Presented on March 23rd, 2017 at the TESOL International Convention and English Language Expo, Seattle, USA

1. Flexible, Free and Open Data-
Driven Learning for the
Masses
Alannah Fitzgerald
http://maxpixel.freegreatpicture.com/photo-1742679

2. MINING & LINKING OPEN CONTENT
FOR DATA DRIVEN LEARNING
FLAX Language Digital Library Project, University of Waikato, NZ

3. Data-Driven Learning
The metaphor that Johns evoked was one where
language is treated as empirical data and “every
student is a Sherlock Holmes”, investigating the
uses of linguistic data directly to assist with
language acquisition (Johns, 2002, p. 108).

4. flax.nzdl.org
Powerful yet simple interfaces for
Data-Driven Learning

5. The eBook of FLAX
“FLAX (Flexible Language Acquisition) is
both a vision and a tool that you can use for
language learning. The Web contains
innumerable language activities, quizzes,
and games, but they are fixed: the activities
are cast in stone and the material is chosen
by others. Our vision is to put the control
back where it belongs, in the hands of
teachers and learners.”

6. WHO ARE WE IN THIS FLAX
RESEARCH & DEVELOPMENT
COLLABORATION?

7. FLAX Language at Waikato University
http://flax.nzdl.org FLAX image by permission of non-commercial reuse by Jane Galloway

8. FLAX Language Project at the
Greenstone Digital Library Lab,
Waikato University NZ
Professor Ian Witten
FLAX Project Lead
Dr Shaoqun Wu
FLAX Project Lead Researcher & Developer

9. Research on Open FLAX Collections
http://oerresearchhub.org/
Alannah Fitzgerald
Open Fellow with OERRH
FLAX Language & Open
Education Researcher

10. OPEN SOURCE LANGUAGE TOOLS
DEVELOPMENT

11. FLAX Digital
Library
Collections
Collocations
database
Glossary
Open
Educational
Resources

12. Contemporary English
(Wikipedia)

13. Google-esque Interface Designs
Designed for the non-expert corpus user, namely:
learners, teachers, subject academics, instructional
designers and language resource developers.
http://flax.nzdl.org/greenstone3/flax?a=fp&sa=collAbout&c=collocations&if=flax

14. Link to the Collocation Learning System
with the Wikipedia Corpus in FLAX
(Wu, Li, Witten & Yu, 2016)
http://flax.nzdl.org/greenstone3/flax?a=g&rt=r&sa=CollocationQuery&s=CollocationQuery&s1.title=&c=collocations&s1.threshold=
0.5&s1.startNum=0&s1.perPage=20&s1.sampleNum=10&s1.type=&s1.wordType=&s1.colloType=&s1.query=role&s1.dbName=Wikip
edia

15. Introducing the Wikipedia Miner Toolkit
(Milne & Witten, 2013)

16. Building Interactivity into
FLAX Language Collections

17. FLAX Activities Continued

18. FLAX TEAM Apps for Android via GooglePlay
http://commons.wikimedia.org/wiki/File:Android_robot_skateboardin
g.svg /
http://commons.wikimedia.org/wiki/File:Google_Play_Store.svg

19. FLAX Team on Google Play
https://play.google.com/store/apps/developer?id=FLAX+TEAM&hl=en

20. FLAX Across Platforms
• FLAX Website flax.nzdl.org for hosting open online
language collections
• Building directly onto the Web with OER
• FLAX multilingual open-source software for download
• Set up your own FLAX server online or;
• Build collections offline for use on your PC
• FLAX Android app for download
• Interact with game-based FLAX collections while on the go
• FLAX for MOODLE plug-in for download
• FLAX for MOOC Platforms?
• FLAX in conjunction with translation technologies?

