TY - JOUR
T1 - Using information-theoretic measures to characterize the structure of the writing system
T2 - the case of orthographic-phonological regularities in English
AU - Siegelman, Noam
AU - Kearns, Devin M.
AU - Rueckl, Jay G.
N1 - Publisher Copyright:
© 2020, The Psychonomic Society, Inc.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - It is generally well accepted that proficient reading requires the assimilation of myriad statistical regularities present in the writing system, including in particular the correspondences between words' orthographic and phonological forms. There is considerably less agreement, however, as to how to quantify these regularities. Here we present a comprehensive approach for this quantification using tools from Information Theory. We start by providing a glossary of the relevant information-theoretic metrics, with simplified examples showing their potential in assessing orthographic-phonological regularities. We specifically highlight the flexibility of our approach in quantifying information under different contexts (i.e., context-independent and dependent readings) and in different types of mappings (e.g., orthography-to-phonology and phonology-to-orthography). Then, we use these information-theoretic measures to assess real-world orthographic-phonological regularities of 10,093 mono-syllabic English words and examine whether these measures predict inter-item variability in accuracy and response times using available large-scale datasets of naming and lexical decision tasks. Together, the analyses demonstrate how information-theoretical measures can be used to quantify orthographical-phonological correspondences, and show that they capture variance in reading performance that is not accounted for by existing measures. We discuss the similarities and differences between the current framework and previous approaches as well as future directions towards understanding how the statistical regularities embedded in a writing system impact reading and reading acquisition.
AB - It is generally well accepted that proficient reading requires the assimilation of myriad statistical regularities present in the writing system, including in particular the correspondences between words' orthographic and phonological forms. There is considerably less agreement, however, as to how to quantify these regularities. Here we present a comprehensive approach for this quantification using tools from Information Theory. We start by providing a glossary of the relevant information-theoretic metrics, with simplified examples showing their potential in assessing orthographic-phonological regularities. We specifically highlight the flexibility of our approach in quantifying information under different contexts (i.e., context-independent and dependent readings) and in different types of mappings (e.g., orthography-to-phonology and phonology-to-orthography). Then, we use these information-theoretic measures to assess real-world orthographic-phonological regularities of 10,093 mono-syllabic English words and examine whether these measures predict inter-item variability in accuracy and response times using available large-scale datasets of naming and lexical decision tasks. Together, the analyses demonstrate how information-theoretical measures can be used to quantify orthographical-phonological correspondences, and show that they capture variance in reading performance that is not accounted for by existing measures. We discuss the similarities and differences between the current framework and previous approaches as well as future directions towards understanding how the statistical regularities embedded in a writing system impact reading and reading acquisition.
KW - information theory
KW - orthography-to-phonology transparency
KW - print-speech correspondences
KW - reading
KW - word recognition
UR - http://www.scopus.com/inward/record.url?scp=85078611337&partnerID=8YFLogxK
U2 - 10.3758/s13428-019-01317-y
DO - 10.3758/s13428-019-01317-y
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C2 - 31950361
AN - SCOPUS:85078611337
SN - 1554-351X
VL - 52
SP - 1292
EP - 1312
JO - Behavior Research Methods
JF - Behavior Research Methods
IS - 3
ER -