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Learning Analytics and Knowledge 2012Syllabus

Click here to sign up for the course:
http://lak12.mooc.ca/cgi-bin/login.cgi?action=Register

This course is offered by the Society for Learning Analytics Research in advance of our 2nd international conference: http://lak12.sites.olt.ubc.ca/

Course Description:
Capturing and analyzing data has changed how decisions are made and resources are allocated in businesses, journalism, government, and military and intelligence fields. Through better use of data, leaders are able to plan and enact strategies with greater clarity and confidence. Data is a value point that drives increased organizational efficiency and a competitive advantage. Simply, analytics provide new insight and actionable intelligence. Companies such as Microsoft, IBM, Google, and Amazon are investing heavily in technologies and techniques in helping individuals and organizations makes sense of, and unlock the value within, big data.

In education, the use of data and analytics to improve learning is referred to as learning analytics. Analytics have not yet made the impact on education that they have made in other fields. That’s changing. Software companies, researchers, educators, and university leaders are starting to recognize the value of data in improving not only teaching and learning, but the entire education industry.

This course will provide an (generally non-technical) introduction to learning analytics and how they are being deployed in various contexts in the education field. Additionally, the tools and methods, ethics and privacy, and the systemic impact of analytics will be explored, presenting a broad overview of the current state and possible future directions of the field.

Course Audience:
This course will be of interest to individuals across the full learning spectrum: K-12, higher education, corporate learning, and informal/life long learning. Leaders, educators, and even students will benefit from the topics explored and the related implementation issues (in particular, privacy and ethics of analytics).

Course Facilitators:

Simon Buckingham Shum (Open University): http://people.kmi.open.ac.uk/sbs/welcome/, Twitter: sbskmi (https://twitter.com/#!/sbskmi)

Shane Dawson (University of British Columbia): http://isit.arts.ubc.ca/about-us/staff.html, Twitter: shaned07 (https://twitter.com/#!/shaned07)

Erik Duval (Katholieke Universiteit Leuven): http://erikduval.wordpress.com/, Twitter: erikduval (https://twitter.com/#!/erikduval)

Dragan Gasevic (Athabasca University): http://dgasevic.athabascau.ca/, Twitter: dgasevic (https://twitter.com/#!/dgasevic)

George Siemens (Athabasca University): www.learninganalytics.net, Twitter: gsiemens (https://twitter.com/#!/gsiemens)


Course Outcomes:
At the conclusion of this course, participants will be able to:

1. Describe learning analytics and how it differs from related concepts such as educational datamining and academic analytics.
2. Analyze, plan, and deploy a small learning analytics pilot
3. Develop a matrix of prominent learning analytics tools and the particular analytics strategies each tool addresses.
4. Evaluate current state of learning analytics technologies and describe the benefits and drawbacks to open source and proprietary tool sets.
5. Evaluate and describe the role of semantic web and linked data in next generation educational content.

Technology Used:
Various technologies will be used throughout this course. As the course progresses participants will share additional tools, so the tool set will increase.

Tools for taking the course:
Blogs
Google Groups
Blackboard Collaborate
Daily Newsletter
Twitter
Diigo
etc

Tools for analysis:
SNAPP
CMAP or VUE or Cohere
Many Eyes
NodeXL
R
Gephi
Gapminder
etc

Data sources:
OECD FactBook
Open data sources: data.gov, Guardian data
etc

Course Schedule:
Week
Topic
Dates
1
Trends and context: why learning analytics? Why now?
January 23-29
2
What are learning analytics?
January 30-February5
3
Cases and examples of implementation of learning analytics analytics
February 6-12
4
Smarter curriculum: semantic web, linked data, and learning content
February 13-19
5
Privacy and ethics: principles for governing LA use and implementation
February 20-26
6
Tools, methods, and levels of learning analytics
February 27-March 4
7
Open Learning Analytics
March 5-11
8
Planning: Society for Learning Analytics Research
March 12-18

Guest Speakers:

January 31: Ryan S.J.d. Baker
February 7: John Campbell
February 14: Dragan Gasevic
February 21: Erik Duval
February 28: Shane Dawson
March 6: Simon Buckingham Shum

Live sessions will be held weekly on Tuesdays at 1 pm Mountain time (http://www.timeanddate.com/worldclock/fixedtime.html?iso=20120124T13&p1=80 to different timezones). All live sessions will be held here in Blackboard Collaborate:
https://sas.elluminate.com/m.jnlp?sid=2008104&password=M.13942243B0B58B854EE5D590716D09

How to participate:

This course has two components:
1. Asynchronous interaction through blogs, twitter, and google groups
2. Synchronous interaction through Blackboard Collaborate for weekly lectures and discussion sessions

Please see these tutorials and general information on the course and how to participate: http://lak12.wikispaces.com/Help_Resources

Course tag: LAK12
Diigo Group: http://groups.diigo.com/group/lak2012
Biblio: http://lak12.wikispaces.com/Bibliography



Course syllabus is licensed: CC-BY-SA