Inferring New Vocabulary Using Online Texts

dc.contributor.author	Stvan, Laurel Smith
dc.date.accessioned	2022-12-13T18:15:15Z
dc.date.available	2022-12-13T18:15:15Z
dc.date.issued	2005
dc.identifier.citation	Stvan, Laurel Smith. 2005. Inferring New Vocabulary Using Online Texts. Computers in the Schools Volume 22, Issue 1/2(1/2). 85–96.	en_US
dc.identifier.uri	http://hdl.handle.net/10106/31009
dc.description.abstract	Please note that the full text is embargoed ABSTRACT: Through small-scale sampling of relevant specialized texts to craft hands-on inferential vocabulary tasks, both students and teachers can benefit from corpus linguistic information. By discovering ways to collect and access real data, second-language teachers can create topic-specific corpora and use software to sort and highlight the data to create more rich and revealing classroom materials for improving vocabulary learning. This student-centered, data-driven learning can be easily adapted for different levels of reading students. Free or purchased software, as well as features of existing programs, can be put to use to access online texts	en_US
dc.language.iso	en_US	en_US
dc.publisher	Routledge	en_US
dc.subject	Vocabulary, second language acquisition, online texts, corpus linguistics, reading, context, concordancing	en_US
dc.title	Inferring New Vocabulary Using Online Texts	en_US
dc.type	Article	en_US