Here, with this research, we are proposing that OERs, and some MOOCs potentially, are increasing access to high quality online educational content for the development of language education resources, with some MOOC providers licensing their educational content under open Creative Commons (CC) licences as OER. English-medium MOOCs present a further opportunity for the development and uptake of language education resources that are derived from MOOC content to support academic English.
Through research and development with the FLAX open-source language project, we are demonstrating this process by building open language collections out of openly-licensed course readings, lectures, blogs, student written work and so on; as well as from Open Access publications, datasets from Wikimedia and Google, and large reference language corpora such as the British National Corpus (BNC). We realise that these are somewhat new areas in language education, and we hope that the resources developed and the issues raised in this research will help to bridge the world of online open education with traditional classroom-based language education.
The use of domain-specific corpora is a growing trend in language teaching and learning (Stubbs and Barth, 2003; Gabrielatos, 2005). FLAX uses the Greenstone digital library system, which is widely used open-source software that enables end users to build collections of documents and metadata directly onto the Web (Witten et al., 2010). The FLAX system offers a powerful suite of interactive text-mining tools, using Natural Language Processing and Artificial Intelligence designs, to enable novice collections builders to link selected language content to large pre-processed language databanks, including collocations and Wikipedia databases and the live Web.
To draw your attention to a few of the innovative features in the FLAX language system, let’s start with the Wikipedia Miner tool (Milne and Witten, 2013) which extracts key concepts and their definitions from Wikipedia articles to related words and phrases in language collections built in FLAX. The development of wordlist and keyword interfaces also allow learners to analyze the range of vocabulary used in a specified document, including the General Service List (West, 1953), the Academic Word List (AWL) by Coxhead (1998) and Off-list words that are often domain-specific (Chung and Nation, 2003) and useful to understand and acquire.
Coxhead, A. (2000). A new academic word list. TESOL Quarterly, 34(2), 213–238 (Reprinted: Critical concepts in linguistics, pp. 123–149, in Corpus linguistics by W. Teubert and R. Krishnamurthy, Eds., 2007, Oxford, England: Routledge)
Chung, T. & Nation, P. (2003). “Technical vocabulary in specialised texts”. Reading in a Foreign Language, 15(2) http://nflrc.hawaii.edu/rfl/october2003/chung/chung.html
Gabrielatos, C. (2005) “Corpora and language teaching: Just a fling or wedding bells?” Teaching English as a second or foreign language, 8(4). http://tesl-ej.org/ej32/a1.html.Retrieved Oct 21 2013.
Milne, D. and Witten, I.H. (2013) “An open-source toolkit for mining Wikipedia.” Artificial Intelligence, (194), pp. 222-239, January.
Stubbs, M., and Barth, I. (2003) “Using recurrent phrases as text-type discriminators: A quantitative method and some findings.” Functions of Language, 10(1), 61-104.
West, M. (1953). A general service list of English words. Longman, Green & Co., London.
Witten, I.H., Bainbridge, D. and Nichols, D.M. (2010). How to Build a Digital Library. Morgan Kaufmann, Burlington, MA (second edition).