When novices surpass experts: The difficulty of a task may increase with expertise.
Abstract
A detailed look at the representations constructed by novice and expert computer programmers is presented. The issue is addressed by looking at the interaction between the representation naturally formed by programmers at each level of expertise and .an experimentally induced abstract or concrete mental set. The data suggest that, in the absence of an experimentally provided set, experts form abstract representations (denned here as what a program does), whereas novices form concrete representations (defined here as how a program functions). The data also suggest that appropriate sets can aid each group to form the representation not natural to them; however, these representations are not as stable as the preferred ones. The generality of the findings and the utility of the experts' representation of a task is discussed both in relation to computer programming and to problem solving in other domains. In the semantically rich domains of skilled problem solving (Bhaskar & Simon, 1977), the difference between experts and nonexperts is both qualitative and quantitative. Not only do experts perform better than novices on quantitative measures of skill but experimental manipulations also uncover qualitative differ- ences in the representations and strategies used by experts. Repeatedly, we find that the work- ing representations of experts are abstract conceptualizations of the original problem statement, whereas those of novices are less abstract and focus more on surface features of the problem. For example, in a recent ex- periment, Adelson (1981c) found that expert programmers used abstract, conceptually based representations when attempting to re- call programming material, whereas novices used syntactically based representations. Using a multitrial free-recall procedure, Adelson asked novice and expert programmers to recall a set of 16 lines of programming code that had been presented in random order. Although the subjects had not been told that the 16 lines
Cites (1)
- Perception in chessChase, William G., Simon, Herbert A. · 1973 · Cognitive Psychology
Cited by (6)
- Dimensions of Consumer ExpertiseAlba, Joseph W., Hutchinson, J. Wesley · 1987 · Journal of Consumer Research
- EXPERT AND EXCEPTIONAL PERFORMANCE: Evidence of Maximal Adaptation to Task ConstraintsEricsson, K. A., Lehmann, A. C. · 1996 · Annual Review of Psychology
- Stimulus structures and mental representations in expert comprehension of computer programsPennington, Nancy · 1987 · Cognitive Psychology
- Relationships between reading, tracing and writing skills in introductory programmingLopez, Mike, Whalley, Jacqueline, Robbins, Phil, Lister, Raymond · 2008 · Proceedings of the Fourth international Workshop on Computing Education Research
- The forensic confirmation bias: A comparison between experts and novicesvan den Eeden, Claire A. J., de Poot, Christianne J., van Koppen, Peter J. · 2019 · Journal of Forensic Sciences
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: When novices surpass experts: The difficulty of a task may increase with expertise. https://app.cochat.ai/papers/10.1037//0278-7393.10.3.483
- The paper
- Adelson, B. (1984). When novices surpass experts: The difficulty of a task may increase with expertise. Journal of Experimental Psychology Learning Memory and Cognition. https://doi.org/10.1037//0278-7393.10.3.483
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.