Abstract
A learner corpus (LC) is widely known as a rich source of information regarding the use of expressions and the errors made by students in their productions. In fact, we, as teachers, can profit from the compilation of their tasks so as to analyze in detail their way of writing. However, the mere compilation of texts does not guarantee a successful exploitation, as more steps than saving texts must be involved in the whole process. Therefore, it seems essential to follow a protocolized methodology of compilation. In this paper we propose five phases for compiling a LC containing texts from the spontaneous written productions from undergraduate and postgraduate students. The outcomes thrown with the LC exploitation will reveal the errors in students’ productions regarding the use of plural, comparative and superlative in adjectives and also other fails detected in the tagging phase, most of which are due to students’ misuses.
Highlights
IntroductionAs a branch of applied linguistics, corpus linguistics has conferred upon language researchers around the world ─and, any user interested in languages─ a great tool for observing and analyzing words in their context
Under the umbrella of the conceptualization of what we know today as learner corpora research (LCR), we present a study in which we analyze the written production of students at university
In the case with which we are concerned, for detecting some errors made by students and the fails of the tagger software, we have to search for the corresponding tag in every component from the two subcorpora
Summary
As a branch of applied linguistics, corpus linguistics has conferred upon language researchers around the world ─and, any user interested in languages─ a great tool for observing and analyzing words in their context. The different uses and applications that corpus linguistics can offer to, among many other disciplines, teaching practice and methodology are certainly numerous. There is a very wide range of linguistic aspects that can be analyzed and worked on by using corpora in language teaching (Nesselhauf, 2004). Under the umbrella of the conceptualization of what we know today as learner corpora research (LCR), we present a study in which we analyze the written (and spontaneous) production of students at university (undegraduate and postgraduate levels). We will analyze the fails detected when automatically tagging with another program
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