Phonological awareness & reading Phonological and lexical influences on phonological awareness performance Research supports causal link between and early reading Good good readers Poor poor readers Rebecca B. Volk University of Arizona ASHA 2007 rbvolk@email.arizona.edu Tiffany P. Hogan Less is known about the factors linked to individual differences in the development of Phonological awareness & reading Tests of have been used to identify children who will be at risk for reading impairment Poor poor reader need reading treatment Current Test of Phonological Awareness Over-identify good readers as having poor (Heath & Hogben, 2004) Using data-driven, theory-based selection of test words is likely to improve early detection of reading impairment Theories on the development of phonological deficit hypothesis lexical restructuring model Phonological Deficit Hypothesis (Catts, 1986, 1989; Elbro, 1996; Elbro, Nielsen, & Petersen, 1994) Suggests that deficits in phonological/ sound processing delay the emergence of Problems with perception/storage of phonological information poor formation of sound representations Poor readers are less accurate at discriminating, identifying, and/or repeating the sounds in words 1
Lexical Restructuring Model (Metsala & Walley, 1998) vocabulary growth segmental nature of lexical representations Lexical Restructuring Model (Metsala & Walley, 1998) Few words in the child s lexicon Holistic representations of those words with minimal phonemic information are sufficient to differentiate each word from every other word in the lexicon More and more words enter the lexicon Underlying representations must become more phonemically detailed to differentiate newly learned words from existing words Example illustrates concept of restructuring bat bat pat bat voiced bat voiced pat pat unvoiced 2
bat pat voiced unvoiced Lexical Restructuring Model (Metsala & Walley, 1998) One characteristic associated with changes in the phonemic detail of words Neighborhood density Neighborhood Density Metric for describing similarity amongst words in the lexicon Neighborhood Density Neighbors differ by the subtraction, addition, or substitution of 1 phoneme Neighborhood Density Neighbors differ by the subtraction, addition, or substitution of 1 phoneme many neighbors reside in dense neighborhood cat resides in a dense neighborhood with 27 neighbors Neighborhood Density Neighbors differ by the subtraction, addition, or substitution of 1 phoneme many neighbors reside in dense neighborhood cat resides in a dense neighborhood with 27 neighbors few neighbors reside in sparse neighborhood house resides in a sparse neighborhood with 7 neighbors 3
Neighborhood Density Neighbors differ by the subtraction, addition, or substitution of 1 phoneme many neighbors reside in dense neighborhood cat resides in a dense neighborhood with 27 neighbors few neighbors reside in sparse neighborhood house resides in a sparse neighborhood with 7 neighbors Because words from dense neighborhoods have many neighbors, they contain more phonemic detail in order to differentiate one from another This study tests tenets of the phonological deficit hypothesis and the lexical restructuring model simultaneously Research Questions It is hypothesized that considering both theories in performance will improve the early identification of reading impairments Phonological Deficit Hypothesis: Do test words differing in the type of sound-to-be-deleted differ in accuracy? Lexical Restructuring Model: Do the same tests words differing in neighborhood density differ in accuracy? Are their interactions between sound type and neighborhood density? Participants Methods Typically developing children between the ages of 4 and 6 years from Tucson, Arizona In preschool Middle to high socioeconomic status English only speakers No history of speech and/or language impairment Normal development Hearing WNL Articulation WNL Expressive/receptive vocabulary WNL Nonverbal IQ WNL Phonological awareness/literacy knowledge WNL 4
Task Phonological Awareness Deletion Task Child was asked to repeat a CVC word and then say the word again with a sound deleted creating a CV or VC word (real word) Initial sound deletion Final sound deletion Phoneme Deletion Task Consistently best PA predictor of reading (e.g., Torgesen, Wagner, & Rashotte, 1994) ND is phoneme-based metric Deletion Task Test words: Varied by 1) sound sonority 2) neighborhood density Most sonorous - Dense neighborhood density Least sonorous - Dense neighborhood density Most sonorous - Sparse neighborhood density Least sonorous - Sparse neighborhood density All high frequency (>50) according to adult frequencies (Kucera & Francis, 1967) and/or children frequency databases (Moe, Hopkins, & Rush, 1982). 20 words with initial sound deletion 20 words with final sound deletion Deletion Task Neighborhood density Lexical influences Dense M = 20.05; SD = 2.59 Sparse M = 7.45; SD = 0.44 Sound sonority Phonological influences Sound to be deleted was either a highly sonorous sound or a less sonorous sound Sound Sonority Sonority: resonant property that somewhat corresponds to its degree of constriction during production (Chin, 1996) Highly sonorous: more vowel-like Least sonorous: less vowel-like Sonority Hierarchy Deletion Task Least sonorous 7 = voiceless stops/affricates 6 = voiced stops/affricates 5 = voiceless fricatives 4 = voiced fricatives 3 = nasal 2 = liquids 1 = glides 0 = vowels Most sonorous High sonority Dense wall Target sound: /w/ Sonority: 1 Density: 23 Low sonority - Dense cat Target sound: /k/ Sonority: 7 Density: 27 High sonority Sparse wheel Target sound: /w/ Sonority: 1 Density: 6 Low sonority Sparse coat Target sound: /k/ Sonority: 7 Density: 9 5
