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

TL;DR

This paper presents a comprehensive, empirically grounded decision-based framework for understanding and teaching problem-solving in science and engineering, based on interviews with 52 experts across disciplines.

Contribution

It introduces a novel decision framework of 29 specific decisions that characterize expert problem-solving in science and engineering, grounded in empirical interviews.

Findings

Experts follow 29 key decisions in problem-solving

Decision-making relies on domain-specific predictive models

Framework can guide teaching and assessment of problem-solving

Abstract

A primary goal of science and engineering (S & E) education is to produce good problem solvers, but how to best teach and measure the quality of problem-solving remains unclear. The process is complex, multifaceted, and not fully characterized. Here we present a theoretical framework of the S & E problem-solving process as a set of specific interlinked decisions. This theory is empirically grounded and describes the entire process. To develop this theory, we interviewed 52 successful scientists and engineers (experts) spanning different disciplines, including biology and medicine. They described how they solved a typical but important problem in their work, and we analyzed the interviews in terms of decisions made. Surprisingly, we found that across all experts and fields, the solution process was framed around making a set of just twenty-nine specific decisions. We also found that the process of making those discipline-general decisions (selecting between alternative actions) relied heavily on domain-specific predictive models that embodied the relevant disciplinary knowledge. This set of decisions provides a guide for the detailed measurement and teaching of S & E problem-solving. This decision framework also provides a more specific, complete, and empirically based theory describing the practices of science.