UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Statistical and explicit learning of graphotactic patterns with no phonological counterpart: Evidence from artificial lexicon studies with 6– to 7-year-olds and adults

Singh, Felicia Daniela; (2021) Statistical and explicit learning of graphotactic patterns with no phonological counterpart: Evidence from artificial lexicon studies with 6– to 7-year-olds and adults. Doctoral thesis (Ph.D), UCL (University College London). Green open access

[thumbnail of Daniela_Singh_Thesis_2021_Corrections.pdf]
Preview
Text
Daniela_Singh_Thesis_2021_Corrections.pdf

Download (3MB) | Preview

Abstract

Children are powerful statistical spellers: They can learn novel written patterns with phonological counterparts under experimental conditions, via implicit learning processes, akin to “statistical learning” processes established for spoken language acquisition. Can these mechanisms fully account for children’s knowledge of written patterns? How does this ability relate to literacy measures? How does it compare to explicit learning? This thesis addresses these questions in a series of artificial lexicon experiments, inducing graphotactic learning under incidental and explicit conditions, and comparing it with measures of literacy. The first experiment adapted an existing design (Samara & Caravolas, 2014), with the goal of searching for stronger effects. Subsequent experiments address a further limitation: Previous studies assessed learning of spelling rules which have counterparts in spoken language; however, while this is also the case for some naturalistic spelling rules (e.g., English phonotactics prohibit word initial /ŋ/ and accordingly, written words cannot begin with ng), there are also purely visual constraints (graphotactics) (e.g., gz is an illegal spelling of a frequent word-final sound combination in English: *bagz). Can children learn patterns unconfounded from correlated phonotactics? In further experiments, developing and skilled spellers were exposed to patterns replete of phonotactic cues. In post-tests, participants generalized over both positional constraints embedded in semiartificial strings, and contextual constraints created using homophonic non-word stimuli. This was demonstrated following passive exposure and even under meaningful (word learning) conditions, and success in learning graphotactics was not hindered by learning word meanings. However, the effect sizes across this thesis remained small, and the hypothesized positive associations between learning performance under incidental conditions and literacy measures were never observed. This relationship was only found under explicit conditions, when pattern generalization benefited. Investigation of age effects revealed that adults and children show similar patterns of learning but adults learn faster from matched text.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Statistical and explicit learning of graphotactic patterns with no phonological counterpart: Evidence from artificial lexicon studies with 6– to 7-year-olds and adults
Event: UCL (University College London)
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Copyright © The Author 2021. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
Keywords: statistical learning, explicit instruction, graphotactics, Bayes factors, word learning
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10129656
Downloads since deposit
291Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item