title: Beyond curve fitting: a dynamical systems account of exponential learning in a discrete timing task.
abstract: 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 degrees 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.
authors.affiliation: Department of Physical Education, Taiwan Normal University, Taiwan.
authors.forename: Yeou-Teh
authors.initials: YT
authors.lastname: Liu
authors.forename: Gottfried
authors.initials: G
authors.lastname: Mayer-Kress
authors.forename: Karl M
authors.initials: KM
authors.lastname: Newell
mesh_terms: D005260:Female; D006801:Humans; D007858:Learning; D008297:Male; D008954:Models, Biological; D009048:Motor Skills / Q000502:physiology*; D011187:Posture; D013647:Task Performance and Analysis; D013997:Time Factors