Mental models of mechanical systems: Individual differences in qualitative and quantitative reasoning

Hegarty, Mary; Just, Marcel Adam; Morrison, Ian R.

doi:10.1016/0010-0285(88)90019-9

Cited by 58 publications

(43 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hegarty, Just, and Morrison (1988) reported that adults with higher mechanical reasoning ability were better able to discriminate relevant from irrelevant attributes of an illustrated text on a pulley and rope system. Hodgson et al (2000) collected eyetracking data while college students attempted to solve a Tower of London problem.…”

Section: Discussionmentioning

confidence: 99%

Question asking and eye tracking during cognitive disequilibrium: Comprehending illustrated texts on devices when the devices break down

et al. 2005

View full text Add to dashboard Cite

Section: Discussionmentioning

confidence: 99%

Question asking and eye tracking during cognitive disequilibrium: Comprehending illustrated texts on devices when the devices break down

et al. 2005

View full text Add to dashboard Cite

“…As is characteristic of physical problems, there are several ways one might solve this problem depending on one's knowledge state and maturation (e.g., Bruner, 1966;Chi, Feltovich, 8z Glaser, 1981;Larkin, McDermott, Simon, & Simon, 1980;Me.&, 1985;Weld, 1986;White & Frederiksen, 1990). One approach is to use a global level description or rule about the device (e.g., Hegarty, Just, & Morrison, 1988). For example, people could use a parity rule that states, "If there is an odd number of gears in a chain, then the first and last gears turn the same direction."…”

Section: Depiction As a Source Of Evidence For Novel Problemsmentioning

confidence: 99%

Shuttling Between Depictive Models and Abstract Rules: Induction and Fallback

1996

View full text Add to dashboard Cite

When reasoning about physical systems, people sometimes experience the phenomenology of depicting the system's behavior in their imagination (Clement, 1994;disessa, 1993;Hegarty, 1992). Because people do not experience this phenomenology throughout their reasoning, we assume that its onset reflects a functional shift in problem solving strategies. Beginning with this assumption, we consider why and when people use imagistic models to reason about a physical system, and how this imagery becomes related to

show abstract

“…Virtually all of these studies have used verbal materials exclusively; relatively little work has explored the use of visual analogies. Most studies of diagrammatic reasoning have focused on the interpretation of pictures and diagrams that directly represent the information in the problem to be solved (e.g., by using a static picture of a pulley system to infer the direction of motion; see Ferguson & Hegarty, 1995;Funt, 1995;Hegarty, 1991Hegarty, , 1992Hegarty, , 1995Hegarty, Just, & Morrison, 1988). In this line of research, the use of analogy between one problem and another has not been examined.…”

mentioning

confidence: 99%

The use of diagrams in analogical problem solving

2001

View full text Add to dashboard Cite

In four experiments, we examined the impact of perceptual properties on the effectiveness of diagrams in analogical problem solving, using variants of convergence diagrams as source analogues for the radiation problem. Static diagrams representing the initial problematic state (one large line directed at a target) and the final state for a convergence solution (multiple converging lines) were not accessed spontaneously but were often used successfullyonce a hint to consider the diagram had been provided. The inaccessibility of static diagrams was not alleviated by adding additional diagrams to represent intermediate states (Experiment 1), but spontaneous access was improved by augmenting static diagrams with a verbal statement of the convergence principle (Experiment 3). Spontaneous retrieval and noticing were increased markedly by animating displays representing converging forces and thereby encouraging encoding of the lines as indicating motion toward a target (Experiments 3 and 4). However, neither static nor animated diagrams were effective when the arrows were reversed to imply divergence rather than convergence (Experiment 2). The results indicate that when animation encourages the interpretation of a diagram as a helpful source analogue, it can greatly enhance analogical transfer.

show abstract

Mental models of mechanical systems: Individual differences in qualitative and quantitative reasoning

Cited by 58 publications

References 9 publications

Question asking and eye tracking during cognitive disequilibrium: Comprehending illustrated texts on devices when the devices break down

Question asking and eye tracking during cognitive disequilibrium: Comprehending illustrated texts on devices when the devices break down

Shuttling Between Depictive Models and Abstract Rules: Induction and Fallback

The use of diagrams in analogical problem solving

Contact Info

Product

Resources

About