Individual differences in learning to perceive length by dynamic touch: Evidence for variation in perceptual learning capacities

Abstract

Recent studies of perceptual learning have explored and commented on variation in learning trajectories. Although several factors have been suggested to account for this variation, thus far the idea that humans vary in their perceptual learning capacities has received scant attention. In the present experiment, we aimed at providing a detailed picture of the variation in this capacity by investigating the perceptual learning trajectories of a considerable number of participants. The learning process was studied using the paradigm of length perception by dynamic touch. The results showed that there are substantial individual differences in the way perceivers respond to feedback. Indeed, after feedback, the participants' perceptual performances diverged. We conclude that humans vary in their perceptual learning capacities. The implications of this finding for recent discussions on variation in perception are explored.

Self-training of dynamic touch: Striking improves judgment by wielding

“…The robustness of OLS methods to heteroscedasticity guarantees only that they will compute statistics as if error were, in reality, homogeneously distributed between participants, across time, and across measurement, but there is no guarantee against distortion of the actual longitudinal structure (Molenaar, 2008). The individual differences in perceptual learning (Withagen & van Wermeskerken, 2009) suggest heteroscedasticity in the trajectories of perceptual learning. ML estimation controls for heteroscedasticity by estimating random effects for each participant and for the finest-grain by- To quantify this change in discrepancies, we used a growth curve to model, in the first place, a quadratic function of log(I 1 ) [i.e., a function of log(I 1 ) * log(I 1 ); see Table 4] and, in addition, the effects of block, strike, and hadS as they interact with this quadratic relationship.…”

Examination of gaze behaviors under in situ and video simulation task constraints reveals differences in information pickup for perception and action

“…The tendency to average data in statistical analyses may have masked important individual differences in performance (Newell, Liu, & Mayer-Kress, 2001;Withagen & Chemero, 2009). In future research, it might be more illuminating to consider the gaze behaviors of athletes at an individual level of analysis in order to understand the complex interaction of perception, cognition, and action capabilities that each individual exploits during everyday behavior in complex environments (for comparable approaches in the movement and perceptual learning literature, see Liu, Mayer-Kress, & Newell, 2006;Withagen & van Mermeskerken, 2009). …”

Cultural and learning differences in the Judd illusion

“…This raises the issue of interindividual differences in the capacity for perceptual learning. Over the last decade, several ecologically motivated studies have reported considerable individual differences in perceptual learning in Western participants (e.g., Jacobs, Michaels, & Runeson, 2000;Jacobs et al, 2001;Menger & Withagen, 2009;Michaels & de Vries, 1998;Runeson & Andersson, 2007;Withagen & van Wermeskerken, 2009). Participants have been found to vary in the degrees to which they were able to take advantage of feedback in order to attune to more useful informational variables (Withagen & van Wermeskerken, 2009).…”

“…That is, ecological psychologists have explained differences in perceptual accuracy in terms of the detected informational variables (e.g., Jacobs, Runeson, & Michaels, 2001;Michaels & de Vries, 1998;Withagen & van Wermeskerken, 2009). The idea is that informational variables differ in their degrees of usefulness (e.g., Jacobs & Michaels, 2007;Withagen, 2004;Withagen & van der Kamp, 2010).…”