We All Make Mistakes! . Analysing an Error-coded Corpus of Spanish University Students Written English

Abstract

[EN] The present study analyses the errors identified and coded in the written argumentative texts of 304 Spanish university students of English extracted from two corpora one from a technical university context corpus (totalling 950 written compositions) and the other from learners enrolled in the Humanities (totalling 750 written compositions). Considered an important design criterion for computer learner corpora studies, the students levels were measured using the Oxford Quick Placement Test and the scores obtained (0 to 60) were then related to the CEFR (Common European Framework of Reference for Languages) levels ranging from A1 to C2. Learners writing in a foreign language not only make errors related to grammar and vocabulary, but also with regard to their competence in the use of syntax, discourse relations and pragmatics among others, and the error coding system has been designed to attempt to address all the possible levels of error with as many sub-categories as required. Within the field of applied linguistics and language teaching/learning, many studies have been carried out over the years designed to address the phenomenon of interlanguage errors made by learners of English (Dusková, 1969; Green & Hecht, 1985; Lennon, 1991; Olsen, 1999 among many others). Previously, these studies involved analyzing a small number of texts with a limited number of tags, based on either linguistic taxonomies or surface structure categories of errors (Dulay, Burt, & Krashen 1982). However, in the last three decades, technological advances have been made which have facilitated the analysis of much larger amounts of data using computers for both the development of learner corpora and programs for a more detailed analysis of the learner data. The aim of the present research is two-fold. Firstly, we explore the nature of the errors coded in the corpus i.e. which errors are most frequent, including not only the main categories but also the most delicate levels of errors. Secondly, we address the question of the relationship, if any, of the learners competence levels and the type and frequency of the errors they make. The results show that grammar errors are the most frequent, and that the linguistic competence of the learners has a lower than expected influence on the most frequent types of errors coded in the corpus.