Collaborative Networked Learning Overview
Much work in the information age enterprise involves collaborative, team oriented tasks. Learning workers share information with one another in order to accomplish common tasks in a small group. Professionals share information with each other, and learn something about each others specialization in order to reach consensus on a common problem. Assembly line workers have increased productivity when workers learned from each other how their different individual parts of the task fit together to produce the whole. All of these different learning workers are engaging in activities which involve collaboration.
Life-long learning in the workplace is becoming a necessity rather than an ideal. The need for collaboration is great and will continue. By facilitating collaborative methods of learning, we could help workers acquire individually and collectively the rapidly, changing knowledge required in the high-tech workplace.
3. Collaboration is a condition of learning in the information workplace.
While the worker in the industrial era factory learned how to manipulate objects and memorized actions, the worker in the modern organization learns how to think, learn and apply information to a task.
• Workers need to engage in activities that allow them to approach problems from different vantage points, testing out assumptions,and redefining meanings,i.e.creative thinking in order to develop new viewpoints.
• Workers need to engage in the social,collaborative exchange of ideas in order to pose hypothetical problems, general hypotheses, conduct experiments and reflect on outcomes. Basically, workers are learning in groups to make meaning out of information. Not only do workers need to make meaning out of the information but in order to actually perform their jobs they need to be able to share that meaning with others.
This blog is to serve as a basic resource for individuals planning, implementing, and participating in Collaborative Networked Learning (CNL) communities as co-learners. The general guidelines and discussion here draw upon published research and from experience with successful applications of different CNL models.