title: Modes of knowledge acquisition and retrieval in artificial grammar learning.
abstract: The aim of this study was to conceptualize artificial grammar learning (AGL) in terms of two orthogonal dimensions--the mode of knowledge acquisition and the mode of knowledge retrieval--as was done by Perlman and Tzelgov (2006) for sequence learning. Experiment 1 was carried out to validate our experimental task; Experiments 2-4 tested, respectively, performance in the intentional, incidental, and automatic retrieval modes, for each of the three modes of acquisition. Furthermore, signal detection theory (SDT) was used as an analytic tool, consistent with our assumption that the processing of legality-relevant information involves decisions along a continuous dimension of fluency. The results presented support the analysis of AGL in terms of the proposed dimensions. They also indicate that knowledge acquired during training may include many aspects of the presented stimuli (whole strings, relations among elements, etc.). The contribution of the various components to performance depends on both the specific instruction in the acquisition phase and the requirements of the retrieval task.
authors.affiliation: Achva Academic College, Shikmim, Israel. yaelp@bgu.ac.il
authors.forename: Yael
authors.initials: Y
authors.lastname: Poznanski
authors.forename: Joseph
authors.initials: J
authors.lastname: Tzelgov
mesh_terms: D001185:Artificial Intelligence; D001331:Automation; D016001:Confidence Intervals; D006801:Humans; D008037:Linguistics; D011939:Mental Recall / Q000502:physiology*; D009483:Neuropsychological Tests; D017603:Signal Detection, Psychological / Q000502:physiology*; D013334:Students; D014495:Universities; D014706:Verbal Learning / Q000502:physiology*