21. DOMAIN-SPECIFIC OPEN
LANGUAGE COLLECTIONS BUILDING

22. The eBook of FLAX
“FLAX enables teachers to build bespoke
libraries very easily. It is built upon powerful
digital library technology, and provides access to
vast linguistic resources containing countless
examples of actual, authentic, usage in
contemporary text. But teachers can also build
collections using their own material, focusing
on language learning in a particular domain
(e.g., business, law) or motivating students by
using text from a particular context (e.g.,
country or region, common interests).”

23. RESEARCH INTO MOOC LINGUISTIC
SUPPORT

24. FLAX Academic English Collections
http://flax.nzdl.org/greenstone3/flax?a=fp&sa=library

25. MOOC Research Participants
• CopyrightX (Harvard University – formerly an
edX MOOC, now a networked course)
• ContractsX (Harvard University with edX)
• English Common Law (University of London
with Coursera)

26. Role and courses taken by respondents 2014-
2016

27. Age bands of respondents

28. Educational background of respondents

29. Languages spoken by MOOC learners
• English (95.71%), followed by increasingly
smaller numbers of participants who identified as
being able to speak fluent:
• Spanish (16.56%), French (12.88%), German
(8.59%), Italian (7.98%), Catalan (3.0%), Chinese,
Finnish, Gujarati, Swahili (1.84%), French Creole,
Hindi, Japanese, Korean, Luo, Norwegian,
Portuguese, Russian, Serbian (1.23%), Arabic,
Georgian, Slovak, Thai, Turkish, Ukrainian, Urdu,
Vietnamese (0.61%).

30. “When you want to find out how to express something in English what
resource(s) do you use? You can select more than one.”
Language Resources Informal learners (N=163) CopyrightX teachers (N=11)
Paper-based dictionaries 18.40% 18.18%
Online dictionaries 76.07% 100.00%
Online reference resources
(e.g. Wikipedia) 52.15% 81.82%
Search engines (e.g. Google,
using inverted commas ""
and asterisks * to search for
keywords/phrases for
language use) 57.67% 100.00%
Corpora / searchable web-
based language collections
(e.g. FLAX, WebCorp) 7.98% 0.00%
Grammar books 11.66% 9.09%
Language course books 1.84% 9.09%
Ask someone 31.90% 27.27%
Need nothing 2.45% 0.00%

31. Keyword search for creative in CopyrightX collection

32. Wikify function in the CopyrightX MOOC collection

33. Preview of some of the top 100 collocations in the
CopyrightX collection displaying summary judgment

34. Learner motivations for using FLAX
and other language support resources

35. FLAX user experience for learners

36. Learner feedback on the searchability of the
FLAX ContractsX MOOC collection

37. Learner feedback on the collocations and Cherry
Basket features in the English Common Law
MOOC collection

38. Negative features of FLAX according to respondents

39. Positive features of FLAX according to respondents

40. Extra comments on FLAX from respondents

41. RESEARCH INTO THE REUSE OF
MOOC LINGUISTIC CONTENT

42. Fitzgerald, A., Marin. M.J., Wu, S. & Witten, I.H.
(2017). Evaluating the Efficacy of the Digital
Commons for Scaling Data-Driven Learning. In
M. Carrier, R. M. Damerow, & K. M. Bailey (Eds.),
Digital Language Learning and Teaching:
Research, Theory, and Practice (pp. 38 – 51).
New York, NY: Routledge & TIRF.

43. The Digital Commons
Typically, the digital commons involves the
creation and distribution of informational
resources and technologies that have been
designed to stay in the digital commons using
various open licenses, including the GNU Public
License and the Creative Commons suite of
licenses (Wikipedia, 2016). One of the most
widely used informational resources developed
by and for the digital commons is Wikipedia.

44. Data Collection Procedure
• 52 students in the fourth year of the
Translation Degree program at the University
of Murcia (Spain) were selected as informants.
• All the students’ linguistic competence level
complied with the Common European
Framework of Reference for Languages
requirements for the B2 level.

