Friday, January 27, 2012

Analytics vs. Learning Analytics

(Updated: After starting this blog, I identified that I might still decide to re-name this article to something like "Learning Analytics associated terminology" instead of "Analytics vs. Learning Analytics" just to broaden the scope related to the reading topics.)

In diving into the associated readings for the Learning Analytics session, it has now become clearer as to a distinction, yet relationship, between the discipline of "Analytics" and a much newer discipline, based on "Analytics", regarded as "Learning Analytics".

As a starting point, according to Wikipedia, "Analytics" is "the application of computer technology, operational research, and statistics to solve problems in business and industry." []

Similarly, "Learning Analytics" is "the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs" ["Call for Papers of the 1st International Conference on Learning Analytics & Knowledge (LAK 2011)"] Related to "Analytics", and simplified, "Learning Analytics" is the application of Analytics within and focused on learning environments.

Phillip J. Goldstein, in "Academic Analytics: The Uses of Management Information and Technology in Higher Education" (by the Educause Center for Applied Research (ECAR)), introduces the topic of "Academic Analytics" as "the intersection of technology, information, management culture, and the application of information to manage the academic enterprise".

Goldstein, also reports how the basis of Academic Analytics (and the "research methodology for this study") relies on the thought disciplines of "business intelligence", "competitive intelligence", "data warehousing", and "information-based decision making", which also deserve to be defined here.

Goldstein also references, what sounds like an interesting resource, in the document "University of Phoenix: Driving Decisions Through Academic Analytics" (by the Educause Center for Applied Research (ECAR)).


Tuesday, January 24, 2012

Interesting Resource for further review #lak12

Learning Analytics and Linked Data (LALD2012)

located here


Promoting Learning Analytics Course #lak12

According to Wikipedia, Analytics is "the application of computer technology, operational research, and statistics to solve problems in business and industry". []

The Society for Learning Analytics Research (SoLAR) ( is currently (starting the week of January 23, 2012) promoting an online "Learning Analytics" course. The course registration and course introductory information can be accessed at

I received an e-mail invitation to participate in the course myself, so I am in now way tied to the organization, nor the course, and cannot take any responsibility for any inaccurate information I am reporting here. As it appears that this course is open to any interested persons, I have decided to initiate in helping make the course known, especially to all the Learners out there. Read all of the website instructions, and just use your own judgement on whether this is something that you want to pursue, irrespective of this announcement.

Please respond back if you decided to try to go through the registration, and report any successes or failures, for my personal knowledge, as well as anyone else who might be interested in this as well.

Best wishes and success for anyone who attempts this course.

Andy Raffalski

Learning Analytics - Introduction: #lak12

Opening video by George Siemens:

- this was informative and provided an acceptable introduction and overview to the course

Per George, here were some of the notes I captured from his introduction, for class reference:

This will be an Open Online Course for the next 8 weeks, which will lead up to the Learning Analytics conference in Vancouver some time in April or May 2012. This course is being hosted by the Society for Learning Analytics Research

This online course is different from other centralized management or learning systems.
This course is a participatory pedagogical model.
This will be a distributed course with distributed conversations.

Each week during the course participants can expect to:
- create a blog
- interact with other students and track other participants involvement in the course
- own your own space of interaction, through your blog, or choice of social media
- allows participants to form a personal learning network or structure that naturally lasts beyond the duration of the course, which serves as one outcome for the course

There will be a weekly live session through Blackboard Collaborate (instructions are provided on the website where to access Blackboard Collaborate).

Participants are being asked of various things:
- active blogging
- share resources
- contribute to the wiki
- Biblio on the main site - list other resources that might be useful to the field of learning analytics

There will be a week where we are focusing on tools and techniques
How do we analyze a text document?
How do we analyze interaction space?
How do we analyze physical world data that we capture from classroom activities?
- ask of participants to:
- share their favorite tools and techniques
- what do you do with the tools
- provide an opportunity to learn from the course instructors and other participants

Ethical and Appropriate Uses of Learning Analytics
- think together - what would be an ethical criteria
- what are the ethics that influence analytics

Comments? Questions?
Feel free to respond back, or follow my weekly blog efforts.