Dissertation Information for Frank LeeNAME:
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SCHOOL: ADVISORS: COMMITTEE MEMBERS: MPACT Status: Incomplete - Not_Inspected Title: Does learning of a complex task have to be complex? A study in learning decomposition Abstract: Many theories of skill acquisition have had considerable success in addressing the fine details of learning in relatively simple tasks, but will they scale up to complex tasks that are typical of human learning in the real world? Some theories argue for scalability by making the implicit assumption that complex tasks consist of many smaller parts which are being learned according to basic learning principles. Surprisingly, there has been rather sparse empirical testing of this crucial assumption. In this dissertation, I examine this hypothesis directly by decomposing learning in the Kanfer-Ackerman Air-Traffic Controller (Ackerman, 1989) task, from the learning at the global level all the way down to the learning at the keystroke level. First, I reanalyze the data from Ackerman (1988) and show that the learning in this complex task does indeed reflect the learning of the smaller parts. Second, in a follow up eye-tracking experiment, I show that a large portion of the learning at the keystroke level reflects people learning where not to look. And third, I present an ACT-R/PM (Byrne & Anderson, 1998) model of the asymptotic performance in the KA-ATC task. |
MPACT Scores for Frank LeeA = 0 Advisors and Advisees Graph |