Beyond curve fitting: A dynamical systems account of exponential learning in a discrete timing task

Yeou Teh Liu, Gottfried Mayer-Kress, Karl M. Newell*

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

29 引文 斯高帕斯(Scopus)

摘要

The authors examined the function for learning a discrete timing task from a dynamical systems perspective rather than solely the traditional curve-fitting viewpoint. Adult participants (N = 8) practiced a single-limb angular movement task of 125 ms over 20° for 200 trials. There was no significant difference in percentage of variance accounted for in 3 parameter exponential and power-law nonlinear fits to the individual and averaged data. The percentage of variance increased in both exponential and power-law equations when the data were averaged over participants and trials. Drawing on a dynamical systems approach to time scales in motor learning and on analysis of the distinctive features of exponential and power-law functions, however, the authors conclude that the exponential is the learning function for that task and that level of practice.

原文英語
頁(從 - 到)197-207
頁數11
期刊Journal of Motor Behavior
35
發行號2
DOIs
出版狀態已發佈 - 2003 6月

ASJC Scopus subject areas

  • 生物物理學
  • 骨科和運動醫學
  • 實驗與認知心理學
  • 認知神經科學

指紋

深入研究「Beyond curve fitting: A dynamical systems account of exponential learning in a discrete timing task」主題。共同形成了獨特的指紋。

引用此