Problem Solving
The efficacy of the Mind Lab Method has been put to the test in a number of comparative research projects carried out in conjunction with senior researchers, most notably with Professor Donald Green of Yale University. The research verifies that the Mind Lab Method significantly improves pupils’ thinking abilities and life skills.
In one of these research projects, the following hypothesis was tested: Children can be taught abstract strategic thinking by learning meta-cognitive models and by being exposed to the applications of these models in thinking games and in real life situations. In order to test this assumption, a field study was conducted in which children aged 8-12, from diverse socio-economic backgrounds, took part.
- In the first stage, all the children were presented with the computerized version of the game “Rush Hour.” This advanced version monitors children’s performance and progress and then collates it all into a database.
- In the second stage, children in the research group were taught abstract models for problem-solving, and their analogies to real-life situations. Subsequently they were shown how these models could be applied directly in the games. The children in the control group simply participated freely in game-playing sessions.
- In the third stage, all the children were taught a new game, “Lunar Lockout.” Both groups received identical instruction.
The results show that the children in the research group significantly improved their performance levels in relation to their counterparts in the control group, even though the latter were allocated more time in their game-playing sessions. The remarkable fact is that even in Stage Three, the research group achieved notably higher results. In fact, the disparity between the two groups actually increased between Stages Two and Three.
The conclusions drawn from these results are:
- The learning of Mind Lab problem-solving models significantly improves children’s strategic thinking skills.
- The children who learned Mind Lab abstract models succeeded in transferring the knowledge acquired to new fields, and the improvement in these new fields was even greater than in the original game.