Publications

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  • Lai, J., & Poletiek, F. H. (2013). How “small” is “starting small” for learning hierarchical centre-embedded structures? Journal of Cognitive Psychology, 25, 423-435. doi:10.1080/20445911.2013.779247.

    Abstract

    Hierarchical centre-embedded structures pose a large difficulty for language learners due to their complexity. A recent artificial grammar learning study (Lai & Poletiek, 2011) demonstrated a starting-small (SS) effect, i.e., staged-input and sufficient exposure to 0-level-of-embedding exemplars were the critical conditions in learning AnBn structures. The current study aims to test: (1) a more sophisticated type of SS (a gradually rather than discretely growing input), and (2) the frequency distribution of the input. The results indicate that SS optimally works under other conditional cues, such as a skewed frequency distribution with simple stimuli being more numerous than complex ones.
  • Warmelink, L., Vrij, A., Mann, S., Leal, S., & Poletiek, F. H. (2013). The effects of unexpected questions on detecting familiar and unfamiliar lies. Psychiatry, Psychology and law, 20(1), 29-35. doi:10.1080/13218719.2011.619058.

    Abstract

    Previous research suggests that lie detection can be improved by asking the interviewee unexpected questions. The present experiment investigates the effect of two types of unexpected questions: background questions and detail questions, on detecting lies about topics with which the interviewee is (a) familiar or (b) unfamiliar. In this experiment, 66 participants read interviews in which interviewees answered background or detail questions, either truthfully or deceptively. Those who answered deceptively could be lying about a topic they were familiar with or about a topic they were unfamiliar with. The participants were asked to judge whether the interviewees were lying. The results revealed that background questions distinguished truths from both types of lies, while the detail questions distinguished truths from unfamiliar lies, but not from familiar lies. The implications of these findings are discussed.
  • Lai, J., & Poletiek, F. H. (2010). The impact of starting small on the learnability of recursion. In S. Ohlsson, & R. Catrambone (Eds.), Proceedings of the 32rd Annual Conference of the Cognitive Science Society (CogSci 2010) (pp. 1387-1392). Austin, TX, USA: Cognitive Science Society.
  • Van den Bos, E., & Poletiek, F. H. (2010). Structural selection in implicit learning of artificial grammars. Psychological Research-Psychologische Forschung, 74(2), 138-151. doi:10.1007/s00426-009-0227-1.

    Abstract

    In the contextual cueing paradigm, Endo and Takeda (in Percept Psychophys 66:293–302, 2004) provided evidence that implicit learning involves selection of the aspect of a structure that is most useful to one’s task. The present study attempted to replicate this finding in artificial grammar learning to investigate whether or not implicit learning commonly involves such a selection. Participants in Experiment 1 were presented with an induction task that could be facilitated by several characteristics of the exemplars. For some participants, those characteristics included a perfectly predictive feature. The results suggested that the aspect of the structure that was most useful to the induction task was selected and learned implicitly. Experiment 2 provided evidence that, although salience affected participants’ awareness of the perfectly predictive feature, selection for implicit learning was mainly based on usefulness.

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  • Poletiek, F. H. (2008). Het probleem van escalerende beschuldigingen [Boekbespreking van Kindermishandeling door H. Crombag en den Hartog]. Maandblad voor Geestelijke Volksgezondheid, (2), 163-166.
  • Van den Bos, E., & Poletiek, F. H. (2008). Effects of grammar complexity on artificial grammar learning. Memory & Cognition, 36(6), 1122-1131. doi:10.3758/MC.36.6.1122.

    Abstract

    The present study identified two aspects of complexity that have been manipulated in the implicit learning literature and investigated how they affect implicit and explicit learning of artificial grammars. Ten finite state grammars were used to vary complexity. The results indicated that dependency length is more relevant to the complexity of a structure than is the number of associations that have to be learned. Although implicit learning led to better performance on a grammaticality judgment test than did explicit learning, it was negatively affected by increasing complexity: Performance decreased as there was an increase in the number of previous letters that had to be taken into account to determine whether or not the next letter was a grammatical continuation. In particular, the results suggested that implicit learning of higher order dependencies is hampered by the presence of longer dependencies. Knowledge of first-order dependencies was acquired regardless of complexity and learning mode.
  • Van den Bos, E., & Poletiek, F. H. (2008). Intentional artificial grammar learning: When does it work? European Journal of Cognitive Psychology, 20(4), 793-806. doi:10.1080/09541440701554474.

    Abstract

    Actively searching for the rules of an artificial grammar has often been shown to produce no more knowledge than memorising exemplars without knowing that they have been generated by a grammar. The present study investigated whether this ineffectiveness of intentional learning could be overcome by removing dual task demands and providing participants with more specific instructions. The results only showed a positive effect of learning intentionally for participants specifically instructed to find out which letters are allowed to follow each other. These participants were also unaffected by a salient feature. In contrast, for participants who did not know what kind of structure to expect, intentional learning was not more effective than incidental learning and knowledge acquisition was guided by salience.
  • Wolters, G., & Poletiek, F. H. (2008). Beslissen over aangiftes van seksueel misbruik bij kinderen. De Psycholoog, 43, 29-29.

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