Abstract
Given 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.
Recommended Citation
Osman, Magda
(2008)
"Seeing is as Good as Doing,"
The Journal of Problem Solving: Vol. 2
:
Iss.
1,
Article 3.
DOI: 10.7771/1932-6246.1029
Available at:
https://docs.lib.purdue.edu/jps/vol2/iss1/3