Compressing Learner Language: An Information-Theoretic Measure of Complexity in SLA Production Data

Autor/inn/en	Ehret, Katharina; Szmrecsanyi, Benedikt
Titel	Compressing Learner Language: An Information-Theoretic Measure of Complexity in SLA Production Data
Quelle	In: Second Language Research, 35 (2019) 1, S.23-45 (23 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0267-6583
DOI	10.1177/0267658316669559
Schlagwörter	Second Language Learning; Difficulty Level; Contrastive Linguistics; Language Research; Morphology (Languages); Syntax; Second Language Instruction; Teaching Methods; Essays; Writing Instruction; Native Language; Prediction; Language Classification; Correlation; Language Proficiency; College Students; English (Second Language); Computational Linguistics + Suchen Sie Ihr Suchwort? Zweitsprachenerwerb; Schwierigkeitsgrad; Linguistics; Kontrastive Linguistik; Sprachforschung; Morphology; Morphologie; Fremdsprachenunterricht; Teaching method; Lehrmethode; Unterrichtsmethode; Essay; Aufsatzunterricht; Schreibunterricht; Vorhersage; Sprachtypologie; Korrelation; Language skill; Language skills; Sprachkompetenz; Collegestudent; English as second language; English; Second Language; Englisch als Zweitsprache; Computerlinguistik
Abstract	We present a proof-of-concept study that sketches the use of compression algorithms to assess Kolmogorov complexity, which is a text-based, quantitative, holistic, and global measure of structural surface redundancy. Kolmogorov complexity has been used to explore cross-linguistic complexity variation in linguistic typology research, but we are the first to apply it to naturalistic second language acquisition (SLA) data. We specifically investigate the relationship between the complexity of second language (L2) English essays and the amount of instruction the essay writers have received. Analysis shows that increased L2 instructional exposure predicts increased overall complexity and increased morphological complexity, but decreased syntactic complexity (defined here as less rigid word order). While the relationship between L2 instructional exposure and complexity is robust across a number of first language (L1) backgrounds, L1 background does predict overall complexity levels. (As Provided).
Anmerkungen	SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01