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Examining Social Networks and Collaborative Learning

Posted on the 06 October 2011 by Combi31 @combi31

Specific instructional systems like Altered Vista are utilizing a form of filtering technique to enhance the learning experience and to bolster context-sensitive learning.

Contexts, as one may expect is often lost during migration of information from one medium to another. Context loss in a broader usage is also being felt as one of the major challenges of data migration of large multinational companies.

The nature of communication is hinged completely on context during the process of communication. “Word of mouth” social networks are part being seen as part of the educational circuit that can be used by instructional systems.

Special systems approach

According to Mimi M. Recker and Andrew Walker, researchers for the Journal of Interactive Learning Research:

“In its contextual form, the system can mine the data using collaborative filtering techniques to provide personalized recommendations of web sites to an individual user. Because of this capability, Altered Vista is an example of what is called a “recommender system”.”

“In addition, because of the underlying collaborative filtering algorithm, Altered Vista can also provide recommendations of like-minded people. Thus, Altered Vista sets the stage for future collaboration and communication.”

Constant improvement

Constant improvement in the system may be seen in the way it gradually improves all existing modes of cooperation and collaboration amongst users.

In a way, new systems like Altered Vista remain unique because of the specific functions and processes that it has been able to implement. The implementation is still due to the concerted efforts of researchers.

Information filtering

The process of categorizing and storing required data is the information filtering mechanism present in the Altered Vista system. The learning system is not limited to classrooms. Rather, the globalist usefulness of such a system is manifest.

The potential use and naturalness of the system is expounded further by the two researchers:

“For example, you’ve arrived in a brand new city, and hunger pangs have erupted. How do you make that all-important decision: Where to dine? You might consult restaurant guides, newspapers, or the phone book.”

“More likely, you would ask friends with similar tastes in cuisine to recommend their favorite spots. In the end, you want trusted sources to provide you with information about the quality of restaurants to help you make the best selection.”

As illustrated above, the kind of “filtering” that is happening is based on a proactive, necessary and organic selection of specific types of data. The selection is made per demand and is done in light of specific situations.

Other applications

To some degree, many well known outfits on the World Wide Web are implementing similar strategies. Google for example, is implementing a region and language specific keyword system.

To some, the keyword system is simply a way to enhance the visibility of online merchants. But from a more scientific perspective, the keywords are the result of a strategic data filtering method.

The filtering method is implemented to enhance the experience of using a particular service on the Internet. All other repercussions are linked to other regions of the operation of the Internet.

But it remains clear that collaborative learning has a very bright future, both for actual learning and for the propagation of businesses.

Author: Benedict Yossarian
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