TOPIC SIGNALING METADISCOURSE DEVICES IN THE TUNISIAN LECTURE CORPUS

被引:2
|
作者
Bouziri, Basma [1 ]
机构
[1] Univ Gabes, Dept Educ, Gabes, Tunisia
关键词
academic lectures; metadiscourse; topic signaling; spoken corpus; Tunisia; DISCOURSE MARKERS; LEXICAL BUNDLES; ENGLISH; SPOKEN;
D O I
10.18485/esptoday.2020.8.2.3
中图分类号
H0 [语言学];
学科分类号
030303 ; 0501 ; 050102 ;
摘要
Identifying main topics is a major academic listening skill that students should develop to efficiently follow and learn from lectures. They should construct a coherent cognitive map of the lecture that they can use to understand and discuss its content. This paper examines topic signaling metadiscourse devices (MDs) in the Tunisian Lecture Corpus (TLC), a corpus of academic lectures delivered in English in the disciplines of Applied Linguistics, Cultural Studies, and Literature. The approach adopted was both qualitative and quantitative relying on the manual coding of the data following three major stages: the design of topic hierarchies, the coding of discourse structuring phases, and the identification of MDs used to signal topics. One finding was the variety of MDs used to introduce topics in TLC. Phenomena related to the use of these devices were also reported and reflected an audience-oriented approach. Potential issues uncovered included absence and ambiguity of marking as well as embedding. These findings are discussed particularly with reference to their pedagogical implications, as the data and its analysis can be used to design professional development programs for lecturers and academic materials to support English majors when attending lectures in Tunisia.
引用
收藏
页码:227 / 249
页数:23
相关论文
共 50 条
  • [41] Automatize Document Topic and Subtopic Detection with Support of a Corpus
    Turan, Metin
    Sonmez, Coskun
    FIRST GLOBAL CONFERENCE ON CONTEMPORARY ISSUES IN EDUCATION (GLOBE-EDU 2014), 2015, : 169 - 177
  • [42] A Corpus of Spontaneous Speech in Lectures : The KIT Lecture Corpus for Spoken Language Processing and Translation
    Cho, Eunah
    Fuenfer, Sarah
    Stueker, Sebastian
    Waibel, Alex
    LREC 2014 - NINTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 2014, : 1554 - 1559
  • [43] A Phrase Topic Model for Large-scale Corpus
    Li, Baoji
    Xu, Wenhua
    Tian, Yuhui
    Chen, Juan
    2019 IEEE 4TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND BIG DATA ANALYSIS (ICCCBDA), 2019, : 634 - 639
  • [44] Functional mapping of corpus callosum:: a research topic for neuropsychologists
    Michel, F
    Hénaff, MA
    REVUE DE NEUROPSYCHOLOGIE, 2001, 11 (02): : 219 - 240
  • [45] Topic Modeling and Word Sense Disambiguation on the Ancora corpus
    Izquierdo, Ruben
    Postma, Marten
    Vossen, Piek
    PROCESAMIENTO DEL LENGUAJE NATURAL, 2015, (55): : 15 - 22
  • [46] TopCat: Data mining for topic identification in a text corpus
    Clifton, C
    Cooley, R
    Rennie, J
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2004, 16 (08) : 949 - 964
  • [47] NEWTS: A Corpus for News Topic-Focused Summarization
    Bahrainian, Seyed Ali
    Feucht, Sheridan
    Eickhoff, Carsten
    FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2022), 2022, : 493 - 503
  • [48] Discovering topic structures of a temporally evolving document corpus
    Adham Beykikhoshk
    Ognjen Arandjelović
    Dinh Phung
    Svetha Venkatesh
    Knowledge and Information Systems, 2018, 55 : 599 - 632
  • [49] Topic Discovery for Biomedical Corpus Using MeSH Embeddings
    Xun, Guangxu
    Jha, Kishlay
    Yuan, Ye
    Zhang, Aidong
    2019 IEEE EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL & HEALTH INFORMATICS (BHI), 2019,
  • [50] The LECTRA Corpus - Classroom Lecture Transcriptions in European Portuguese
    Trancoso, Isabel
    Martins, Rui
    Moniz, Helena
    Mata, Ana Isabel
    Viana, M. Ceu
    SIXTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, LREC 2008, 2008, : 1416 - 1420