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Looking at L2 Vocabulary Knowledge Dimensions from an Assessment Perspective – Challenges and Potential Solutions.

Gyllstad, Henrik LU (2013) In L2 vocabulary acquisition, knowledge and use: New perspectives on assessment and corpus analysis Eurosla Monographs Series, 2. p.11-28
Abstract
The heightened interest in L2 vocabulary over the last two or three decades has brought with it a number of suggestions of how vocabulary knowledge should be modeled. From a testing and assessment perspective, this paper takes a closer look at some of these suggestions and attempts to tease out how terms like model, dimension and construct are used to describe different aspects of vocabulary knowledge, and how the terms relate to each other. Next, the two widely assumed dimensions of vocabulary breadth and depth are investigated in terms of their viability for testing purposes. The paper identifies several challenges in this regard, among others the questionable assumption that multi-word units like collocations naturally belong in the... (More)
The heightened interest in L2 vocabulary over the last two or three decades has brought with it a number of suggestions of how vocabulary knowledge should be modeled. From a testing and assessment perspective, this paper takes a closer look at some of these suggestions and attempts to tease out how terms like model, dimension and construct are used to describe different aspects of vocabulary knowledge, and how the terms relate to each other. Next, the two widely assumed dimensions of vocabulary breadth and depth are investigated in terms of their viability for testing purposes. The paper identifies several challenges in this regard, among others the questionable assumption that multi-word units like collocations naturally belong in the depth dimension, and problems that follow from the complex and often ill-defined nature of the depth dimension. Suggestions for remedies are provided. (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
L2 vocabulary acquisition, knowledge and use: New perspectives on assessment and corpus analysis
editor
Bardel, Camilla; Laufer, Batia and Lindqvist, Christina
volume
Eurosla Monographs Series, 2
pages
11 - 28
publisher
EUROSLA
ISBN
978-1-300-88407-1
language
English
LU publication?
yes
id
bd65bad1-a55f-4471-b890-413e2ad1ee94 (old id 3218074)
alternative location
http://eurosla.org/monographs/EM02/getfile.php?name=Gyllstad
date added to LUP
2012-12-03 09:01:37
date last changed
2016-04-16 09:19:24
@inbook{bd65bad1-a55f-4471-b890-413e2ad1ee94,
  abstract     = {The heightened interest in L2 vocabulary over the last two or three decades has brought with it a number of suggestions of how vocabulary knowledge should be modeled. From a testing and assessment perspective, this paper takes a closer look at some of these suggestions and attempts to tease out how terms like model, dimension and construct are used to describe different aspects of vocabulary knowledge, and how the terms relate to each other. Next, the two widely assumed dimensions of vocabulary breadth and depth are investigated in terms of their viability for testing purposes. The paper identifies several challenges in this regard, among others the questionable assumption that multi-word units like collocations naturally belong in the depth dimension, and problems that follow from the complex and often ill-defined nature of the depth dimension. Suggestions for remedies are provided.},
  author       = {Gyllstad, Henrik},
  editor       = {Bardel, Camilla and Laufer, Batia and Lindqvist, Christina},
  isbn         = {978-1-300-88407-1},
  language     = {eng},
  pages        = {11--28},
  publisher    = {EUROSLA},
  series       = {L2 vocabulary acquisition, knowledge and use: New perspectives on assessment and corpus analysis},
  title        = {Looking at L2 Vocabulary Knowledge Dimensions from an Assessment Perspective – Challenges and Potential Solutions.},
  volume       = {Eurosla Monographs Series, 2},
  year         = {2013},
}