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Different levels of statistical learning-hidden potentials of sequence learning tasks

Different levels of statistical learning-hidden potentials of sequence learning tasks

Szegedi-Hallgató, Emese, Janacsek, Karolina and Nemeth, Dezso (2019) Different levels of statistical learning-hidden potentials of sequence learning tasks. PloS one, 14 (9):e0221966. ISSN 1932-6203 (doi:https://doi.org/10.1371/journal.pone.0221966)

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Abstract

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.

Item Type: Article
Uncontrolled Keywords: statistical learning, sequence learning
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Faculty / Department / Research Group: Faculty of Education, Health & Human Sciences
Faculty of Education, Health & Human Sciences > Department of Psychology, Social Work & Counselling
Last Modified: 16 Jan 2020 16:33
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/25766

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