This document discusses data-driven learning (DDL), an approach to language teaching that uses computer-generated concordances to expose learners to real language patterns. It outlines the profits and problems of DDL, including enhanced engagement but also technical, pedagogical, and ideological barriers. Looking forward, the document envisions prospects for DDL beyond the classroom through mobile and teacher-free approaches, and introduces a concordancing tool called KWICen designed for mobile language learning.

1. DATA-DRIVEN
LEARNING (DDL)
REVISITED
PROFITS, PROBLEMS & PROSPECTS
Bill Zhi QUAN
wisdomquan@gmail.com
PhD candidate, AUT University,
Auckland, New Zealand

2. PREVIEW
RETROSPECT
• Essence of DDL
- concordancing, language
exposure & learner autonomy
• Profits and problems
PROSPECT
• Tech-based and teacher-free
DDL beyond the classroom
• Mobile DDL
• KWICen

3. MR. DDL
• “the use in the classroom of
computer generated concordances
to get students to explore the
regularities of patterning in the
target language, and the
development of activities and
exercises based on concordance
output” (Johns & King, 1991, p. iii).

4. CONCORDANCER: A POWERFUL TOOL
• 1) ays that universities urgently need to convince academics that popularising research is re
• 2) rviews by Professor Ian Fells ought to convince producers elsewhere that talking heads are
• 3) produce literature detailed enough to convince the prospective buyer. Ivanov's major inte
• 4) hbouring system will find it harder to convince their own establishment that they need new
• 5) ggling sister or even the queen should convince us that behaviour can seem intelligent in
•
• 1) manager for remote sensing will try to persuade different parts of the government to spend
• 2) in of sense. Incidentally, how did you persuade Michael Heseltine to write it for you? Gal
• 3) n early stage. Second, it is trying to persuade researchers that it is a good thing to wor
• 4) t two years trying, unsuccessfully, to persuade the British government to make some contrl
• 5) ogy, is planning a mission to India to persuade the country to invest in British satellite
• (Johns, 1991, p. 16, with the number for each node word reduced to 5)

5. ESSENCEActive
learner
engagement
Great language
exposure
Concordancing
• Envisaged:
• ‘language detective’, learning to
recognize and interpret clues from
context (‘Every student a Sherlock
Holmes’) (Johns, 1997, p. 101)

6. MULTIPLE AFFORDANCES
• Technology can enhance education mainly in two ways: providing teaching
resources and enhanced learning experience (Laesen-Freeman & Anderson,
2011, p. 199). DDL can do both.
• Boulton (2011a, p. 575) summarised:
• … fully compatible with communicative language teaching; discovery
learning and learning by doing; autonomisation and learning to learn;
learner-centredness and individualization; collaborative learning and
creativity; task-based and process as well as product orientations; form and
meaning in constructivism; with an emphasis on the authentic language of
discourse by register/genre.

7. DEVELOPMENTAL BENEFITS
• Enriched and enhanced input
• Frequent and salient encounters
• can be considered as “mindful
repetition in an engaging
communicative context” (N. Ellis,
2002, p. 177), which is expected
to facilitate language acquisition
• ‘Learn how to learn’ skills:
• “predicting, observing, noticing,
thinking, reasoning, analysing,
interpreting, reflecting, exploring,
making inferences, focusing,
guessing, comparing,
differentiating” (O'Sullivan, 2007,
p. 277)

8. THEORETICAL RECOGNITION
• The noticing hypothesis
• As DDL enables or helps
students to attend to recurrent
language features in rich
contexts, it is an ideal means to
acquire language via noticing.
• (L. Flowerdew, 2012, 2015)
• Constructivism
• “learn by doing” (Schank, 1995)
• Learners are supposed to take
the initiative without explicit
instructions from teachers or
tutors; they are not taught but at
most directed.

9. PRACTICAL DILEMMA
• “although various educational uses of concordancing are frequently
talked about, they are not so frequently tested with real learners”
(Johns, Lee, & Wang, 2008, p. 494).
• John (1986, p. 161) observed that the most suitable audience of DDL
would be “well-motivated” and “sophisticated” learners with some
research experience and great need to develop learning skills
• Boulton (2009a) Chambers (2010) provide a comprehensive review of
the large body of literature on specific problems of DDL

10. TECHNICAL BARRIERS
•Lack of computers As computers become more affordable
and available
Lack of appropriate corpora (size,
specialty, access, difficulty, etc.)
Creating pedagogic corpus; providing
access to online resources
Lack of user-friendly tools Developing concordancers tailored to
learners’ needs
Lack of expertise and know-how Awareness-raising, training

11. PEDAGOGICAL BARRIERS
Too difficult linguistically and
culturally
pedagogical processing or mediation:
text grading, simpler reader, familiar or
interesting content
No results or too many Batch selection for observation
Inductive learning, bottom-up
text processing
Mixed with deductive and other
methods in practice
Evaluation of efficacy and
efficiency
Large-scale longitudinal research
required

12. IDEOLOGICAL BARRIERS
Teachers may prefer a
teacher-centred approach
Promoting learner centredness
and autonomy; embracing
teaching and learning with
machine
Learners may not favour
learner-centredness

13. SUMMARY OF THE PAST
• Enhance input, awareness
• Too much, too difficult
Language
exposure
• Constructivism
• Too demanding
Learner
engagement

