A corpus-driven error analysis of the oral and written production of Leaving Certificate Spanish learners

Show simple item record

dc.contributor.advisor Buffery, Helena en
dc.contributor.author Costello, Kerrill
dc.date.accessioned 2016-01-08T16:25:09Z
dc.date.available 2016-01-08T16:25:09Z
dc.date.issued 2015
dc.date.submitted 2015
dc.identifier.citation Costello, K. 2015. A corpus-driven error analysis of the oral and written production of Leaving Certificate Spanish learners. PhD Thesis, University College Cork. en
dc.identifier.uri http://hdl.handle.net/10468/2171
dc.description.abstract The Leaving Certificate (LC) is the national, standardised state examination in Ireland necessary for entry to third level education – this presents a massive, raw corpus of data with the potential to yield invaluable insight into the phenomena of learner interlanguage. With samples of official LC Spanish examination data, this project has compiled a digitised corpus of learner Spanish comprised of the written and oral production of 100 candidates. This corpus was then analysed using a specific investigative corpus technique, Computer-aided Error Analysis (CEA, Dagneaux et al, 1998). CEA is a powerful apparatus in that it greatly facilitates the quantification and analysis of a large learner corpus in digital format. The corpus was both compiled and analysed with the use of UAM Corpus Tool (O’Donnell 2013). This Tool allows for the recording of candidate-specific variables such as grade, examination level, task type and gender, therefore allowing for critical analysis of the corpus as one unit, as separate written and oral sub corpora and also of performance per task, level and gender. This is an interdisciplinary work combining aspects of Applied Linguistics, Learner Corpus Research and Foreign Language (FL) Learning. Beginning with a review of the context of FL learning in Ireland and Europe, I go on to discuss the disciplinary context and theoretical framework for this work and outline the methodology applied. I then perform detailed quantitative and qualitative analyses before going on to combine all research findings outlining principal conclusions. This investigation does not make a priori assumptions about the data set, the LC Spanish examination, the context of FLs or of any aspect of learner competence. It undertakes to provide the linguistic research community and the domain of Spanish language learning and pedagogy in Ireland with an empirical, descriptive profile of real learner performance, characterising learner difficulty. en
dc.description.sponsorship University College Cork (UCC Strategic Research Fund) en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher University College Cork en
dc.rights © 2015, Kerrill Costello. en
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/ en
dc.subject Learner corpus research en
dc.subject Applied linguistics en
dc.subject Foreign language learning en
dc.title A corpus-driven error analysis of the oral and written production of Leaving Certificate Spanish learners en
dc.type Doctoral thesis en
dc.type.qualificationlevel Doctoral en
dc.type.qualificationname PhD (Arts) en
dc.internal.availability Full text not available en
dc.check.info No embargo required en
dc.description.version Accepted Version
dc.contributor.funder University College Cork en
dc.description.status Not peer reviewed en
dc.internal.school Spanish, Portuguese and Latin American Studies en
dc.check.type No Embargo Required
dc.check.reason No embargo required en
dc.check.opt-out Yes en
dc.thesis.opt-out true
dc.check.embargoformat Not applicable en
dc.internal.conferring Spring Conferring 2016 en

Files in this item

This item appears in the following Collection(s)

Show simple item record

© 2015, Kerrill Costello. Except where otherwise noted, this item's license is described as © 2015, Kerrill Costello.
This website uses cookies. By using this website, you consent to the use of cookies in accordance with the UCC Privacy and Cookies Statement. For more information about cookies and how you can disable them, visit our Privacy and Cookies statement