How People Learn to Act on Goals: A New Examination of the Mechanistic Ideomotor Action Account

Dan Sun

Research output: ThesisDoctoral thesis 1 (Research UU / Graduation UU)

Abstract

Humans are agents that engage in intentional action based on the goals or desired outcomes they have in mind. For goal achievement to materialize one needs to know what action causes the desired outcome and how to act on it. A classic question in psychology is how such intentions translate into action. This link between thought and behavior is elegantly explained by the ideomotor (IM) theory, according to which the mere ideation of an outcome would even be enough to set the relevant action in motion. Little is known, however, about the conditions under which action-outcome representations are formed. It is generally assumed this happens whenever people observe events that follow their actions, suggesting that people spontaneously encode these events as outcomes, linking them to the actions that produced them. Yet, this does not always appear to be the case. In the current thesis, we ask the question: “When and how do people actually represent events in the world as outcomes that are the result of their actions?”. What we found is that the automatic spreading of activation via mere imagination should be cautioned; at least, future research should consider the joint impacts of propositions and associations on the ideomotor effects. Upon the broad implication, exploring the factors related to causal inferences allow us to investigate the mechanism of information processing when interacting with other people or with the environment.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Utrecht University
Supervisors/Advisors
  • Aarts, Henk, Primary supervisor
  • Custers, Ruud, Co-supervisor
Award date21 Jun 2022
Place of PublicationUtrecht
Publisher
Print ISBNs978-90-393-7482-5
DOIs
Publication statusPublished - 21 Jun 2022

Keywords

  • Action control
  • Goal-directed behavior
  • Ideomotor
  • Propositional learning
  • Implicit learning
  • Automaticity

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