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INCIDENCIA DE LOS ACTIVADORES DE JUICIOS DE METAMEMORIA Y SUGERENCIAS DE ESTRATEGIAS EN EL APRENDIZAJE AUTÓNOMO
Author(s) -
Luis Facundo Maldonado Granados
Publication year - 2000
Publication title -
tecné, episteme y didaxis ted/tecné, episteme y didaxis/revista de la facultad de ciencia y tecnologia
Language(s) - English
Resource type - Journals
eISSN - 2323-0126
pISSN - 0121-3814
DOI - 10.17227/ted.num8-5633
Subject(s) - psychology , generalization , task (project management) , artificial intelligence , frame (networking) , computer science , cognitive psychology , mathematics , mathematical analysis , management , economics , telecommunications
Develop skills for autonomous learning is a challenge for educational systems in thecurrent knowledge society. ln fact, as information and knowledge production increasesupdate learning becomes a necessary condition for person and enterprise achievement.Three questions are at the core of this paper: a- if metamemory judgment activatorsincrease problem solution; b- lf suggestion of strategy facilitates learning of problemsolving; and c- if strong strategy learning generalizes for handling new problems. Anexperimental study was conducted using discovery problems on spatial reasoning. 9computer games were programmed to support 4 experimental conditions: a) Withmetammemory judgment activators and strategy suggestion, b) With meta-memoryjudgment activa tors and no strategy suggestion, c) Without meta-memory judgmentactivators and with strategy suggestion, and d- With no meta-memory judgment activatorsand no strategy suggestion. 150 high school students were randomly assigned to theexperimental conditions. Statistical analysis uses factor analysis of variance andregression analysis. A simulation program allows reproducing the sequence of transitionstates followed by the problem solvers and identifying solution strategies. Metamemoryjudgements activators effects are interpreted in the frame of a motivational micro-system.Strategy suggestion operates after some basic experience on the task environment andmainly after the first success of solving the problem. Strategy generalization is evidentamong the initial stages of the learning curve of different problems.

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