Analogical problem solving

Gick, Mary L.; Holyoak, Keith J.

doi:10.1016/0010-0285(80)90013-4

Cited by 1,990 publications

(1,376 citation statements)

References 10 publications

(3 reference statements)

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“…We theorize that it is a determinant of relational transfer (Forbus et al 1995). Relational transferretrieving a prior situation that shares relational structure with the current situation -is generally quite poor (compared to retrieval based on surface matches), even for adults who have no trouble recognizing the relational match when both items are present (Gentner et al 1993;Gick and Holyoak 1980;Ross 1987). We suggest that this is in part because relational information is typically encoded in a more context-dependent manner than is object information (Asmuth and Gentner 2005;Gentner 1981c;Gentner and France 1988).…”

Section: How Language Augments Analogical Processingmentioning

confidence: 99%

Mutual bootstrapping between language and analogical processing

Gentner¹,

Christie²

2010

Lang. cogn.

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Section: How Language Augments Analogical Processingmentioning

confidence: 99%

Mutual bootstrapping between language and analogical processing

Gentner¹,

Christie²

2010

Lang. cogn.

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“…In most of Gick and Holyoak's experiments, one or more of the experimental groups was presented with the solution to the AttackDispersion problem, in which a military commander disperses his troops and has them converge on the enemy from several directions. Gick and Holyoak (1980) conclude that presenting the solution to an analogous problem significantly improves the likelihood that students will succeed. However, merely presenting the solution is not sufficient.…”

Section: Analogical Problem Solvingmentioning

confidence: 86%

“…Several researchers have chronicled the approaches that students use in different education-related problem solving contexts (Anderson, Greeno, Kline, & Neves, 1981;Carbonell, 1982;Gentner & Holyoak, 1997;Gick & Holyoak, 1980, 1983Polya, 1945). In particular, these scholars examined the ways that students leverage similarities between a prior problem, or solution, and the current problem, in order to formulate a solution.…”

Section: Analogical Problem Solvingmentioning

confidence: 99%

“…In particular, these scholars examined the ways that students leverage similarities between a prior problem, or solution, and the current problem, in order to formulate a solution. Foundational work by Gick & Holyoak (1980, 1983 coined the term ''analogical problem solving,'' and influenced several later instantiations of analogical problem solving (e.g., case-based reasoning (Kolodner, 1992) and learning-by-analogy (Carbonell, 1982;Gentner & Holyoak, 1997)). The initial research on analogical problem solving was based on problem solving scenarios in which participants were provided with a story whose essence could be used to solve a target problem.…”

Section: Analogical Problem Solvingmentioning

confidence: 99%

“…Hence, even though a student may be able to retrieve a prior experience, they may not know when, or how, to use it. Similarly, students may be able to use a prior experience that they did not spontaneously generate, which is what frequently occurred in Gick and Holyoak (1980). Gick and Holyoak (1983) take the research one step further by disentangling the role that schema abstraction plays in predicting student success on the radiation problem.…”

Section: Analogical Problem Solvingmentioning

confidence: 99%

See 2 more Smart Citations

Reasoning Strategies in the Context of Engineering Design with Everyday Materials

Worsley¹,

Blikstein

2017

Journal of Pre-College Engineering Education Research (J-PEER)

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Abstract''Making'' represents an increasingly popular label for describing a form of engineering design. While making is growing in popularity, there are still open questions about the strategies that students are using in these activities. Assessing and improving learning in making/ engineering design contexts require that we have a better understanding of where students' ideas are coming from and a better way to characterize student progress in open-ended learning environments. In this article, we use a qualitative analysis of students' responses (N 5 13) in order to identify the origins of their ideas. Four strategies emerged from this analysis: unexplained reasoning; materials-based reasoning; example-based reasoning; and principle-based reasoning. We examine key characteristics of each strategy and how each strategy relates to learning and expertise through in-depth case studies. Furthermore, we identify how these four strategies are a complement to prior work on analogical problem solving and creativity, and offer a number of unique contributions that are particularly relevant for engineering education. Finally, we include two coding schemes that can be used to classify students' responses. Studying reasoning strategies in this way is a fruitful means for characterizing student learning in complex learning environments. Moreover, understanding reasoning strategies impacts the nature of student-teacher discussions and informs how to help students progress most effectively.

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Minority influence and optimal problem solving

Martin

Hewstone

1999

Eur. J. Soc. Psychol.

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An analogous thinking task was used to test Nemeth's Convergent±Divergent theory of majority and minority in¯uence. Participants read a (base) problem and one of three solutions (one of which is considered the`best' solution). They then generated solutions to a second (target) problem which shared similar structural features to the ®rst problem. Due to the similarities between problems, the solution given to the ®rst problem can be used as an analogy in solving the second. In contrast to Nemeth's theory, when the solution to the base problem was endorsed by a numerical majority there was not an increase in analogy-transfer in solving the target problem. However, in support of Nemeth's theory, when the base solution was supported by a numerical minority then the participants were more likely to generate the`best' solution to the target problem regardless of which base solution they were given.

show abstract

Analogical problem solving

Cited by 1,990 publications

References 10 publications

Mutual bootstrapping between language and analogical processing

Mutual bootstrapping between language and analogical processing

Reasoning Strategies in the Context of Engineering Design with Everyday Materials

Minority influence and optimal problem solving

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