15. TECHNOLOGY-BASED?
PRACTICE
• Low-tech / soft DDL
• Boulton (2010b, 2010c): Paper-
based DDL
• Johns (1991, 1994) promoted
DDL using print-outs
ARGUMENT
• Johns himself is a diligent
programmer
• The central role of computers in
corpus linguistics and CALL

16. TEACHER-FREE?
PRACTICE
• DDL could be used in a more
traditional teacher-centred
setting (Johns, 1994);
• even the latest DDL experiments
are conducted in the classroom,
initiated and managed by the
teacher
ARGUMENT
• Johns‘ vision
• “What distinguishes the DDL
approach is the attempt to cut
out the middleman as far as
possible and to give the learner
direct access to the data” (1994,
p. 297).

17. GO MOBILE?
• The word ‘mobile’ has three layers of
meaning: mobility of the device, the user
and the content.
• the leap from desktops (and also from
the knees) to pockets represents new
behaviours of use and new ways of
learning: formal and informal, in and
beyond the classroom, with and without
of teacher assistance
Mobile tech may provide
an alternative for DDL
penetration and integration
Highly portable
Truly personal

18. TAKE ME TO SCHOOL
• Crompton (2013, p. 81) notes that 2005 was the year when ‘mobile
learning / m-learning’ became a widely recognised term.
• Chinnery (2006) expressly proposed “going to the MALL”
• in the U.S., over 50% of middle school students use smartphones and
tablets for in-class and at-home study; for high school students, the
percentage is above 60% (Harris Interactive, 2013)

19. KWICEN: AN ANDROID TOOL
• A concordancer for ordinary learners
to conduct ‘fingers-on’ learning
through mobile devices in the hope of
‘quickening’ their language
acquisition, particularly vocabulary
learning

20. GENRE DIVISION

21. RANDOM SELECTION

22. CONTEXT EXTENSION

23. REFERENCES
• Boulton, A. (2009). Data-driven learning: Reasonable fears and rational reassurance. Indian Journal of Applied Linguistics, 35(1), 81-106.
• Boulton, A. (2010). Data-driven learning: On paper, in practice. In T. Harris & M. Moreno-Jaen (Eds.), Corpus linguistics in language teaching (pp. 17-52). Bern: Peter Lang.
• Boulton, A. (2010). Data-driven learning: Taking the computer out of the equation. Language Learning, 60(3), 534-572.
• Chambers, A. (2010). What is data-driven learning? In A. O'Keeffe & M. McCarthy (Eds.), The Routledge handbook of corpus linguistics (pp. 345-358). London: Routledge.
• Chinnery, G. M. (2006). Going to the MALL: Mobile assisted language learning. Language Learning and Technology, 10(1), 9-16.
• Crompton, H. (2013). A historical overview of M-Learning: Towards learner-centred education. In Z. L. Berge & L. Muilenburg (Eds.), Handbook of mobile learning (pp. 80-107). New York: Routledge.
• Ellis, N. (2002). Frequency effects in language processing: A review with implications for theories of implicit and explicit language acquisition. Studies in Second Language Acquisition, 24, 143-188.
• Flowerdew, L. (2012). Corpora in the classroom: An applied linguistic perspective. In K. Hyland, C. M. Huat & M. Handford (Eds.), Corpus applications in applied linguistics (pp. 208-224). London: Continuum.
• Flowerdew, L. (2015). Data-driven learning and language learning theories: Whither the twain shall meet. In A. Lenko-Szymanska & A. Boulton (Eds.), Multiple affordances of language corpora for data-driven
learning (pp. 15-36). Amsterdam: John Benjamins.
• Harris Interactive. (2013). Pearson Student Mobile Device Survey 2013.
• Johns, T. (1986). Micro-concord: A language learner's research tool. System, 14(2), 151-162.
• Johns, T. (1991). Should you be persuaded - two examples of data-driven learning materials. In T. Johns & P. King (Eds.), Classroom concordancing (English Language Journal, 4) (pp. 1-16). Birmingham:
Birmingham University.
• Johns, T. (1994). From printout to handout: Grammar and vocabulary teaching in the context of data-driven learning. In T. Odlin (Ed.), Perspectives on pedagogical grammar (pp. 293-314). Cambridge:
Cambridge University Press.
• Johns, T. (1997). Contexts: The background, development and trialling of a concordance-based CALL program. In A. Wichmann, S. Fligelstone, T. McEnery & G. Knowles (Eds.), Teaching and language corpora
(pp. 100-115). London: Longman.
• Johns, T., & King, P. (Eds.). (1991). Classroom concordancing (Vol. 4).
• Johns, T., Lee, H., & Wang, L. (2008). Integrating corpus-based CALL programs in teaching English through children's literature. Computer Assisted Language Learning, 21(5), 483-506.
• Laesen-Freeman, D., & Anderson, M. (2011). Techniques and principles in language teaching. Oxford: Oxford: University Press.
• O'Sullivan, Í. (2007). Enhancing a process-oriented approach to literacy and language learning: The role of corpus consultation literacy. ReCall, 19(3), 269-286.
• Schank, R. (1995). What we learn when we learn by doing Technical Report No. 60: Institute of Learning Sciences, Northwestern University.