Dual space search during scientific reasoning

Douglas Klahr

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Science Education and Pedagogy AI-based Problem Solving and Planning Cognitive Science and Education Research

Abstract

The purpose of the two studies reported here was to develop an integrated model of the scientific reasoning process. Subjects were placed in a simulated scientific discovery context by first teaching them how to use an electronic device and then asking them to discover how a hitherto unencountered function worked. To do this task, subjects had to formulate hypotheses based on their prior knowledge, conduct experiments, and evaluate the results of their experiments. In the first study, using 20 adult subjects, we identified two main strategies that subjects used to generate new hypotheses. One strategy was to search memory and the other was to generalize from the results of previous experiments. We described the former group as searching an hypothesis space, and the latter as searching an experiment space. In a second study, with 10 adults, we investigated how subjects search the hypothesis space by instructing them to state all the hypotheses that they could think of prior to conducting any experiments. Following this phase, subjects were then allowed to conduct experiments. Subjects who could not think of the correct rule in the hypothesis generation phase discovered the correct rule only by generalizing from the results of experiments in the experimental phase. Both studies provide support for the view that scientific reasoning can be characterized as search in two problem spaces. By extending Simon and Lea's (1974) Generalized Rule Inducer, we present a general model of Scientific Discovery as Dual Search (SDDS) that shows how search in two problem spaces (an hypothesis space and an experiment space) shapes hypothesis generation, experimental design, and the evaluation of hypotheses. The model also shows how these processes interact with each other. Finally, we interpret earlier findings about the psychology of scientific reasoning in terms of the SDDS model.

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References

1983Structure‐Mapping: A Theoretical Framework for Analogy*1980Expert and Novice Performance in Solving Physics Problems 1960On the Failure to Eliminate Hypotheses in a Conceptual Task 1987Confirmation, disconfirmation, and information in hypothesis testing.1988Dual Space Search During Scientific Reasoning 1983Structure-mapping: A theoretical framework for analogy 1975The functional equivalence of problem solving skills 1974If you want to get ahead, get a theory

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2000Bridging Research and Practice: A Cognitively Based Classroom Intervention for Teaching Experimentation Skills to Elementary School Children 1997An extended dual search space model of scientific discovery learning 2010Hypothesis generation, sparse categories, and the positive test strategy.2001Note-Taking for Self-Explanation and Problem Solving 2000Designing for Collaborative Discovery Learning 2008Positive transfer and negative transfer/antilearning of problem-solving skills.

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