Abstract
ABSTRACTWhile feedback is a key facilitator of learning, researchers have yet to determine the ideal feedback process for optimal performance in learners. The current study investigates the combined effects of ease of decoding, and utility of feedback during learning. Accuracy and rate of learning were recorded alongside changes to the feedback related negativity (FRN), an event‐related potential (ERP) elicited by feedback stimuli. This study investigates the FRN within the context of future‐focused directive feedback (DF), in addition to past‐focused evaluative feedback (EF) typically seen in the neuroscience literature. Results indicate a main effect of utility together with an interaction with ease of decoding on the accuracy data, but only the main effect of utility on learning rate. DF produced an FRN, like EF, which was then larger during high‐utility feedback, specifically following negative EF or when hard‐to‐decode. Implications and future research directions are discussed.
Highlights
While feedback is a key facilitator of learning, researchers have yet to determine the ideal feedback process for optimal performance in learners
High-utility screens contained a green bar behind the feature relevant for flavor preference, while low-utility screens contained a red bar behind an irrelevant feature
EEG Recording and Preprocessing EEG data were recorded from 30 Ag/AgCl electrodes mounted on an elastic cap (Easycap) and positioned according to the extended international 10–20 system, with online reference at FCz and ground at FPz
Summary
Participants Data were collected from 27 volunteers recruited through social media snowballing and through a participant recruitment system (SONA). Participants aimed to ascertain which flavor ice cream various potato head figures ( called “the character”) preferred. This setup allowed for the variation of three different features (hat, eyes or shoes), with three variations each (e.g., black, white or blue shoes) that were systematically varied to create the 27 character images used in this experiment. High-utility screens contained a green bar behind the feature relevant for flavor preference, while low-utility screens contained a red bar behind an irrelevant feature. Instructions noted that green feedback bars indicated a relevant feature, while red bars highlighted an irrelevant feature, but there could be other, noninformative, colors present. After artifact extraction an average of 37.80 (SD 3.10) trials remained in each condition, an appropriate number for FRN analysis (Marco-Pallares, Cucurell, Münte, Strien, & Rodriguez-Fornells, 2011)
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