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Explanatory completeness.

Joanna Korman1, Sangeet Khemlani2

  • 1Bentley University, USA.

Acta Psychologica
|August 5, 2020
PubMed
Summary
This summary is machine-generated.

People assess explanation completeness by mentally modeling causes and effects. Explanations requiring multiple causal models are perceived as less complete than those needing only one.

Keywords:
Causal reasoningExplanatory reasoningIncompletenessMental models

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Area of Science:

  • Cognitive Psychology
  • Causal Reasoning

Background:

  • Reasoners perceive explanations as varying in completeness.
  • Existing theories do not fully account for this perceived difference.

Purpose of the Study:

  • To propose and test a novel theory of how people assess explanatory incompleteness.
  • To investigate the role of mental models in evaluating explanations.

Main Methods:

  • Developed a theory where explanations are represented as causal mental models.
  • Conducted four experiments using causal descriptions to elicit single or multiple explanatory models.
  • Assessed participants' judgments of explanatory completeness.

Main Results:

  • Participants consistently preferred explanations requiring a single mental model over those requiring multiple models.
  • This preference was observed in both implicit and explicit completeness assessment tasks.
  • Findings support the theory that gaps in causal relations lead to multiple models and perceived incompleteness.

Conclusions:

  • The proposed theory offers a new framework for understanding the assessment of explanatory completeness.
  • The mental representation of explanations as causal models is crucial for evaluating their completeness.
  • This research sheds light on the cognitive processes underlying causal reasoning and explanation evaluation.