Board games as a teaching tool for technology classes in Compulsory Secondary Education

Aquest treball estudia la tècnica coneguda com game-based learning, és a dir, l’ús dels jocs com a eina didàctica. Primer que res, es fa recerca sobre els treballs ja existents i es veu que, tot i haver-hi articles sobre game-based learning, és difícil trobar-ne de relacionats amb la tecnologia, més enllà d’ensenyar a programar. A continuació, es revisen els continguts curriculars i les competències de secundària i es relacionen amb alguns jocs de taula ja existents, dels quals es detallen breument les regles de joc. Es veu que hi ha continguts curriculars, pels quals es difícil trobar un joc que hi encaixi. A més a més, es desenvolupa la idea d’un nou joc de taula, basat en el ja existent Party & Co., per treballar alguns dels continguts curriculars pels quals no s’ha trobat cap joc existent que s’hi escaigui. Finalment, s’explica una experiència duta a terme durant el període de pràctiques en el centre escolar al curs de 3r d’ESO. Es disposava de tres grups i en tots tres es va seguir la mateixa programació: classe introductòria expositiva, una sessió de muntatge de robots LEGO, 4 sessions de programació i un petit test. En un dels tres grups, però, es va fer una classe prèvia extra on es va jugar a un joc de taula anomenat RoboRally. Els objectius eren dobles: que aprenguessin la importància de l’algorísmica i que s’ho passessin bé. Els resultats mostren que aquest grup va treballar més i millor. En el treball s’analitzen els resultats obtinguts

Robotic ubiquitous cognitive ecology for smart homes

Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

The Virtual University and Avatar Technology: E-learning Through Future Technology

E-learning gains increasingly importance in academic education. Beyond present distance learning technologies a new opportunity emerges by the use of advanced avatar technology. Virtual robots acting in an environment of a virtual campus offer opportunities of advanced learning experiences. Human Machine Interaction (HMI) and Artificial Intelligence (AI) can bridge time zones and ease professional constraints of mature students. Undergraduate students may use such technology to build up topics of their studies beyond taught lectures. Objectives of the paper are to research the options, extent and limitations of avatar technology for academic studies in under- and postgraduate courses and to discuss students' potential acceptance or rejection of interaction with AI. The research method is a case study based on Sir Tony Dyson's avatar technology iBot2000. Sir Tony is a worldwide acknowledged robot specialist, creator of Star Wars' R2D2, who developed in recent years the iBot2000 technology, intelligent avatars adaptable to different environments with the availability to speak up to eight different languages and capable to provide logic answers to questions asked. This technology underwent many prototypes with the latest specific goal to offer blended E-learning entering the field of the virtual 3-D university extending Web2.0 to Web3.0 (Dyson. 2009). Sir Tony included his vast experiences gained in his personal (teaching) work with children for which he received his knighthood. The data was mainly collected through interviews with Sir Tony Dyson, which helps discover the inventor’s view on why such technology is of advantage for academic studies. Based on interviews with Sir Tony, this research critically analyses the options, richness and restrictions, which avatar (iBot2000) technology may add to academic studies. The conclusion will discuss the opportunities, which avatar technology may be able to bring to learning and teaching activities, and the foreseeable limitations – the amount of resources required and the complexity to build a fully integrated virtual 3-D campus. Key Words: virtual learning, avatar technology, iBot2000, virtual universit

Onboard Evolution of Understandable Swarm Behaviors

Designing the individual robot rules that give rise to desired emergent swarm behaviors is difficult. The common method of running evolutionary algorithms off‐line to automatically discover controllers in simulation suffers from two disadvantages: the generation of controllers is not situated in the swarm and so cannot be performed in the wild, and the evolved controllers are often opaque and hard to understand. A swarm of robots with considerable on‐board processing power is used to move the evolutionary process into the swarm, providing a potential route to continuously generating swarm behaviors adapted to the environments and tasks at hand. By making the evolved controllers human‐understandable using behavior trees, the controllers can be queried, explained, and even improved by a human user. A swarm system capable of evolving and executing fit controllers entirely onboard physical robots in less than 15 min is demonstrated. One of the evolved controllers is then analyzed to explain its functionality. With the insights gained, a significant performance improvement in the evolved controller is engineered

Multi-Modal Human-Machine Communication for Instructing Robot Grasping Tasks

A major challenge for the realization of intelligent robots is to supply them with cognitive abilities in order to allow ordinary users to program them easily and intuitively. One way of such programming is teaching work tasks by interactive demonstration. To make this effective and convenient for the user, the machine must be capable to establish a common focus of attention and be able to use and integrate spoken instructions, visual perceptions, and non-verbal clues like gestural commands. We report progress in building a hybrid architecture that combines statistical methods, neural networks, and finite state machines into an integrated system for instructing grasping tasks by man-machine interaction. The system combines the GRAVIS-robot for visual attention and gestural instruction with an intelligent interface for speech recognition and linguistic interpretation, and an modality fusion module to allow multi-modal task-oriented man-machine communication with respect to dextrous robot manipulation of objects.Comment: 7 pages, 8 figure