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Poletiek, F. H., & Van Schijndel, T. J. P. (2009). Stimulus set size and statistical coverage of the grammar in artificial grammar learning. Psychonomic Bulletin & Review, 16(6), 1058-1064. doi:10.3758/PBR.16.6.1058.
Abstract
Adults and children acquire knowledge of the structure of their environment on the basis of repeated exposure to samples of structured stimuli. In the study of inductive learning, a straightforward issue is how much sample information is needed to learn the structure. The present study distinguishes between two measures for the amount of information in the sample: set size and the extent to which the set of exemplars statistically covers the underlying structure. In an artificial grammar learning experiment, learning was affected by the sample’s statistical coverage of the grammar, but not by its mere size. Our result suggests an alternative explanation of the set size effects on learning found in previous studies (McAndrews & Moscovitch, 1985; Meulemans & Van der Linden, 1997), because, as we argue, set size was confounded with statistical coverage in these studies. nt]mis|This research was supported by a grant from the Netherlands Organization for Scientific Research. We thank Jarry Porsius for his help with the data analyses. -
Poletiek, F. H. (2009). Popper's Severity of Test as an intuitive probabilistic model of hypothesis testing. Behavioral and Brain Sciences, 32(1), 99-100. doi:10.1017/S0140525X09000454.
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Poletiek, F. H., & Wolters, G. (2009). What is learned about fragments in artificial grammar learning? A transitional probabilities approach. Quarterly Journal of Experimental Psychology, 62(5), 868-876. doi:10.1080/17470210802511188.
Abstract
Learning local regularities in sequentially structured materials is typically assumed to be based on encoding of the frequencies of these regularities. We explore the view that transitional probabilities between elements of chunks, rather than frequencies of chunks, may be the primary factor in artificial grammar learning (AGL). The transitional probability model (TPM) that we propose is argued to provide an adaptive and parsimonious strategy for encoding local regularities in order to induce sequential structure from an input set of exemplars of the grammar. In a variant of the AGL procedure, in which participants estimated the frequencies of bigrams occurring in a set of exemplars they had been exposed to previously, participants were shown to be more sensitive to local transitional probability information than to mere pattern frequencies. -
Poletiek, F. H., & Rassin E. (
Eds. ). (2005). Het (on)bewuste [Special Issue]. De Psycholoog. -
Poletiek, F. H., & Van den Bos, E. J. (2005). Het onbewuste is een dader met een motief. De Psycholoog, 40(1), 11-17.
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Poletiek, F. H. (2005). The proof of the pudding is in the eating: Translating Popper's philosophy into a model for testing behaviour. In K. I. Manktelow, & M. C. Chung (
Eds. ), Psychology of reasoning: Theoretical and historical perspectives (pp. 333-347). Hove: Psychology Press. -
Poletiek, F. H. (2000). De beoordelaar dobbelt niet - denkt hij. Nederlands Tijdschrift voor de Psychologie en haar Grensgebieden, 55(5), 246-249.
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Poletiek, F. H., & Berndsen, M. (2000). Hypothesis testing as risk behaviour with regard to beliefs. Journal of Behavioral Decision Making, 13(1), 107-123. doi:10.1002/(SICI)1099-0771(200001/03)13:1<107:AID-BDM349>3.0.CO;2-P.
Abstract
In this paper hypothesis‐testing behaviour is compared to risk‐taking behaviour. It is proposed that choosing a suitable test for a given hypothesis requires making a preposterior analysis of two aspects of such a test: the probability of obtaining supporting evidence and the evidential value of this evidence. This consideration resembles the one a gambler makes when choosing among bets, each having a probability of winning and an amount to be won. A confirmatory testing strategy can be defined within this framework as a strategy directed at maximizing either the probability or the value of a confirming outcome. Previous theories on testing behaviour have focused on the human tendency to maximize the probability of a confirming outcome. In this paper, two experiments are presented in which participants tend to maximize the confirming value of the test outcome. Motivational factors enhance this tendency dependent on the context of the testing situation. Both this result and the framework are discussed in relation to other studies in the field of testing behaviour.
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