Educational Text Mining

Making Educational Research Transparent

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Workshop at AECT 2016

Title: Online Learning Analytics on Social Networking Sites: How to Tap the Potential of Data Mining in Research of Educational Technology
Session Information: 24 Registrants, 22 Participants; AECT 2016 Convention, Las Vegas, NV

Goals of this Workshop

This half-day workshop is intended for educational researchers or teachers who are interested in analyzing big data of learners’ online activities on social networking sites.

An increasing number of students have expressed their preference of using social networking sites, like Twitter or Facebook, for learning communication rather than using institutional learning management systems (Bosch, 2009; McCarthy, 2010). Some pioneering teachers and researchers have already chose to put part of their classroom learning and teaching activities on these sites or organize other online learning activities (Bosch, 2009; Williams & Chinn, 2009; Brady, Holcomb, & Smith, 2010; McLoughlin & Lee, 2010). Data can easily accumulate online to a gigantic amount, which brings new challenge to data collection and following analysis. This workshop aims at teaching practical skills on how to collect and analyze big data of online learning activities.

By the end of this workshop participants will be able to:

  1. identify research questions that can be explored through data mining
  2. extract big data from social networking sites, like Facebook and Twitter
  3. identify ways to answer relevant research questions using big data analysis techniques

Slides of the Workshop

Download PDF File of the Presentation


Workshop at SITE 2016

Title: Introduction to Text Mining in Educational Research
Session Information: 10 Registrants, 9 Participants; SITE 2016 Annual Conference, Savannah, GA

Goals of this Workshop

This 4-hour workshop is designed for educational researchers interested in learning analytics and text mining. By the end of the workshop participants will be able to 1) identify research questions that can be explored through text mining, 2) extract text data from social networking sites, like Facebook and Twitter, 3) identify ways to answer relevant research questions using text data analysis techniques. The only prerequisites are to bring your own laptops and have your own ideas for online learning activities.

Slides of the Workshop

Download PDF File of the Presentation


Workshop at AECT 2015

Title: Online Learning Analytics on Social Networking Sites: How to Tap the Potential of Data Mining in Research of Educational Technology
Session Information: 22 Registrants, 19 Participants; AECT 2015 Convention, Indianapolis, IN

Goals of this Workshop

This half-day workshop is intended for educational researchers or teachers who are interested in analyzing big data of learners’ online activities on social networking sites.

An increasing number of students have expressed their preference of using social networking sites, like Twitter or Facebook, for learning communication rather than using institutional learning management systems (Bosch, 2009; McCarthy, 2010). Some pioneering teachers and researchers have already chose to put part of their classroom learning and teaching activities on these sites or organize other online learning activities (Bosch, 2009; Williams & Chinn, 2009; Brady, Holcomb, & Smith, 2010; McLoughlin & Lee, 2010). Data can easily accumulate online to a gigantic amount, which brings new challenge to data collection and following analysis. This workshop aims at teaching practical skills on how to collect and analyze big data of online learning activities.

By the end of this workshop participants will be able to:

  1. identify research questions that can be explored through data mining
  2. extract big data from social networking sites, like Facebook and Twitter
  3. identify ways to answer relevant research questions using big data analysis techniques

Slides of the Workshop

Download PDF File of the Presentation


Seminar at DDR 2015

Title: Data Mining and Text Mining in Educational Research
Session Information: 16 Participants; DDR 2015 Annual Conference, Athens, GA

Goals of this Workshop

A quick introduction to the application of data mining and text mining in educational research.

Slides of the Workshop

Download PDF File of the Presentation


Download Weka


Click here to download Weka.

Download R and RStudio


Download R

If you are using a Mac, click here to download R. If you are using a PC, click here to download R.

Download RStudio

Click here to download RStudio.

Road Map to Data Mining


Get your consumer key and secret from Twitter


To collect data from Twitter, you will need a developer account on Twitter first. You can register one at https://dev.twitter.com/. Once you have a developer account, return to the page and scroll down to the bottom of the page, click “Manage Your Apps” under “Tools”.

Now, simply click on “Create New Application” button on the following new page:

On the application creation page, the only thing you need to remember is to fill the Callback URL as http://127.0.0.1:1410.

When you finish the creation step, you can check the details of your application:

The generated consumer keys and secrets would be under the tab “Keys and Access Token”. This piece of information will be important for you to successfully connect to Twitter later on.