Distributed_Learning_Applications

6. What situations are best for applying Distributed Learning? Attending a traditional or residential learning environment to gain new knowledge or skills demand major time commitment. For working professionals with family responsibilities, the pursuit of knowledge and training in the traditional manner is gradually becoming unattainable (Atieh, 1998). However, advances in computer and communication technologies have provided new distributed learning opportunities for adult learners. In addition, according to Knowles (1984), adults are self-directed learners. Self-directed learning is an “activity for which the learner takes the initiative and responsibility for the learning process” (French, 1999, p. 16). Self-directed learning places the learner rather than the teacher in charge for some or most of the learning process. In order to use the Internet-based materials effectively and move away regarding the teacher as “sage on the stage,” learners must learn to be self-directed and not remain passive receptors of knowledge. The ultimate goal is to increase access to knowledge and help learners to become life-long learners (French, 1999).


 * a. Does Distributed Learning work for any students in any learning environment?**

b. When is Distributed Learning used best? Distributed Learning has no boundaries and when it is “used best” is still being defined. The National Science Foundation Task Force on Cyberlearning emphasize that the “transformative power of information and communications technology for learning, is from K to grey” (NSF 2008). The authors reference of "K to grey" is a unique way of describing life-long learners as young as Kindergarteners to the mature learner with greying hair engaged in using techology as an educational tool. Distributed learning (DL) can be used in combination with traditional classroom-based courses, with traditional distance learning courses, or it can be used to create virtual classrooms available anyplace, any time, delivered on demand. With the advancement of DL, the barriers of distance and time have been broken down. Students separated in time and space from their peers and the instructor now has a viable option for learning. The distributed learning experience can also be tailored to accommodate those with learning disabilities or alternative learning styles.

The intended audience for distributed education can be segmented into numerous categories, ranging from traditional students seeking additional flexibility to “recreational learners” engaged in expanding their personal knowledge (Oblinger, D., Barone, C., & Hawkins, 2001).  Further examples of those benefiting from the transformative power of distributed learning: The U.S. Department of Defense uses distributed simulation technology to create virtual battlefields on which learners at remote sites develop collective military skills (Orlansky & Thorp, 1991); "Knowledge webs" enable distributed access to experts, archival resources, authentic environments, and shared investigations. Distributed science projects enable conducting shared experiments dispersed across time and space, each team member learning more than would be possible in isolation about the phenomenon being studied and about scientific investigation (Dede, 1996); and “Open educational resources” (OER) are educational materials and resources offered without cost for anyone to use anytime and under a license to remix, improve, and redistribute (Atkins et al., 2007).
 * K-12 students
 * Degree-completion adult learners are working to complete a degree at an older age.
 * Professional enhancement learners are seeking to advance their careers or shift careers.
 * Corporate learners work for corporations and are seeking education to maintain or upgrade their skills.

Today distributed teams in research laboratories, businesses, and education can collaboratively conduct their activities using Internet telephony, videoconferencing, and screen sharing and be “together” in immersive graphic worlds. Scientific work further incorporates shared data repositories, software data-analytic workbenches, and remote instrumentation in collaboratories (Bos, Zimmerman, Olson et al., 2007).