Problems are encountered frequently in everyday activity, varying in complexity and occurring across a diverse array of settings. So-called problem isomorphs instantiated in different task ecologies draw upon different skills and abilities a distributed cognition analysis may provide a fruitful perspective on learning and transfer. Learning was evident in both the low and high interactivity groups, but latency per move was significantly faster in the high interactivity group, in both presentations. Experiment 2 was designed to determine the amount of learning in a low and high interactivity condition in this experiment participants completed the problem twice, but level of interactivity was manipulated between subjects. Participants thus showed greater facility to transfer their experience of completing the problem from a low to a high interactivity condition. When participants first completed the task in the high interactivity condition, transfer to the low interactivity condition during the second attempt was limited Experiment 1B replicated this pattern of results. Learning, as gauged in terms of latency to completion, was much more pronounced when the high interactivity condition was experienced second.
In Experiment 1A, participants completed the same problem twice, once in a low interactivity condition, and once in a high interactivity condition (with order counterbalanced across participants). The role of interactivity in problem solving was investigated using a river-crossing problem.
Outside the psychologist’s laboratory, thinking proceeds on the basis of a great deal of interaction with artefacts that are recruited to augment problem-solving skills.
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