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 * Learning Analytics and Knowledge 2012 ** ** Syllabus **

Click here to sign up for the course: []

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

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.
 * Course Description: **

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.

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 Audience: **


 * 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)

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

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.

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

// 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 ([] 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: [] Biblio: http://lak12.wikispaces.com/Bibliography

Course syllabus is licensed: CC-BY-SA