Article

The use of control groups in artificial grammar learning.

Department of Psychology, University of Bern, Bern, Switzerland.
The Quarterly Journal of Experimental Psychology A (Impact Factor: 2.45). 02/2003; 56(1):97-115. DOI: 10.1080/02724980244000297
Source: PubMed

ABSTRACT Experimenters assume that participants of an experimental group have learned an artificial grammar if they classify test items with significantly higher accuracy than does a control group without training. The validity of such a comparison, however, depends on an additivity assumption: Learning is superimposed on the action of non-specific variables-for example, repetitions of letters, which modulate the performance of the experimental group and the control group to the same extent. In two experiments we were able to show that this additivity assumption does not hold. Grammaticality classifications in control groups without training (Experiments 1 and 2) depended on non-specific features. There were no such biases in the experimental groups. Control groups with training on randomized strings (Experiment 2) showed fewer biases than did control groups without training. Furthermore, we reanalysed published research and demonstrated that earlier experiments using control groups without training had produced similar biases in control group performances, bolstering the finding that using control groups without training is methodologically unsound.

0 Bookmarks
 · 
75 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The literature on repetition processing reveals an intriguing paradox between the particular salience of repetitions, which makes them easy to learn, and a tendency to avoid them when generating sequences. The aim of this experiment was to study the extent to which children can learn to produce these avoided behaviours by means of an artificial grammar paradigm using generation tests with implicit or explicit instructions. The analysis of the control group's performance confirmed the presence of a spontaneous tendency to avoid generating repetitions. A comparison with chance revealed that the children learned to produce repetitions in the explicit test but not in the implicit test. However, a comparison with the control group showed that learning nonetheless occurred in the experimental group with the implicit test. The discussion focused on this antirepetition behavioural bias and how it interacted with the type of information processes elicited by the tests selected for assessing implicit learning effects.
    Quarterly journal of experimental psychology (2006) 03/2011; 64(6):1173-86. · 1.82 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Humans have remarkable statistical learning abilities for verbal speech-like materials and for nonverbal music-like materials. Statistical learning has been shown with artificial languages (AL) that consist of the concatenation of nonsense word-like units into a continuous stream. These ALs contain no cues to unit boundaries other than the transitional probabilities between events, which are high within a unit and low between units. Most AL studies have used units of regular lengths. In the present study, the ALs were based on the same statistical structures but differed in unit length regularity (i.e., whether they were made out of units of regular vs. irregular lengths) and in materials (i.e., syllables vs. musical timbres), to allow us to investigate the influence of unit length regularity on domain-general statistical learning. In addition to better performance for verbal than for nonverbal materials, the findings revealed an effect of unit length regularity, with better performance for languages with regular- (vs. irregular-) length units. This unit length regularity effect suggests the influence of dynamic attentional processes (as proposed by the dynamic attending theory; Large & Jones (Psychological Review 106: 119-159, 1999)) on domain-general statistical learning.
    Psychonomic Bulletin & Review 08/2012; · 2.99 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Past research has demonstrated that infants can rapidly extract syllable distribution information from an artificial language and use this knowledge to infer likely word boundaries in speech. However, artificial languages are extremely simplified with respect to natural language. In this study, we ask whether infants' ability to track transitional probabilities between syllables in an artificial language can scale up to the challenge of natural language. We do so by testing both 5.5- and 8-month-olds' ability to segment an artificial language containing four words of uniform length (all CVCV) or four words of varying length (two CVCV, two CVCVCV). The transitional probability cues to word boundaries were held equal across the two languages. Both age groups segmented the language containing words of uniform length, demonstrating that even 5.5-month-olds are extremely sensitive to the conditional probabilities in their environment. However, neither age group succeeded in segmenting the language containing words of varying length, despite the fact that the transitional probability cues defining word boundaries were equally strong in the two languages. We conclude that infants' statistical learning abilities may not be as robust as earlier studies have suggested.
    Developmental Science 03/2010; 13(2):339-45. · 3.89 Impact Factor

Full-text (2 Sources)

View
30 Downloads
Available from
Jun 5, 2014