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Related Experiment Video

Updated: Oct 24, 2025

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A Detailed Characterization of the Expert Problem-Solving Process in Science and Engineering: Guidance for Teaching

Argenta M Price1, Candice J Kim2,3, Eric W Burkholder1

  • 1Department of Physics, Stanford University, Stanford, CA 94305.

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Summary

Scientists and engineers solve problems by making 29 specific decisions, a process grounded in domain-specific knowledge. This framework aids in teaching and measuring science and engineering (S&E) problem-solving skills.

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Area of Science:

  • Science and Engineering Education
  • Cognitive Science

Background:

  • Effective problem-solving is a key goal in science and engineering (S&E) education.
  • The complex nature of S&E problem-solving hinders clear pedagogical and assessment strategies.

Purpose of the Study:

  • To characterize the S&E problem-solving process.
  • To develop an empirically grounded framework of decisions in S&E problem-solving.

Main Methods:

  • Conducted interviews with 52 scientists and engineers across various disciplines.
  • Analyzed interview data to identify and map the decision-making process during problem-solving.

Main Results:

  • Identified a universal framework of 29 specific, interlinked decisions common across different S&E disciplines.
  • Found that discipline-general decision-making relies on domain-specific predictive models embodying disciplinary knowledge.

Conclusions:

  • The decision-making framework provides a guide for measuring and teaching S&E problem-solving.
  • Offers a precise, empirically supported description of scientific practices.