Different levels of statistical learning - Hidden potentials of sequence learning tasks
Autoři:
Emese Szegedi-Hallgató aff001; Karolina Janacsek aff004; Dezso Nemeth aff004
Působiště autorů:
Doctoral School of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
aff001; Institute of Psychology, Faculty of Humanities, University of Szeged, Szeged, Hungary
aff002; Prevention of Mental Illnesses Interdisciplinary Research Group, University of Szeged, Szeged, Hungary
aff003; Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
aff004; Brain, Memory and Language Research Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary
aff005; Lyon Neuroscience Research Center, Université de Lyon, Lyon, France
aff006
Vyšlo v časopise:
PLoS ONE 14(9)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0221966
Souhrn
In this paper, we reexamined the typical analysis methods of a visuomotor sequence learning task, namely the ASRT task (J. H. Howard & Howard, 1997). We pointed out that the current analysis of data could be improved by paying more attention to pre-existing biases (i.e. by eliminating artifacts by using new filters) and by introducing a new data grouping that is more in line with the task’s inherent statistical structure. These suggestions result in more types of learning scores that can be quantified and also in purer measures. Importantly, the filtering method proposed in this paper also results in higher individual variability, possibly indicating that it had been masked previously with the usual methods. The implications of our findings relate to other sequence learning tasks as well, and opens up opportunities to study different types of implicit learning phenomena.
Klíčová slova:
Biology and life sciences – Neuroscience – Cognitive science – Cognitive psychology – Learning – Human learning – Attention – Cognitive neuroscience – Reaction time – Learning and memory – Psychology – Social sciences – Research and analysis methods – Database and informatics methods – Bioinformatics – Sequence analysis – Research assessment – Research validity – Mathematical and statistical techniques – Statistical methods – Physical sciences – Mathematics – Statistics – Statistical data
Zdroje
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