Predicting the Vocabulary of Children from Written or Spoken Texts.

Autor/inn/en	Moore, Michael; Goldstein, Zahava
Titel	Predicting the Vocabulary of Children from Written or Spoken Texts.
Quelle	(1986), (8 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Child Language; Foreign Countries; Grade 6; Grade 8; Hebrew; Junior High School Students; Junior High Schools; Mathematical Models; Oral Language; Preadolescents; Predictor Variables; Reliability; Socioeconomic Status; Uncommonly Taught Languages; Validity; Vocabulary; Word Frequency; Written Language; Israel + Suchen Sie Ihr Suchwort? 'Children''s language'; Kindersprache; Ausland; School year 06; 6. Schuljahr; Schuljahr 06; School year 08; 8. Schuljahr; Schuljahr 08; Junior High Schools; Student; Students; Sekundarstufe I; Schüler; Schülerin; Mathematical model; Mathematisches Modell; Oral interpretation; Mündlicher Sprachgebrauch; Pre-adolescence; Präadoleszenz; Prädiktor; Reliabilität; Socio-economic status; Sozioökonomischer Status; Minderheitensprache; Gültigkeit; Wortschatz; Word analysis; Frequency; Wortanalyse; Häufigkeit; Geschriebene Sprache
Abstract	A study investigated the use of a mathematical model to predict individuals' total active Hebrew vocabulary from samples of their written and spoken language. The model is based on a generalized inverse Gaussian distribution. The subjects were Israeli junior high school students from both high and low socioeconomic groups. Hebrew language samples of at least 2,000 words were obtained from each child. In 60 of 70 cases, the fit between empirical data and the theoretical model was acceptable. Several hypotheses relating to the model's construct and concurrent validity and its reliability and objectivity were tested. In addition, a hypothesis about the significantly richer vocabulary of higher socioeconomic status children was confirmed. The model can serve as a viable basis for further extensive inquiry into the vocabulary of different samples. (Author/MSE)
Erfasst von	ERIC (Education Resources Information Center), Washington, DC