164 research outputs found

    Designing an Educational Game: Case Study of ’Europe 2045’

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    Abstract. This paper presents a theoretical framework, which has been adopted in designing an on-line multi-player strategy game Europe 2045. Europe 2045 is an educational tool for high school social science courses, aimed at familiar-izing students with political, economic, and social issues in contemporary Europe. Apart from learning facts, players develop a range of key skills: discus-sion ability, negotiation, teamwork, and group decision-making. The presented theoretical framework is based on a critical analysis of crucial issues, which seem to determine the success or failure of development and implementation of an educational game in the formal school environment. It demonstrates key ap-proaches the authors of Europe 2045 have adopted in order to overcome already known problems related to game-based learning. On a general level this paper discusses issues related to formal fact learning in educational systems and the possible role of educational games in enhancing these systems

    Learning Mazes with Aliasing States: An LCS Algorithm with Associative Perception

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    Learning classifier systems (LCSs) belong to a class of algorithms based on the principle of self-organization and have frequently been applied to the task of solving mazes, an important type of reinforcement learning (RL) problem. Maze problems represent a simplified virtual model of real environments that can be used for developing core algorithms of many real-world applications related to the problem of navigation. However, the best achievements of LCSs in maze problems are still mostly bounded to non-aliasing environments, while LCS complexity seems to obstruct a proper analysis of the reasons of failure. We construct a new LCS agent that has a simpler and more transparent performance mechanism, but that can still solve mazes better than existing algorithms. We use the structure of a predictive LCS model, strip out the evolutionary mechanism, simplify the reinforcement learning procedure and equip the agent with the ability of associative perception, adopted from psychology. To improve our understanding of the nature and structure of maze environments, we analyze mazes used in research for the last two decades, introduce a set of maze complexity characteristics, and develop a set of new maze environments. We then run our new LCS with associative perception through the old and new aliasing mazes, which represent partially observable Markov decision problems (POMDP) and demonstrate that it performs at least as well as, and in some cases better than, other published systems

    Dificultades para codificar, relacionar y categorizar problemas verbales algebraicos: dos estudios con estudiantes de secundaria y profesores en formación

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    En resolución de problemas verbales por transferencia, la activación de problemas ya conocidos que sirvan de guía, depende de las analogías percibidas entre éstos y el problema a resolver. Se desarrollan dos estudios relacionados para analizar en qué características se basan los estudiantes para codificar problemas y detectar sus analogías, en tareas de categorización (sorting). Se utilizaron técnicas cuantitativas y cualitativas combinadas. Primero se analizó cómo los estudiantes de secundaria son influidos por diferentes variables características de problemas de ciencias. Una gran proporción de sujetos no fue capaz de percibir las analogías y diferencias adecuadas entre problemas. El segundo estudio trató de avanzar una explicación de estos resultados. El nivel académico y la familiaridad con las temáticas fueron factores significativos, pero los futuros profesores participantes mostraron demasiadas dificultades, alertando sobre la conveniencia de revisar algunos supuestos instruccionales habituales

    Psychology and aggression

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68264/2/10.1177_002200275900300301.pd

    Where Did Everybody Go?

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    High school dictionary

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    1096 tr.; 26 cm

    Reinforcement without Awareness: II. Word Class

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