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"In teaching a second language we must design forms of work in which the student's attention shall be directed to the subject matter and away from the form in which it is expressed."
Harold Palmer (1877-1949)
Task 1: What is data-driven learning? (5 MINUTES)
The principles behind data-driven learning are not new or bound by the use of computers.
As Palmer suggested in the quote above, learning is a process of discovery. Data-driven learning builds on this foundation to encourage the learner to construct knowledge by a cycle of hypothesizing, experimentation and observation. This is one of the key elements of a constructivist approach. Other approaches, such as task-based learning and the lexical approach, share this founding principle and are therefore complementary approaches.
Here are four key characteristics of data-driven learning - match the two halves of each characteristic.
Paste the text into the input window and press GO.
Wait for the 'word cloud' to appear--the larger the word, the more often it appears in the text. This is a simple graphical representation of a vocabulary profile.
Compare the most frequent words in the 'word cloud' to the words you identified as keywords. Were any the same?
You will get a graphical representation of the vocabulary profile of the text that shows the top 150 words, with words in different sizes according to how frequently they appear in the text. It will look like this:
What are the top five words in the text according to frequency?
How can such a view of a text be useful in teaching English?
What other information from the original text would be useful to see as part of such a vocabulary profile?
There are many tools for creating vocabulary profiles. We'll look in detail at the vocabulary profilers in Lextutor in the next section.
Task 3: What is a concordance? (20 MINUTES)
Aside from a vocabulary profile, a concordance is one of the other essential tools in data-driven learning. The most common kind of concordance is called KWIC - Key Word In Context. Let's take a look at another simple tool to illustrate the basic features of a concordance and contrast it to a vocabulary profile.
You will see the text taken from "A brief rationale for data-driven learning' in the text input box.
Below the text area you will see a vocabulary profile, showing words in different font sizes according to how often they are used in the text. This will appear as a 'word cloud', similar to the profile your created in the previous step with WORDLE.
Click a word in the 'word cloud' vocabulary profile of the text - start with the word "MATERIALS"
Scroll down to see the area below the 'word cloud' and you will see a list of all the times the "key word" MATERIALS was used, with the context to the left and right of the word. This is a KWIC display.
What extra information does a concordance provide that you couldn't get from the vocabulary profile?
Take the word "MATERIALS" as an example -- what lexico-grammatical information does the KWIC suggest about the word?
Try to explore the collocates of "MATERIALS" - compare the collocates 'ENHANCED" with "AUTHENTIC" (Find these words in the word cloud and click on them - the KWIC of each will appear in sections above the MATERIALS KWIC
Which is a 'stronger' collocate of MATERIALS in this text?
Concordances in literature have a long history. The early concordances were of the Bible, the earliest being done in 1230.
How can the additional information given by a concordance be used in a data-driven learning approach?
What is Lextutor? (10 MINUTES)
Lextutor is a free web-based resource. It was developed by Tom Cobb, a professor in applied linguistics at UQAM, with a view to the practical application of data-driven learning using principled approaches supported by published research.
Here is short video about ''Lextutor'. Watch it and then answer the following questions.
Now, see what you can remember by taking this quiz:
We'll take a closer look at Lextutor in another wikiworksheet.
Follow up: Over to you
How could you use Lextutor in teaching?
Create a new blog post in your blog
Consider the two basic tools in data-driven learning we looked at: a vocabulary profile and a concordance.
List a few ways you would like to try using these tools in teaching. Tag this with "teaching ideas" "CTE319" and "Data-driven learning"
Visit some of your colleagues blogs and find their blog post about using data-driven learning in teaching.
Tom Cobb's paper in the Langauge Learning Technology journal gives a very good overview of the principles of use behind the site with clear examples: http://llt.msu.edu/vol11num3/cobb/default.html
You can also join the FACEBOOK group for Lextutor users if you want to keep up with recent developments.
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