Construction and Application of English Language Context-Driven Multimodal Corpus

被引:0
|
作者
Yang, Jianhong [1 ]
机构
[1] Tianjin Univ, Renai Coll, Tianjin 301636, Peoples R China
关键词
context-driven multimodal corpus; data-driven concordancing; Elan; multiliteracies teaching; LEARNERS;
D O I
10.1145/3318396.3318407
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper investigates the approach and process of constructing context-driven multimodal corpus with Elan software in terms of its diversity of annotation tiers, controlled vocabulary and speed control. By creating the rich and real language environment in diverse context and providing potentially user-customizable strategies, the construction of multimodal corpus for English learning represents an ideal paradigm of data-driven learning model. It is conducive to inspire the learner with great interest and enthusiasm in language learning, and thus improve their language proficiency and cognitive capability by extracting knowledge from corpus compelled by data and inducting abstract linguistic rules by locating authentic examples of language in real-world language use. Based on the multimedia data-driven concordancing, this paper further elaborates the feasible pedagogic application of multimodal corpus in such aspects as vocabulary differentiation, communication contextualization, listening perception, cross-culture awareness cultivation and multiliteracies teaching. This paper concludes with suggestions for surmounting the challengeable disadvantages that multimodal corpus entailed.
引用
收藏
页码:147 / 152
页数:6
相关论文
共 50 条
  • [11] Context-Driven Interactive Query Simulations Based on Generative Large Language Models
    Engelmann, Bjoern
    Breuer, Timo
    Friese, Jana Isabelle
    Schaer, Philipp
    Fuhr, Norbert
    ADVANCES IN INFORMATION RETRIEVAL, ECIR 2024, PT II, 2024, 14609 : 173 - 188
  • [12] Active Learning in Context-Driven Stream Mining With an Application to Image Mining
    Tekin, Cem
    van der Schaar, Mihaela
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2015, 24 (11) : 3666 - 3679
  • [13] DroidSecTester: Towards context-driven modelling and detection of Android application vulnerabilities
    Baheux, Ivan
    Aktouf, Oum-El-Kheir
    Tebib, Mohammed El Amin
    Graa, Mariem
    Andre, Pascal
    Ledru, Yves
    2023 IEEE 34TH INTERNATIONAL SYMPOSIUM ON SOFTWARE RELIABILITY ENGINEERING WORKSHOPS, ISSREW, 2023, : 136 - 141
  • [14] Across-session consistency of context-driven language processing: A magnetoencephalography study
    Roos, Natascha Marie
    Piai, Vitoria
    EUROPEAN JOURNAL OF NEUROSCIENCE, 2020, 52 (05) : 3457 - 3469
  • [15] Context-Driven Satirical Headline Generation
    Horvitz, Zachary
    Do, Nam
    Littman, Michael L.
    FIGURATIVE LANGUAGE PROCESSING, 2020, : 40 - 50
  • [16] Context-Driven Diversification in Social Enterprises
    Bhawe, Nachiket
    Jha, Srivardhini K.
    BUSINESS & SOCIETY, 2024,
  • [17] Context-driven Business Process Modelling
    Born, Matthias
    Kirchner, Jens
    Mueller, Joerg P.
    ADVANCED TECHNOLOGIES AND TECHNIQUES FOR ENTERPRISE INFORMATION SYSTEMS, 2009, : 17 - +
  • [18] Big Bang and context-driven collapse
    Mark Robertson-Tessi
    Alexander R A Anderson
    Nature Genetics, 2015, 47 : 196 - 197
  • [19] Limits on the generalizability of context-driven control
    Hutcheon, Thomas G.
    Spieler, Daniel H.
    QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2017, 70 (07): : 1292 - 1304
  • [20] A Context-Driven Framework for Distributed Collaboration
    Sabbir, Ali Shihab
    Ravindran, Kaliappa
    13TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON DISTRIBUTED SIMULATION AND REAL-TIME APPLICATIONS, PROCEEDINGS, 2009, : 243 - +