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dc.contributor.authorOsman, M
dc.date.accessioned2010-03-29T12:49:56Z
dc.date.available2008
dc.date.available2010-03-29T12:49:56Z
dc.date.issued2010-03-29T12:49:56Z
dc.identifierhttp://www.sbcs.qmul.ac.uk/staff/magdaosman.html
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/128
dc.description.abstractGiven the privileged status claimed for active learning in a variety of domains (visuomotor learning, causal induction, problem solving, education, skill learning), the present study examines whether action-based learning is a necessary, or a suffi cient, means of acquiring the relevant skills needed to perform a task typically described as requiring active learning. To achieve this, the present study compares the effects of action-based and observation-based learning when controlling a complex dynamic task environment (N = 96). Both action- and observation-based individuals learn either by describing the changes in the environment in the form of a conditional statement, or not. The study reveals that for both active and observational learners, advantages in performance (p < .05), accuracy in knowledge of the task (p < .05), and self-insight (p < .05) are found when learning is based on inducing rules from the task environment. Moreover, the study provides evidence suggesting that, given task instructions that encourage rule-based knowledge, both active and observation-based learning can lead to high levels of problem solving skills in a complex dynamic environment.
dc.relation.isreplacedby123456789/1020
dc.relation.isreplacedbyhttp://qmro.qmul.ac.uk/jspui/handle/123456789/1020
dc.subjectComplex Control, Metacognition
dc.titleSeeing is as Good as Doing
pubs.author-urlhttp://www.sbcs.qmul.ac.uk/staff/magdaosman.html


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