provides education in applied industrial biology at level of MSc engineering degree. Fluid mechanics at EBI was considered by students as difficult who seemed somewhat unmotivated. In order to motivate them, we applied a new play-based pedagogy. Students were asked to draw inspiration from everyday life situations to find applications of fluid mechanics and to do experiments to verify and validate some theoretical results obtained in course. In this paper, we present an innovative teaching/learning pedagogy which includes the concept of learning through play and its implications in fluid mechanics for engineering. Examples of atypical experiments in fluid mechanics made by students are presented. Based on teaching evaluation by students, it is possible to know how students feel the course. The effectiveness of this approach to motivate students is presented through an analysis of students' teaching assessment. Learning through play proved a great success in fluid mechanics where course evaluations increased substantially. Fluid mechanics has been progressively perceived as interesting, useful, pleasant and easy to assimilate. It is shown that this pedagogy which includes educational gaming presents benefits for students. These experiments seem therefore to be a very effective tool for improving teaching/learning activities in higher education

Toward a Play Management System for Play-Based Learning

International audienceThis position paper is dedicated to describing a preliminary model of an integrated system, called Play Management System (PMS). PMS is designed to support both players and teachers to deliver, use, manage and track play situations. This PMS model results from a design-based research methodology. Our approach focuses on (1) the learners and the situation that emerges when they play the game, rather than the system dedicated to play and (2) the teachers who want to manage a game-based learning situation. Thus, we argue for a shift from a game-based to a play-based perspective. 1 Introduction Within a context marked by the development of alternative pedagogies, this position paper aims to describe a model of an integrated system, called Play Management System (PMS), dedicated to support players and teachers to deliver, use, manage and track play situations. The purpose of this article is to propose an innovative approach for implementing a play-based learning approach by (1) focusing on the learners and taking into consideration the situation that emerges when they play rather than the artifact dedicated to play (play vs game) and (2) focusing on the teachers who want to implement and manage a play-based learning situation in their classroom (play management vs game design). Thus, we address the issue of teachers' requirements for the orchestration of a play situation within an educational context. In the first section of this paper, we advocate for a player-centered approach for game-based learning. The second section presents a game developed during the project and the design-based research methodology adopted for designing this game. The third section describe

Learning and Type Compatibility in Signaling Games

Which equilibria will arise in signaling games depends on how the receiver interprets deviations from the path of play. We develop a micro-foundation for these off-path beliefs, and an associated equilibrium refinement, in a model where equilibrium arises through non-equilibrium learning by populations of patient and long-lived senders and receivers. In our model, young senders are uncertain about the prevailing distribution of play, so they rationally send out-of-equilibrium signals as experiments to learn about the behavior of the population of receivers. Differences in the payoff functions of the types of senders generate different incentives for these experiments. Using the Gittins index (Gittins, 1979), we characterize which sender types use each signal more often, leading to a constraint on the receiver's off-path beliefs based on "type compatibility" and hence a learning-based equilibrium selection

Deep Reinforcement Learning from Self-Play in Imperfect-Information Games

Many real-world applications can be described as large-scale games of imperfect information. To deal with these challenging domains, prior work has focused on computing Nash equilibria in a handcrafted abstraction of the domain. In this paper we introduce the first scalable end-to-end approach to learning approximate Nash equilibria without prior domain knowledge. Our method combines fictitious self-play with deep reinforcement learning. When applied to Leduc poker, Neural Fictitious Self-Play (NFSP) approached a Nash equilibrium, whereas common reinforcement learning methods diverged. In Limit Texas Holdem, a poker game of real-world scale, NFSP learnt a strategy that approached the performance of state-of-the-art, superhuman algorithms based on significant domain expertise.Comment: updated version, incorporating conference feedbac

Content-driven design and architecture of E-learning applications

E-learning applications combine content with learning technology systems to support the creation of content and its delivery to the learner. In the future, we can expect the distinction between learning content and its supporting infrastructure to become blurred. Content objects will interact with infrastructure services as independent objects. Our solution to the development of e-learning applications – content-driven design and architecture – is based on content-centric ontological modelling and development of architectures. Knowledge and modelling will play an important role in the development of content and architectures. Our approach integrates content with interaction (in technical and educational terms) and services (the principle organization for a system architecture), based on techniques from different fields, including software engineering, learning design, and knowledge engineering

Learning spillover and analogy-based expectations: a multi-game experiment

We consider a multi-game interactive learning environment and ask ourselves whether long run behaviors in one game are a¤ected by behaviors in the other, i.e whether there are learning spillovers. Our main �nding is that learning spillovers arise whenever the feedback provided to subjects about past play is not easily accessible game by game and thus subjects get a more immediate impression about aggregate distributions. In such a case, long run behaviors stabilize to an analogy-based expectation equilibrium (Jehiel 2005), thereby suggesting how one should broaden the notion of equilibrium to cope with learning spillovers

'Right I can do this now'. Community based adult learning, health and well-being

This article explores the experiences of participants in community based adult learning (CBAL) in relation to health and well-being. It draws on data from a small-scale life history study undertaken with 10 adult learners in two local authority areas in Scotland. The article concludes that, for some learners, participation in CBAL had contributed to a sense of well-being and was seen by them as supporting their capacity to cope with ill-health. In addition, it is suggested that community based adult learning can play a role in the recovery from mental ill-health and depression