More information on Register Studies here.
Requested by one of my students, a selection of 5 recent papers on Data-driven learning and the use of corpora in language education.
Ballance, O. J. (2017). Pedagogical models of concordance use: correlations between concordance user preferences. Computer Assisted Language Learning, 30(3-4), 259-283. (Link)
Boulton, A. (2017). Corpora in language teaching and learning. Language Teaching, 50(4), 483-506. (Link)
Boulton, A., & Cobb, T. (2017). Corpus Use in Language Learning: A Meta‐Analysis. Language Learning, 67(2), 348-393. (Link)
Godwin-Jones, R. (2017). Data-informed language learning. Language Learning & Technology, 21(3), 9–27. (Link)
Lee, H., Warschauer, M., & Lee, J. H. (2018). The Effects of Corpus Use on Second Language Vocabulary Learning: A Multilevel Meta-analysis. Applied Linguistics. (Link)
Love this art by Christopher Vorlet in The Chronicle of Higher Education. This is about how those in the academia experience anxiety and the never-ending feeling that there is not such thing as “enough”. I was shocked by this quote: “Academia is like a pie-eating contest where the reward is more pie.”
Productivity anxiety: the uneasy feeling that there is always something left to do.
You can read the whole piece here:
https://www.chronicle.com/article/Feeling-Anxious-You-re-Not/243117
The following is a selection of quotes from the following paper:
Parish AJ, Boyack KW, Ioannidis JPA (2018) Dynamics of co-authorship and productivity across different fields of scientific research. PLoS ONE 13(1): e0189742. https://doi.org/10.1371/journal.pone.0189742
You can find here something I wrote co-authorship in the area of applied linguistics where I call for a re-evaluation of collaboration in this area.
Collaboration is now seen as essential to progress in scientific research, and over the past several decades large-scale collaborative projects have become increasingly frequent in fields as diverse as medicine, genetics, and high-energy physics. Although these large collaborations have received more media attention, collaboration on a smaller scale is also important for scientific productivity.
The average number of co-authors per paper published by individual scientists has steadily increased in all fields over the past century. The possible effect of collaboration on improving scientific efficiency and productivity is particularly appealing.
Increased collaboration has long been found to be associated with increased scientific productivity using individual researchers as the unit of study. Collaboration is also frequently mentioned as an important factor in scientists’ own reflections on their success.
A researcher’s productivity may also shape their future role in networks of co-authors, with greater scientific success and exposure allowing the researcher more opportunities to collaborate.
Highly collaborative authors also seem to cite more recently published articles and to re-cite (citing the same references in multiple papers) less frequently, and thus may dwell closer to and push the frontiers of research. International collaboration in particular seems to be strongly related to productivity, as measured by total publications.
Different scientific fields to possess distinguishing network characteristics, including average number of collaborators per author.
In one study of 36,211 Italian scientists, Abramo et al found that across scientific fields women have a slightly higher tendency to engage in collaboration, as measured by the fraction of publications resulting from collaboration.
Within biology, earth sciences, and social sciences, there is not a significant relationship between R and h-index in 2015. Additionally, the association is strongest for physicists. This particularly strong association makes sense given the growing number of large, high impact, intensely collaborative projects in experimental physics.
I Jornadas Vocational Guidance In Clil (VGCLIL). Universidad de Murcia. 23 October, 2018.
CLIL en contextos profesionales.Acceso a la presentación online.
Links:
Languages for the future. British Council 2017.
The value of languages. Cambridge Language Sciences. 2017.
SMEs language survey. British Academy. 2015
Algunos datos sobre VGCLIL (Prof. Purificación Sánchez Hernández, Coordinadora en España VGCLIL)
Sitio web: http://vgclil.eu/index.php
Twitter: @VGCLILproject
Plataforma de formación: http://vgclil.eu/pages/page.php?id=4
Referencias sobre CLIL, EMI e internacionalización
Dafouz, E., & Smit, U. (2014). Towards a dynamic conceptual framework for English-medium education in multilingual university settings. Applied Linguistics, 37(3), 397-415.
Referencias usadas en el proyecto VGCLIL
Our article, Language teachers’ perceptions on the use of OER language processing technologies in MALL, has just been published on Computer Assisted Language Learning Journal, Taylor & Francis Online.
50 free eprints can be downloaded from the following URL:
http://www.tandfonline.com/eprint/epWFWhVAGFZ4yRSIaMcA/full
Get yours now!!!!
Abstract
Combined with the ubiquity and constant connectivity of mobile devices, and with innovative approaches such as Data-Driven Learning (DDL), Natural Language Processing Technologies (NLPTs) as Open Educational Resources (OERs) could become a powerful tool for language learning as they promote individual and personalized learning. Using a questionnaire that was answered by language teachers (n = 230) in Spain and the UK, this research explores the extent to which OER NLPTs are currently known and used in adult foreign language learning. Our results suggest that teachers’ familiarity and use of OER NLPTs are very low. Although online dictionaries, collocation dictionaries and spell checkers are widely known, NLPTs appear to be generally underused in foreign language teaching. It was found that teachers prefer computer-based environments over mobile devices such as smartphones and tablets and that teachers’ qualification determines their familiarity with a wider range of OER NLPTs. This research offers insight into future applications of Language Processing Technologies as OERs in language learning.
KEYWORDS: Language learning, teachers’ perceptions, OER, MALL, natural language processing technologies, higher education