A Portrait of Academic Literacy in Mid-Adolescence: A Computational Longitudinal Account of Cognitive Academic Language Proficiency during Secondary School

Autor/inn/en	Granados, Adrián; Lorenzo-Espejo, Antonio; Lorenzo, Francisco
Titel	A Portrait of Academic Literacy in Mid-Adolescence: A Computational Longitudinal Account of Cognitive Academic Language Proficiency during Secondary School
Quelle	In: Language and Education, 37 (2023) 3, S.288-307 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Granados, Adrián) ORCID (Lorenzo-Espejo, Antonio) ORCID (Lorenzo, Francisco)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0950-0782
DOI	10.1080/09500782.2022.2079951
Schlagwörter	Academic Language; Literacy Education; Longitudinal Studies; History Instruction; Essays; Computer Software; Computational Linguistics; Syntax; Phrase Structure; Word Frequency; Vocabulary; Connected Discourse; Speech Communication; Spanish; Native Language; Language Usage; Secondary School Students; Nouns; Morphology (Languages); Writing Evaluation + Suchen Sie Ihr Suchwort? Academic; Language; Languages; Akademiker; Sprache; Wissenschaftssprache; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; History lessons; Geschichtsunterricht; Essay; Aufsatzunterricht; Linguistics; Computerlinguistik; Phrasenstruktur; Word analysis; Frequency; Wortanalyse; Häufigkeit; Wortschatz; Spanisch; Sprachgebrauch; Sekundarschüler; Morphology; Morphologie
Abstract	This study describes academic literacy development during mid-adolescence, when learners need to adjust to the demands of academic discourse as a gateway to linguistic adulthood. Unlike most research to date, which is cross-sectional and detached from disciplinary content, this study provides a two-year longitudinal description of academic language in the form of history essays. During the two-year study, a group of 20 students (whose first language was Spanish) produced a corpus of history essays in relation to topics covered in the official curriculum. These essays were processed with MultiAzterTest, a state-of-the-art computational tool that produces linguistic and discursive representations of texts. A statistical analysis of the metrics shows a significant evolution of key measures, which may contribute to charting academic language literacy. More precisely, the results point to a statistically significant evolution of the length of language units (i.e. the amount of words, sentences and paragraphs), in syntactic complexity (i.e. the proportion of nouns and the complexity of noun phrases), in lexical richness (i.e. the frequency and precision of lexis) and in cohesion metrics (i.e. the overall use of connectives), hence exploring the boundaries between basic child speech and adult discourse. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01