Task Details Presented by the computer to minimize presentation differences across subjects Initial and final sound deletion blocks Initial vs. Final Deletion blocks order of presentation randomized between subject Randomized test words within initial vs. final deletion blocks Initial Deletion Task Example Low sonority - Dense cat Research Questions Results Phonological Deficit Hypothesis: Do test words differing in the type of sound-to-be-deleted differ in accuracy? Lexical Restructuring Model: Do the same tests words differing in neighborhood density differ in accuracy? Are their interactions between sound type and neighborhood density? Predictions Phonological influences Most Sonorous sounds 1) may be harder to delete compared to less sonorous sounds because they are vowel-like co-articulation 2) may be easier to delete compared to less sonorous sounds because they are vowel-like able to elongate and hold in memory Predictions Lexical influences Based on the lexical restructuring model, it is predicted that test items from dense neighborhoods will be more accurate than those from sparse neighborhoods Dense words have more phonemic detail due to restructuring 6
Preliminary Findings Data collection is still underway N = 4 participants 2 Male; 2 Female 4;11 5;7 Preliminary Findings Initial Sound Deletion Sonority Most sonorous sounds easier to delete Able to elongate and hold in memory Neighborhood Density No effect Interaction No interaction Preliminary Findings Final Sound Deletion Sonority Most sonorous sounds easier to delete Able to elongate and hold in memory Neighborhood Density No effect Interaction Most sonorous sounds = no neighborhood density effects Least sonorous = dense easier than sparse Implications of Preliminary Findings Need to collect more data to confirm trends Supports sonority as metric for test word difficulty Lexical restructuring model predictions supported for final sound Positional effects present Initial sound deletion may have restructuring ceiling effect (Storkel, 2002) Future Directions Lexicality Picture vs. No picture conditions Real words vs. nonwords Orthography influences Influence of letter knowledge on PA (e.g., Tyler & Burnham, 2006 and Castle, Holmes, Neath, & Kinoshita, 2003) Task Influences Odd-one-out Acknowledgements Research supported by: ASHA Advancing Academic Research Careers (AARC) Award PI: Hogan International Dyslexia Association PI: Hogan Thank you to: Mary Alt Elise Benadom Tarynn Ciechoski Marianne Cracovaner Analydia Gonzales Tina Meyers Serena Singh L4 Lab: Language, Literacy, Lexicon, and Learning 7
References Subject Info Castle, A., Holmes, V.M., Neath, J., Kinoshita, S. (2003). How does orthographic knowledge influence performance on task? The Quarterly Journal of Experimental Psychology, 56, 445-467. Catts, H. W. (1986). Speech production/phonological deficits in reading disordered children. Journal of Learning Disabilities, 19, 504-508. Catts, H. W. (1989). Speech production deficits in developmental dyslexia. Journal of Speech and Hearing Disorders, 54, 422-428. Catts, H., Wilcox, K., Wood-Jackson, C., Larrivee, L., & Scott, V. (1996). Toward an understanding of. In C.K. Leong & R.M. Joshi (Eds.). Cross-language studies of learning to read and spell: Phonologic and orthographic Subject Gender Age GFTA-2 (Per) >32 nd ROAS (NIX) EO (SS) RO (SS) TOPEL-PK (SS) TOPEL- PA (SS) processing, Kluwer Academic Publishers. Chin, S.B. (1996). The role of the sonority hierarchy in delayed phonological systems. In T.W. Powell (Ed.), Pathologies of speech and language: Contribution of clinical phonetics and linguistics (pp. 109-117). New Orleans, LA: International Clinical Phonetics and Linguistics Association. Elbro, C. (1996). Early linguistic abilities and reading development: A review and hypothesis. Reading and Writing: An interdisciplinary Journal, 8, 453-485. Patest1 Male 5;3 52 116 111 117 105 119 Elbro, C., Neilsen, I., & Petersen, D. K. (1994). Dyslexia in adults: Evidence for deficits in non-word reading and in the phonological representation of lexical items. Annals of Dyslexia, 44, 205-226. Heath, S. & Hogben, J. (2004). Cost-effective prediction of reading difficulties. Journal of Speech, Language, & Research, 47, 751-765. Patest2 Female 4;11 44 98 99 118 119 101 Hogan, T.P., Catts, H.W., & Storkel, H.L. (2007). Phonological lexical processing and word learning in preschool children differing in. Manuscript in preparation. Kucera, H., & Francis, N. (1967). Computational analysis of present-day American English. Providence, RD: Brown University Press. Metsala, J.L., & Walley, A.C. (1998). Spoken vocabulary growth and the segmental restructuring of lexical representations: Precursors to phonemic awareness and early reading ability. In J.L. Metsala & L.C. Ehri (Eds.), Word recognition in Patest3 Female 5;7 78 92 99 87 106 110 beginning literacy (pp. 89-120). Mahwah, NJ: Lawrence Erlbaum Associates. Moe, A. J., Hopkins, C. J., & Rush, R. T. (1982). The vocabulary of first-grade children. Springfield, IL: Thomas. Storkel, H. L. (2002). Restructuring similarity neighborhoods in the developing mental lexicon. Journal of Child Language, 29, 251-274. Torgesen, J. K., Wagner, R. K., & Rashotte, C. A. (1994). Longitudinal studies of phonological processing and reading. Journal of Learning Disabilities, 27, 276-286. Tyler, M. & Burnham, D. (2006). Orthographic influences on phoneme deletion response time. The Quarterly Journal of Experimental Psychology, 59, 2010-2031. Patest16 Male 5;3 48 140 135 122 114 N/A Initial Deletion Task High sonority Dense wall High sonority Sparse wheel Low sonority - Dense cat Low sonority Sparse coat 8