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activity - introduction to ddl

Page history last edited by Steve Neufeld 6 years, 9 months ago

Introduction to data-driven learning

 

 

 

After doing this activity you will be able to

  1. describe the key characteristics of data-driven learning
  2. make a vocabulary profile of a text
  3. use a concordance to analyze lexical patterns in a text
  4. access and navigate the Lextutor site

 

Time

  1. It should take you about 40 minutes to complete this task.

 

Task format

  1. Primarily individual tasks, with some pair work tasks.

 

 

 


CONTENTS

 

Here are the contents of this session.  You can click to visit the different activities, or simply scroll down.

 



 

What is data driven learning?

 

 

"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)

 

  1. 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.
  2. Here are four key characteristics of data-driven learning - match the two halves of each characteristic.

 

 

 

DISCUSSION POINTS: Post your ideas to your blog with label 'DDL'

  • How easy do you think it would be to follow the data-driven learning principles in a face-to-face (f2f) classroom? What problems would you anticipate?
  • Would data-driven learning work best with individual students, or group work?
  • To what extent might computers and the internet enhance data-driven learning?

 

 

Task 2:  What is a vocabulary profile? (20 MINUTES)

 

A vocabulary profile shows us how many unique words make up a text, and how frequently each word is used

  • A vocabulary profile of a text is a good place to start when using a data-driven learning approach. 
  • Knowing which words are used more frequently provides a focus for learning patterns that involve such higher frequency words.

 

Here is the introduction of a recent research article on data-driven learning.

 

DDL which was first coined by Johns in 1991 is a method in which learners read large amounts of authentic language and try to discover linguistic patterns and rules by themselves. DDL is famous because of its potential in language learning. It is a student-centered method; which exhorts rule and pattern discovery and learner autonomy. Johns (1988) expressed that DDL entails a shift in the role of teachers and students. In other words the teacher works as a research director and collaborator instead of transmitting information to the students directly and explicitly. DDL and TaskBased approach to language learning are sometimes taken as similar to each other because of the emphasis which is put on the role of students in both of them. Over the years, different investigators and language teachers have taken advantage of DDL for teaching different components of language such as collocations, grammatical points, affixes, etc. (Ball, 1996; Dyck, 1999; Kettemann, 1995; Tribble, 1997).

 

Samples of authentic language for preparing DDL exercises are usually taken from linguistic corpora. Corpus refers to a big collection of naturally occurring language produced by native speakers which is gathered from both spoken and written language. One of the advantages of corpus is its capability in familiarizing language learners with different patterns in the target language. With the use of corpus, we have the opportunity of analyzing natural language and finding the differences between formal and informal language. We can also learn about the features of spoken as compared with written language. At the present time corpora are mostly computerized but in the past they were produced in printed versions. The advent of computers has made us able to search for special words and patterns among corpora much faster and easier.

 

In DDL, a lot of emphasis is put on students’ role. Teaching and learning are sometimes imagined as two complementary activities, but in reality, learning can occur without the existence of an instructor. Even in some situations, learning is more effective when there is no teacher. This is the basis of DDL in which the learners are exposed to authentic language whether in spoken or written form and are expected to discover patterns without the direct assistance of the teacher. It is believed that DDL has some advantages. For instance it improves learner independency and autonomy, enhances language awareness, and makes the learners able to cope with authentic language.

 

 

 

 

 

  1. Quickly read the article
    • Write down the five to ten keywords that  you could use to summarize the rationale.
  2. Highlight and copy the text.
    1. Go to http://tagul.com
    2. Click CREATE.
    3. 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?
  3. Now, create a 6 sentence summary of the text at http://smmry.com 
    • How would you rate the 'automatic' summary? Did it pick out the key concepts of the article?
    • Move your mouse over the summary.  Which words are 'keywords' in the summary sentences? How do these words compare to the words in the 'word cloud' above?

 

 

 

DISCUSSION POINTS: Post your answers  to your blog with label 'DDL'

  • How can a 'vocabulary profile' of a text be useful in teaching English?
  • What other information 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.  In this section we will explore some of the basic tools aligned to data driven learning for languages.

 

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.

 

 

  1. Open this page:  CONCORDLE
  2. You will see a text taken from "A brief rationale for data-driven learning' in the text input box.
  3. 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.
  4. Click a word in the 'word cloud' vocabulary profile of the text - start with the word "MATERIALS"
  5. 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. 

 

 

 

DISCUSSION POINTS:  Post your answers to your blog with the label 'DDL'.

  • How can the additional information given by a concordance be used in a data-driven learning approach to language learning?

 

 


What is Lextutor? (SELF STUDY - 60 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.

 

Take about 20 minutes to explore the site at http://lextutor.ca 

  • Read Tom Cobb's 'research base' at http://www.lextutor.ca/research/ to understand the fundamental principles behind the site.
    • Try creating a 'word cloud' and an 'automatic summary' of Tom's article (use http://smmry.com)
    • Save your WORD CLOUD in the public gallery and embed this in a blog post.  Paraphrase the executive summary of Tom's article to give a summary in your own words.  Remember to cite Tom's article.
  • All of the resources and tools in LEXTUTOR are based on research principles. There are links to the original research to give the background.

 

 

We'll take a closer look at Lextutor in another wikiworksheet.

 

 


Follow up:  Over to you

 

How could you use Lextutor  in teaching?

 

  1. 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" "" and "DDL"
  2. Visit some of your colleagues' blogs, find their blog post about using data-driven learning in teaching, and comment.

 


REFERENCES

 

My GOOGLE library bookshelf

 

Want to learn more about using Lextutor?

 

 

Video tutorials about Lextutor

 

  • If you want more video tutorials about Lextutor visit Tom Cobb's videos on YouTube.

 

 

 

More on Harold Palmer

 

 

Creative Commons License
This work by Kristina Smith & Steve Neufeld is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
Based on a work at kristinaweb20.pbworks.com.

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