45. Experimental & Control Groups
• The experimental group (16 informants organized
into four sub-groups) were requested to only
consult the FLAX English Common Law MOOC
collection as the single source of information to
draft their essays.
• The remaining 36 students (divided into nine
different sub-groups) would act as the control
group, following the traditional method for the
design and drafting of essays before this
experiment was carried out, that is, using any
information source available.

46. Term Average in each corpus
FLAX Corpus Non-FLAX Corpus
Terms Identified by
Themostat (A) (Drouin,
2003)
226 385
Corpus Size After
Reduction
16,939 16,264
Number of Topics (B) 4 9
Term Average (A/B) 56.5 42.77
Standardized
type/token ratio
35.3 38.63

47. Findings from Reuse Study
• According to the data, the members of the
experimental group appear to have acquired the
specialized terminology of the area better than those
in the control group, as attested by the higher term
average obtained by the texts in the FLAX-based corpus
(56.5) as opposed to the non-FLAX-based text
collection, at 13.73 points below
• However, the standardized type/token ratio assigned to
each set of texts, which is often indicative of the
richness of the vocabulary (the higher, the richer), is
lower for the FLAX-based texts, standing at 3 points
below the texts written by the control group

48. References
• Biber, D., Conrad, S., & Cortes, V. (2004). If you look at . . .: lexical bundles
in university teaching and textbooks. Applied Linguistics, 25, 371–405.
Biber, D. (2006). University Language, A corpus-based study of spoken and
written registers. John Benjamins, Amsterdam.
• Biber, D., Barbieri F. (2007). Lexical bundles in university spoken and
written registers. English for Specific Purpose, 26, 263–286.
• Fitzgerald, A., Marin. M.J., Wu, S. & Witten, I.H. (2017). Evaluating the
Efficacy of the Digital Commons for Scaling Data-Driven Learning. In M.
Carrier, R. M. Damerow, & K. M. Bailey (Eds.), Digital Language Learning
and Teaching: Research, Theory, and Practice (pp. 38 – 51). New York, NY:
Routledge & TIRF.
• Johns, T. (2002). Data-driven learning: the perpetual challenge. In B.
Kettemann & G. Marko (Eds.), Teaching and Learning by Doing Corpus
Analysis. Proceedings of the Fourth International Conference on Teaching
and Language Corpora, Graz 19-24 July, 2000, (pp. 107-117). Amsterdam:
Rodopi.
• Milne, D. & Witten, I.H. (2013). An open-source toolkit for mining
Wikipedia. Artificial Intelligence, 194, 222-239.
• Wu, S., Li, L., Witten, I.H., Yu, A. (2016). Constructing a Collocation
Learning System from the Wikipedia Corpus. International Journal of
Computer-Assisted Language Learning and Teaching (IJCALLT), 6, issue 3,
pp. 18-35

49. Thank You
Special Thanks:
Ruth Crymes TESOL Fellowship for Graduate Study
The International Research Foundation (TIRF) for English Language Education
FLAX Language Project & Software Downloads: http://flax.nzdl.org/
FLAX Language Project Research: https://www.researchgate.net/project/FLAX-Flexible-
Language-Acquisition-flaxnzdlorg
The How-to eBook of FLAX: http://flax-
doc.nzdl.org/BOOK_OF_FLAX/BookofFLAX%20fullsize%20with%20links.pdf
FLAX Game-based Apps for Android via Google Play Store (free):
https://play.google.com/store/apps/developer?id=FLAX%20TEAM&hl=en
Ian Witten (FLAX Project Lead): ihw@cs.waikato.ac.nz
Shaoqun Wu (FLAX Research and Development): shaoqun@waikato.ac.nz
Alannah Fitzgerald (FLAX Open Language Research): a_fitzg@education.concordia.ca
TOETOE Technology for Open English Blog: www.alannahfitzgerald.org
Slideshare: http://www.slideshare.net/AlannahOpenEd/
Twitter: @AlannahFitz