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Language supports for journal abstract writing across disciplines.

Various writing assistance tools have been developed through efforts in the areas of natural language processing with different degrees of success of curriculum integration depending on their functional rigor and pedagogical designs. In this paper, we developed a system, WriteAhead, that provides si...

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Published in:Journal of Computer Assisted Learning Vol. 28; no. 4; pp. 322 - 336
Main Authors: Liou, H.-C., Yang, P.-C., Chang, J.S.
Format: pictorial research tables/charts Journal Article
Published: Wiley-Blackwell Aug2012
Online Access:View this record in EBSCOhost
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        02664909
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      jtl: Journal of Computer Assisted Learning
      issn: 02664909
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      dt: Aug2012
      vid: 28
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        104469426
        77385629
        10.1111/j.1365-2729.2011.00446.x
        104469426
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        atl: Language supports for journal abstract writing across disciplines.
      aug:
        au:
          Liou, H.-C.
          Yang, P.-C.
          Chang, J.S.
        affil: Department of Foreign Languages and Literature, National Tsing Hua University, Hsinchu, Taiwan
      sug:
        subj:
          Language Education
          Serial Publications
          Abstracting and Indexing
          Writing
          Natural Language Processing
          Software
          Questionnaires
          Human
          Summated Rating Scaling
          Experimental Studies
          User-Computer Interface
          Funding Source
          Taiwan
      ab: Various writing assistance tools have been developed through efforts in the areas of natural language processing with different degrees of success of curriculum integration depending on their functional rigor and pedagogical designs. In this paper, we developed a system, WriteAhead, that provides six types of suggestions when non-native graduate students of English from different disciplines are composing journal abstracts, and assessed its effectiveness. The method involved automatically building domain-specific corpora of abstracts from the Web via domain names and related keywords as query expansions, and automatically extracting vocabulary and n-grams from the corpora in order to offer writing suggestions. At runtime, learners' input in the writing area of the system actively triggered a set of corresponding writing suggestions. This abstract writing assistant system facilitates interactions between learners and the system for writing abstracts in an effective and contextualized way, by providing suggestions such as collocations or transitional words. For assessment of WriteAhead, we compared the writing performance of two groups of students with or without using the system, and adopted student perception data. Findings show that the experiment group wrote better, and most students were satisfied with the system concerning most suggestion types, as they can effectively compose quality abstracts through provided language supports from WriteAhead.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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