Evidence and Interpretation in Language Learning Research
Opportunities for Collaboration With Computational Linguistics
Bibliographic Data
| ID | 4501853 |
|---|---|
| Authors | Detmar Meurers (0000-0002-9740-7442, University of Tübingen and Indiana University, corresponding author), Markus Dickinson (University of Tübingen and Indiana University) |
| Year | 2017 |
| Volume | 67 |
| Issue | S1 |
| Pages | 66-95 |
| Publication date | 2017-06-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Language Learning (JOURNAL) |
| Journal identifiers | ISSN: 0023-8333 • E-ISSN: 1467-9922 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/lang.12233 |
| OpenAlex | W2940216647 |
| Language | EN |
| Citations received | 11 |
| References cited | 56 |
This article discusses two types of opportunities for interdisciplinary collaboration between computational linguistics (CL) and language learning research. We target the connection between data and theory in second language (L2) research and highlight opportunities to (a) enrich the options for obtaining data and (b) support the identification and valid interpretation of relevant learner data. We first characterize options, limitations, and potential for obtaining rich data on learning: from Web-based intervention studies supporting the collection of experimentally controlled data to online workbooks facilitating large-scale, longitudinal corpus collection for a range of learning tasks and proficiency levels. We then turn to the question of how corpus data can systematically be used for L2 research, focusing on the central role that linguistic corpus annotation plays in that regard. We show that learner language poses particular challenges to human and CL analysis and requires more interdisciplinary discussion of analysis frameworks and advances in annotation schemes
Annotation · Applied linguistics · Computational linguistics · Corpus linguistics · Data science · Identification (biology) · Interpretation (philosophy) · Language acquisition · Linguistics · Mathematics education · Natural language processing · Artificial Intelligence · Computer Science · Natural Language Processing Techniques · Psychology · Text Readability and Simplification · Topic Modeling
Natural Language Processing and Language learning
A Concept-based Approach to the Instruction of the Chinese ba-construction
Measuring Longitudinal Writing Development Using Indices of Syntactic Complexity and Sophistication
L2 English speaking syntactic complexity
Adapting to children’s individual language proficiency
Vocabulary sophistication in First-Year Composition assignments
A comparison of automated and manual analyses of syntactic complexity in L2 English writing
Typological characteristics of interlanguage
Bibliometric Analysis of Natural Language Processing Technology in Education
Language Learning Research at the Intersection of Experimental, Computational, and Corpus-Based Approaches
Task Effects on Linguistic Complexity and Accuracy
Natural Language Processing and Language Learning
Implicit Learning in Second Language Acquisition
Introduction to Information Retrieval
Lexical Diversity and Language Development
The Relationship of Lexical Richness to the Quality of ESL Learners’ Oral Narratives
Coh-Metrix
MTLD, vocd-D, and HD-D
The most under-used statistical method in corpus linguistics
Representativeness in Corpus Design
HiTS
Complexity, Accuracy, and Fluency in Second Language Acquisition
Automatic analysis of syntactic complexity in second language writing
An ESL Index of Development
Variationist Sociolinguistics. Change, Observation, Interpretation
Modeling Systematicity and Individuality in Nonlinear Second Language Development
How Big Is "Big"? Interpreting Effect Sizes in L2 Research
On the use of electronic corpora for theoretical linguistics
Interdisciplinary Research at the Intersection of Call, NLP, and SLA
Task Effects on Linguistic Complexity and Accuracy
| Unique citing works | 11 |
|---|---|
| Citations per year | 1,22 |
| Citation span | 2017 - 2025 (9) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 11 |