From learner corpus to data-driven learning (DDL): Improving lexical usage in academic writing

Author:

HArtle Sharon1ORCID

Affiliation:

1. Università degli Studi di Verona

Abstract

Despite considerable discussion in the literature (Flowerdew & Peacock, 2001; Hyland, 1998; Tang, 2012) competent English academic writing is still a problem which needs to be solved. English for Academic Purposes (EAP) teaching often focuses on specialized lexis, which may, however, be the area where academic writers need least help. The study of a small corpus of C2 level academic writing which consisted of the sub-genres of summary and discussion writing revealed that one key area which is problematic is collocation. This paper presents the results of this small corpus investigation into learner language and how it informed the classroom implementation of data-driven learning (DDL) to increase learner awareness of and ability to use collocations effectively in written academic English. The article briefly describes the corpus and the resulting teaching procedure adopted. The first step of this procedure is familiarization followed by experimentation using Sketch Engine (SkeLL).

Publisher

E-JournALL

Subject

General Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3