Evolucion del la precisión de los juicios de metamemoria en juegos para instruccion apoyada por computador

Meta memory judgments are entailed to knowledge acquisition, storage and retrieval. From this point of view they are appraisal of: 1. easy of learning; 2. learning achievement during a period of time; 3. feeling of knowledge; and 4. confidence on answers already performed. They assess the memory content looking backward or forward. The assessment precision changes as the learning curve evolves. In this article we describe the evolution of meta memory judgment precision and suggest an explanation model. In the core of this research there are two questions: 1. What is the metamemory judgment behavior when the easiness or difficulty assessment takes as criterion the time or the number of trials invested in solving a game problem?; 2. What is the metamemory judgment behavior when the computer suggests solution strategies at the beginning of the game – fixed suggestion – and what is, when the suggestion is made as long as the performance is going on – adaptive suggestion -? . An experimental study based on seven computer games on spatial reasoning was conducted in order to answer these questions. A sample of 130 students of tenth to eleventh school grade was randomly assigned to four experimental conditions: a: time based meta memory judgment and fixed strategy suggestion; b: event based meta memory judgment and fixed strategy suggestion; c: time based meta memory judgment and adaptive strategy suggestion ; and d: event based meta memory judgment and adaptive strategy suggestion. Given the support of the experimental data, we built a theoretical model to understand the set of relations between the retrospective and prospective meta memory judgments, and between the evolution of the learning curve and the evolution of meta memory judgment accuracy. In this model, in order to make a prospective judgment, a retrospective judgment should be accomplished first, in such a way that previous knowledge be related to the current problem representation. When the learning environment shows a prevision error to the learner, he or she starts assessing the prospective judgment in the previous stage. He or she can go backward assessing each previous step until the initial problem representation. But, according to the least effort law it is no probable and usually learners go back just one or two steps. The importance of this process however is that it constitutes a powerful mechanism to integrate the learning elements in a sequential process and is registered in long term memory. The model introduced here explains why the frequent elicitation of meta cognitive judgments results in a strong capacity for the student to control his or her own process of learning and why it becomes a key element to develop autonomous learning. The model is consistent with the current research on the dynamics on learning control and meta cognition, specially with those which show that eliciting metacognitive judgment results in consistent use of problem solving strategies and better recall performance.