Dual space search during scientific reasoning
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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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The possibility that inquiry-based learning may primarily follow an inductive or deductive reasoning approach is captured in the framework through the use of various sub-phases within the Conceptualization and Investigation phases.
“The possibility that inquiry-based learning may primarily follow an inductive or deductive reasoning approach, as Klahr and Dunbar (1988) discuss, is captured in Fig. 3 through the use of various sub-phases within the Conceptualization and Investigation phases.”
From Phases of inquiry-based learning: Definitions and the inquiry cycle (2015) · cites this paper as Klahr and Dunbar (1988)
The opening summary and §6 describe two strategies for generating hypotheses: drawing on prior knowledge and generalizing from experimental results. This supports the distinction between hypothesis-led and evidence-led inquiry, but the paper does not explicitly characterize them as deductive versus inductive approaches to inquiry-based learning. The Fig. 3 sub-phases are the citing authors’ framework, not a claim attributed to Klahr and Dunbar. (LLM, conf=0.78)
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- Authors
- Klahr, D., & Dunbar, K.
- Affiliations
- Carnegie Mellon University (US)
- Corresponding author
- Klahr, David
- Venue
- Cognitive Science
- Publisher
- Wiley
- Published
- 1988-01
- Volume
- 12
- Issue
- 1
- Pages
- 1-48
- ISSN
- 0364-0213 (ISSN-L)
- 1551-6709
- OpenAlex
- W2131370811
- Cited by
- 1,058
- References
- 7
- Citations by year
- 2026: 30 · 2025: 16 · 2024: 22 · 2023: 19 · 2022: 49 · 2021: 45 · 2020: 48 · 2019: 35 · 2018: 44 · 2017: 37 · 2016: 36 · 2015: 30 · 2014: 44 · 2013: 47 · 2012: 35
- FWCI
- 76.34
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cognitive Science (publishedVersion)
- KiltHub Repository (submittedVersion)
- Topics
- Social Sciences › Education › Science Education and Pedagogy
- Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
- Life Sciences › Neuroscience › Cognitive Neuroscience › Cognitive Science and Education Research
- Keywords
- scientific reasoning, scientific discovery, hypothesis space, hypothesis generation, experimental design, problem space search, rule induction, memory search
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