| We use tools to solve mechanical problems. When the problems are simple, it is easy to decide which tools to use. However, as the difficulty of the problems increase, our standard problem-solving strategies become increasingly ineffective.;Despite the importance of this topic in better understanding how adults think and solve problems with tools, it has received scarce attention. In this dissertation, I focus on how humans use tools to solve problems of considerable difficulty.;The three studies in this dissertation used six 3D mechanical puzzles created in our laboratory. The first study investigated the effects of functional fixedness on mechanical problem solving. Contrary to the idea that this cognitive bias always interferes with problem solving, our results indicated that its effects are confined to simple problems. The second study investigated the contributions of visual and haptic information to the solution of problems. I found that the visual, haptic, and visuo-haptic groups solved the mechanical problems at a similar rate. However, the visual group was notoriously faster in planning the solutions. Further, I compared the manual exploratory procedures (EPs) used by the haptic and visuo-haptic groups and found that the number of EPs generated per second was linked to whether participants solved the puzzles. The third study showed the effects of mechanical problem-solving training on the acquisition of spatial skills. Results suggested that after being exposed to this training, participants increased their spatial skills for at least one week. This training was more effective than both a computerized training strategy and a control condition. Results also suggested that mechanical problem solving is based on spatial visualization. This work sheds light on the mechanisms underlying mechanical problem solving with tools. The dissertation concludes with a discussion about how these results can inform the use of Maker-spaces for educational practices. |
