Influence of learners’ prior knowledge, L2 proficiency and pre-task planning on L2 lexical complexity

词汇多样性 词汇密度 复杂度 词汇项目 任务(项目管理) 流利 心理学 词汇判断任务 语言学 计算机科学 语言能力 自然语言处理 人工智能 词汇 认知 数学教育 社会学 经济 管理 神经科学 哲学 社会科学
作者
Gavin Bui
出处
期刊:International Review of Applied Linguistics in Language Teaching [De Gruyter]
卷期号:59 (4): 543-567 被引量:22
标识
DOI:10.1515/iral-2018-0244
摘要

Abstract Although differentiating between fluency, accuracy and complexity, while assessing L2 task performance, is becoming a standard practice, lexical complexity as a distinctive area has received less attention in the task-based language teaching (TBLT) literature. This study re-examines previous frameworks of lexical complexity and investigates three lexical dimensions, lexical diversity, lexical sophistication and lexical density , using a structured 2 × 2 × 2 split-plot experimental design. The participants were divided into a non-planning group and a planning group and each group was further dichotomised into two proficiency levels. Each participant was assigned one familiar and one unfamiliar oral narrative task. The results show that one’s prior knowledge about a subject is associated with higher lexical diversity and sophistication, while pre-task planning promotes lexical density. The effects of proficiency seem to be largely overridden by the effects of prior knowledge and pre-task planning and show little impact on overall lexical performance. Interestingly, lexical diversity and lexical sophistication are independent of each other, and lexical density is moderately correlated with both lexical diversity and lexical sophistication. The results are discussed with reference to the Levelt model of speech production with some pedagogical implications on content-based language instruction. The exploration of the relationships between the lexical measures reveals a need for deeper and subtler characterisation of L2 lexical complexity.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
shelemi发布了新的文献求助10
刚刚
1秒前
1秒前
无花果应助Xiang采纳,获得10
1秒前
李健应助Xiang采纳,获得10
2秒前
Lucas应助Xiang采纳,获得10
2秒前
allia完成签到 ,获得积分10
3秒前
5秒前
亦74发布了新的文献求助10
5秒前
xchqb发布了新的文献求助10
5秒前
天天好心覃完成签到 ,获得积分10
6秒前
maoxiaogou完成签到,获得积分10
6秒前
wei发布了新的文献求助10
8秒前
Xiang完成签到,获得积分10
8秒前
端庄的孤风完成签到 ,获得积分10
9秒前
9秒前
10秒前
CCCCCL完成签到,获得积分10
10秒前
11秒前
方强完成签到 ,获得积分10
12秒前
大可完成签到 ,获得积分10
12秒前
LLL完成签到,获得积分10
12秒前
孙煜完成签到,获得积分10
12秒前
魁梧的盼望完成签到 ,获得积分10
13秒前
14秒前
充电宝应助阿虎采纳,获得10
14秒前
lhhssll完成签到 ,获得积分10
16秒前
发发发布了新的文献求助10
16秒前
北城发布了新的文献求助10
16秒前
17秒前
冰冰完成签到 ,获得积分10
18秒前
shelemi完成签到,获得积分10
19秒前
徐小锤发布了新的文献求助10
21秒前
xiaoze发布了新的文献求助10
21秒前
007完成签到,获得积分10
23秒前
君君完成签到,获得积分10
23秒前
xiaoze完成签到,获得积分10
25秒前
yubin.cao发布了新的文献求助10
28秒前
医院骑士完成签到,获得积分10
28秒前
wanci应助xchqb采纳,获得10
29秒前
高分求助中
Thinking Small and Large 500
Algorithmic Mathematics in Machine Learning 500
Advances in Underwater Acoustics, Structural Acoustics, and Computational Methodologies 400
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
The Monocyte-to-HDL ratio (MHR) as a prognostic and diagnostic biomarker in Acute Ischemic Stroke: A systematic review with meta-analysis (P9-14.010) 240
The Burge and Minnechaduza Clarendonian mammalian faunas of north-central Nebraska 206
Youths Who Reason Exceptionally Well Mathematically and/or Verbally: Using the MVT:D4 Model to Develop Their Talents 200
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3831561
求助须知:如何正确求助?哪些是违规求助? 3373738
关于积分的说明 10481304
捐赠科研通 3093686
什么是DOI,文献DOI怎么找? 1702949
邀请新用户注册赠送积分活动 819237
科研通“疑难数据库(出版商)”最低求助积分说明 771307