Abstract: This 4-hour workshop is designed for educational researchers interested in learning analytics and data mining. By the end of the 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. The only prerequisites are to bring your own laptops and have your own ideas for online learning activities.

Objectives

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.

Topical Outline

The preliminary schedule for this workshop is as the following: 1) Installation of needed tools 2) Introduction of potential research questions that can be answered by data mining 3) Practice data mining on Twitter 4) Practice data mining on Facebook 5) Practice data mining on discussion boards of a website Learning topics for this workshop include: 1) Introduction to the statistical tool R (http://www.r-project.org/) 2) Data mining of online learning activities on Twitter 3) Data mining of online learning activities on Facebook. 4) Data mining on discussion board

Prerequisites

Basic knowledge of programming.

Experience Level

Intermediate

Qualifications

Qiang Hao is a PhD student majored in Learning, Design and Technology at University of Georgia. He has extensive experience in programming and data mining. He designed and coded the latest-version graduate school website of University of Georgia (http://grad.uga.edu), and leaded several data mining projects, such as Web-Scraping-from-USGSA (http://goo.gl/Qd8Uae) and TwitterHashtagR (http://goo.gl/yV7BBL). Dr. Stefanie Panke works as instructional analyst at the University of North Carolina at Chapel Hill where she provides instructional design consultation and guidance for faculty and teaching professionals as well as project management for educational technology initiatives at the School of Government. In addition, she serves as editor for social software at the Educational Technology and Change Journal (ETC) and social media coordinator for AACE. Prior to her work at UNC, Stefanie was Director of E-Learning at the Institute of Psychology and Education at Ulm University. In this role she implemented university-wide e-learning projects, and taught courses on instructional design, computer mediated communication and webnography. In 2009, she received a PhD in Applied Linguistics from the University of Bielefeld with a thesis on the information design of educational websites. From 2003 to 2008 she worked at the Knowledge Media Research Center in Tuebingen, an interdisciplinary institute for research educational technology. During this time, her team developed the award-winning portal on e-learning in higher education (e-teaching.org).