What Is Lexical Proficiency? Some Answers from Computational Models of Speech Data

Autor/inn/en	Crossley, Scott A.; Salsbury, Tom; McNamara, Danielle S.; Jarvis, Scott
Titel	What Is Lexical Proficiency? Some Answers from Computational Models of Speech Data
Quelle	In: TESOL Quarterly: A Journal for Teachers of English to Speakers of Other Languages and of Standard English as a Second Dialect, 45 (2011) 1, S.182-193 (12 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0039-8322
Schlagwörter	Semantics; Language Proficiency; Second Language Learning; Language Fluency; Academic Achievement; Vocabulary Development; Computational Linguistics; Longitudinal Studies; Speech Communication; Scoring Rubrics; English (Second Language); Language Tests; Test of English as a Foreign Language + Suchen Sie Ihr Suchwort? Semantik; Language skill; Language skills; Sprachkompetenz; Zweitsprachenerwerb; Schulleistung; Wortschatzarbeit; Linguistics; Computerlinguistik; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; Scoring formulas; Auswertungsbogen; English as second language; English; Second Language; Englisch als Zweitsprache; Language test; Sprachtest
Abstract	Lexical proficiency, as a cognitive construct, is poorly understood. However, lexical proficiency is an important element of language proficiency and fluency, especially for second language (L2) learners. Lexical proficiency is also an important attribute of L2 academic achievement. Generally speaking, lexical proficiency comprises breadth of knowledge features (i.e., how many words a learner knows), depth of knowledge features (i.e., how well a learner knows a word), and access to core lexical items (i.e., how quickly words can be retrieved or processed). Understanding how these features interrelate and which features are important indicators of overall lexical proficiency can provide researchers and teachers with insights into language learning and language structure. This study investigates the potential of automated lexical indices related to vocabulary size, depth of knowledge, and access to core lexical items to predict human ratings of lexical proficiency in spoken transcripts. The authors do so by analyzing a corpus of scored speech samples using lexical indices taken from the computational tool Coh-Metrix. L2 speech samples were collected longitudinally from 29 participants at two different universities. The L2 participants ranged in age from 18 to 40 years and came from a variety of L1 backgrounds. Overall, the findings portray greater lexical proficiency in speech data as the ability to use a wide range of words that evoke images less easily and are less familiar. The words are also less specific. Such a finding supports the notion that greater lexical proficiency is characterized by knowledge of more words, stronger lexical networks (i.e., hypernymy), and the production of words that are not easily retrievable (i.e., less imagable and familiar). This finding is in contrast to speech samples that exhibit lower lexical proficiency. (Contains 3 tables.) (ERIC).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10