ACQ Vol 13 no 3 2011

Results Results for all measures and comparisons to the reference data norms for each participant are shown in table 1. Comparisons to the reference data norms are presented with respect to standard deviations for the reference data. Microstructure analysis For the number of C-units, three participants performed within normal limits (WNL), two performed at least one standard deviation (SD) below the SALT database mean, and the eldest participant performed more than two SDs above the mean. For the NDW measure, two participants performed WNL, while two performed at least one SD below the mean and two performed at least two SD below the mean, compared to the reference data base. For MLCU, one participant performed WNL, while four participants performed at least one SD below the mean and one performed at least two SDs below the mean. The adjusted measure for grammatical accuracy, GA-AE, was higher than GA-SAE for five of the six participants, with only one participant’s accuracy remaining the same. The highest increase in GA was seen in P#1, an increase of 56% and the smallest increase of 8% was seen in P#2, from a reported SAE background. The most frequently occurring feature of AE was “reduced past tense markings on verbs” (22 occurrences across participants). Other features present were reduced use of prepositions, verb auxiliaries, copulas, and possessives, and subordinate conjunctions. Less common features of AE were future tense marked with the use of “gonna” and variable past tense marking. Examples are provided in the appendix. Macrostructure analysis Compared to the reference data base, all except one participant performed WNL for the total NSS score. P#3 was an anomaly, scoring much lower than other participants, at least two SDs below the mean. With the exception of P#3, the total NSS scores increased with age. P#3 attained below average scores for each NSS component. Results for the five other participants were more varied and are reported here with key patterns highlighted. For the NSS Introduction component all other participants attained scores WNLs. The two eldest participants gained above average scores for Character development, while all other participant scores were WNL. For Mental states, two participants scored WNLs, one scored at least one SD below the mean and the two eldest participants scored at least two SD below the mean. For Referencing and Cohesion, the two youngest participants scored at least one SD below the mean. P#4 scored at least two SDs above the mean for Referencing while the remaining older participants scored WNLs for Referencing and Cohesion. For Conflict resolution, only the two oldest participants scored WNLs while the two youngest scored at least one SD below the mean and one other participant scored at least two SDs below the mean. For the Conclusion component one participant scored at least one SD below the mean, the youngest and eldest participants scored at least one SD above the mean and the remaining two participants scored WNL. Discussion Within this small study, Aboriginal children identified by their teachers as progressing well at school did not consistently

perform within normal limits on measures of oral narrative microstructure when compared to reference data from the US (Miller & Iglesias, 2008). In contrast, most children performed within normal limits for the total NSS score, a measure of narrative macrostructure, with variable results for the NSS components. Microstructure measures Results suggest a different language profile to the SALT database for Aboriginal children who may be acquiring SAE as a second dialect. Three participants produced narratives of comparable length to the database while one produced a longer narrative and two produced much shorter narratives. On the other hand, lexical diversity was more limited (lower measures for NDW), and syntactic complexity was poorer (lower MLCU). Grammatical accuracy also differed from SAE standards. These findings are congruent with Marinis and Chondrogianni (2010) who showed that children learning a second language required more years of exposure to reach monolingual norms. Reasons for the different language profile may be hypothesised from what is known about Aboriginal culture and language use. Some participants may not have felt fully confident due to unfamiliarity with the task or a person from outside of their cultural community, or unease about telling the examiner something she already knew (Moses & Wigglesworth, 2008; Turnbull, 2002). While “talking less” is often valued more within Aboriginal culture (Malcolm et al., 1999; Moses & Wigglesworth, 2008), shorter stories were not evident for the participants in this study. However, this cultural value may have contributed to lower measures for MLCU. The lower MLCU scores may also have resulted from the reduced use of prepositions, verb auxiliaries, and copulas, which is typical of many forms of AE (e.g., “what you doing?”). The low socioeconomic background of the participants may also have contributed to lower performance on the vocabulary-related microstructure measure, NDW (Hoff & Tian, 2005). Results show that it is important to evaluate GA on the basis of AE features where Aboriginal children have not yet fully acquired SAE. Use of the GA-SAE measure may underestimate the child’s linguistic proficiency. A comparison of two GA measures may provide a means of measuring progress towards competency in both the child’s home dialect and competency in use of SAE, if suitable norms are developed. This is line with Munoz et al. (2003) who recommended excluding utterances that have features of the participant’s language from being classed as grammatically inaccurate, as GA may be an indicator of normal or impaired language development only in the context of the syntactic structures that are typical of the community. Varieties of AE have different grammatical rules from that of SAE and hence require developmental normative data that is individualised to their capacities, to more reliably examine LD and LI. Macrostructure Measures Unlike the microstructure measures, the NSS macrostructure measures were less influenced by features of AE. Most participants gained NSS scores within normal limits compared to the database. Furthermore, variations among the NSS components suggest areas of strength and weakness across different aspects of narrative structure. One exception was P#3, who performed below two SDs on many NSS measures, using the phrase “once upon a time”

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ACQ Volume 13, Number 3 2011

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