Difference between revisions of "Data-Driven Language Learning Using Corpora and Concordancing"

From KNILT
Line 19: Line 19:
 
You can also take a peek at the [[Data-Driven Language Learning Glossary]] to familiarize yourself with the important terms used in this course. It is also linked from each Unit's main page.
 
You can also take a peek at the [[Data-Driven Language Learning Glossary]] to familiarize yourself with the important terms used in this course. It is also linked from each Unit's main page.
  
 +
Here is a list of useful resources, including publications, websites and freely available software: [[DDL Resources]]
 
= Objectives for this course =
 
= Objectives for this course =
  

Revision as of 23:16, 9 December 2009

Introduction

As a teacher of English to speakers of other languages, do you ever wish you could interview thousands - or even millions - of native speakers in a few minutes to find out whether "on line" or "in line" is the more common phrase?

A corpus can help with this sort of thing (and many more sorts of things).

With a teacher's guidance, a student can be exposed to multiple authentic instances of the same bit of language.

So, instead of going over a single page of textbook examples - or struggling to come up with a few yourself - you can find as many real examples as you need to teach a lesson on the difference between "fun" and "funny" or the use of "is feeling" vs. "feels".

In this set of units, you'll be guided through the process of creating a lesson using this powerful resource.

Speakers.jpg

Ready? Let's begin, start, commence, go to Unit 1: Corpora.


You can also take a peek at the Data-Driven Language Learning Glossary to familiarize yourself with the important terms used in this course. It is also linked from each Unit's main page.

Here is a list of useful resources, including publications, websites and freely available software: DDL Resources

Objectives for this course

Upon completion of this course, you should be able to

  • create lessons using the principles of data-driven language learning
  • be familiar with the ideas of language corpora and concordancing software
  • have a working familiarity with at least one corpus of the English language
  • be able to extract useful output from a concordancer

Course Navigation