Rule acquisition events in the discovery of problem-solving strategies

Although there are many machine-learning programs that can acquire new problem-solving strategies, it is not known exactly how their processes will manifest themselves in human behavior, if at all. In order to find out, a line-by-line protocol analysis was conducted of a subject discovering problem-solving strategies. A model was developed that could explain 96% of the lines in the protocol. On this analysis, the subject's learning was confined to 11 rule acquisition events, wherein she temporarily abandoned her normal problem solving and focused on improving her strategic knowledge. Further analysis showed that: (1) Not all rule acquisition events are triggered by impasses; (2) Rules are acquired gradually, both because of competition between new and old rules, and because of the subject's apparently deliberate policy of gradual generalization. (3) This subject took a scientific approach to strategy discovery, even planning and conducting small experiments.