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Expertise in problem solving

Paper · 1982 · Michelene T. H. Chi, Robert Glaser and Ernest Rees

Summary

This chapter, issued as a Learning Research and Development Center report (LRDC-1981/3, University of Pittsburgh), asks what really separates expert from novice problem solvers. The authors first trace a change of emphasis in cognitive psychology and artificial intelligence. Both fields moved away from general, domain-independent search procedures and toward the content and organization of domain knowledge. As background, they cite chess work by de Groot and Chase & Simon, along with similar findings in electronics and architecture.

They then report eight empirical studies of physics problem solving that compare experts with novices. The methods include think-aloud protocols, problem-sorting tasks and analyses of the knowledge people bring to a problem. The core result is that novices perform worse mainly because their knowledge is thinner and organized differently, not because their processing capacity is weaker.

The work matters because it treats expertise, and by extension intelligence, as rooted in a structured knowledge base. That view implies teaching should build and exercise domain-specific knowledge rather than train general mental skills.

Key points

  • Chess background: after a roughly five-second view of a board, masters recalled real positions much better than novices, but did no better on random boards. Masters' recall chunks held about 3–6 pieces, while novices' held single pieces.
  • Sorting studies (Two–Four): novices grouped physics problems by surface features, whereas experts grouped them by the underlying physics principles.
  • Similar basic architecture: experts and novices preferred about the same number of sorting categories and took similar time to reach a stable sort.
  • Novices' knowledge gaps: weaker novices had deficits in declarative physics knowledge, and novices often lacked knowledge of when a principle applies.
  • Studies Seven–Eight: novices spotted key cues in a problem statement about as well as experts, but failed to draw the further inferences that experts' knowledge structures supply.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Fields, topics and concepts

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Social Sciences · 1,772 worksPsychology · 1,552 worksExperimental and Cognitive Psychology · 870 worksEducation · 203 works

🧭 Topics 1Research subjects and languages the work is about.Reasoning · 1,426 works

💡 Concepts 1Key ideas and methods explained on our concept pages.Artificial intelligence · 49 works

Cite

Cite as Michelene T. H. Chi, Robert Glaser and Ernest Rees. 1982. Expertise in problem solving. Defense Technical Information Center (DTIC).

The paper itself, not this page. BibTeX from the library's record of the work.

@inproceedings{chi1982expertise,
  title = {{Expertise in problem solving}},
  author = {Michelene T. H. Chi, Robert Glaser and Ernest Rees},
  booktitle = {Defense Technical Information Center (DTIC)},
  year = {1982},
  url = {https://eric.ed.gov/?id=ED215899}
}

References

21 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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