Home // eLmL 2017, The Ninth International Conference on Mobile, Hybrid, and On-line Learning // View article

Developing Students’ Vocabulary Knowledge in Content Subjects: A Computational Linguistic Approach

Authors:
Kirk L. B. Dowswell

Keywords: data-driven learning; vocabulary self-collection strategy; vocabulary learning; involvement load hypothesis; teaching with wikis.

Abstract:
Undergraduate students are exposed to discipline-specific lexis and concepts, particularly when studying in a second language. Current research suggests that most students find it difficult to fully comprehend academic reading material because they lack the requisite vocabulary, i.e., 5,000 to 8,000 word families for achieving 95% to 98% comprehension, respectively. It has also been suggested that teaching vocabulary explicitly is not an efficient use of classroom time. Thus, in order to enhance vocabulary acquisition and, ultimately, improve the reading comprehension skills of second language learners, this study evaluated the use of a modified version of the Vocabulary Self-Selection Strategy (VSS+) as a self-directed learning tool. The study was conducted in an Arab higher education institution where undergraduate students studied Information Technology (IT) in English. It was anticipated that this unique intervention would improve vocabulary acquisition with minimal use of classroom teaching time. Results indicated that students were actively engaged with the wiki as a learning tool and there was a noticeable improvement in their vocabulary knowledge. Overall, the study has implications for teachers, as well as learners

Pages: 41 to 46

Copyright: Copyright (c) IARIA, 2017

Publication date: March 19, 2017

Published in: conference

ISSN: 2308-4367

ISBN: 978-1-61208-541-8

Location: Nice, France

Dates: from March 19, 2017 to March 23, 2017