Perceptions of Distance Learning

Perceptions of Distance Leaning

This application will reflect on the current and future perceptions of distance learning in our society.  This essay will explore how I can be a proponent for improving societal perceptions of distance learning and how I can be a positive force in the improvement of distance education.  Lastly, I will examine perceptions of distance learning in the future (i.e. 5 to 10 years and in 10 to 20 years) as it relates to lifelong learning for the adult learner.

Simonson, Smaldino, Albright, & Zvacek (2012), stated that we should examine “learner attributes and perceptions as well as interaction patterns and how they contribute to the overall learning environment (p. 64).   Simonson et al, (2012) goes on to describe that Instructional Designers (ID) should not focus on which medium is best (i.e. technology) but we should focus on “what attributes of the medium can contribute to a positive, equivalent learning experience” (p.64).   When I explore how to improve societal perceptions of distance learning, I will look at the attributes of the medium (i.e. the technology proposed) and examine if the technology proposed is the best means to deliver that learning material. 

To be a positive force in the improvement of distance education I feel that it is important to continue my education past Walden University and by keeping abreast of the latest literature or joining trade Associations.  To be a positive force in the improvement of distance education is to take the skills and formal education that I learned at Walden University to my current employer and beyond.  Many trade associations such as The Association for Talent Development (ATD, formerly ASTD) have professional guidelines in ethics that can strengthen my professional development and field.

My thoughts on what the perceptions of distance learning will be in the short term and long term are closely related to what I think what will be the future of distance learning.  Jeff Cobb in book his titled Leading the Learning Revolution describes the importance of informal learning.  Cobb (2013) coined the term “the other 80 percent” in which he describes that in “some estimates, as much as 80 percent of our learning happens in an informal manner” (p. 117).  Leh (2015) in his article for Talented Learning describes the latest technologies that he predicts in the near future are the expanded use of gamification, social learning and mobile learning. To examine the short term perception of distance learning (i.e. 5 to 10 years), ID’s need to explore how to deliver learning material that is assessable (e.g. mobile technology) and informally (e.g. gamification or through social interaction).  In the short term, ID’s and software companies who will deliver learning material conveniently and informally to the adult learner will gain the acceptance of the distance learner.

I predict the perceptions of distance learning for the long term will be linked on how closely the learning technology is perceived by the public (in this case the adult learner).  To explore my vision of the future of DL is to look at trends in web development.  As ID’s at Walden University, we have been exposed to the term Web 2.0 and how it allows users to receive information, as well as, “contribute to the conversation and make it a richer experience” (Strickland, 2008, para. 6).  The next wave in web development has been labeled as Web 3.0 and it can be loosely thought of “a personal assistant who knows practically everything about you and can access all the information on the Internet to answer anything” (Strickland, 2008, para. 8).  Moreover, Kalakota (2012) in his blog about predictive analytics describes predictive search as predictive learning.  He gives an example of how the latest version of Google Now:

Google uses your private data — people you know, documents, images, hangouts,  accessing your location, e-mail, daily calendar, and other info — in order to keep tabs on things like search preferences, appointments, flight reservations, payments and hotel bookings.  Or auto-suggesting restaurants from the Zagat’s guide to have dinner at. (Kalakota, 2012, para. 28).

  My prediction of learning in the next 10 to 20 years is that large enterprise systems that adults use at their work will seamlessly deliver personalized content to educate the adult learner much in the same way Google Now uses your private data.  In other words, companies and or governments will use data harvested from your email or documents and seamlessly deliver personalized education to you – as the learner. To answer the question, what will be society’s perception of distance learning?  Society will need to ask themselves if they are willing to accept corporations or the government to harvest large amounts of data from them.  Skeptics of the future of predictive learning will feel that his technology be too intrusive or reach too far into their personal lives. Proponents will suggest that it will deliver personalized education seamlessly to learners.  Moreover, it will deliver training / education via a personalized assistant before the learner realizes they need it.  As with two extremes, the truth probable lies somewhere in the middle.

In conclusion, this essay reflected the societal forces in the world that can either advocate or skeptically embrace the future of distance learning and how we as ID’s can use our influence in field of distance learning.

 

References

Cobb, J. (2013). Leading the learning revolution the expert's guide to capitalizing on the exploding lifelong education market. New York: American Management Association.

Kalakota, R. (2012, February 11). Predictive Analytics 101. Retrieved February 28, 2015, from https://practicalanalytics.wordpress.com/predictive-analytics-101/

Leh, J. (2015, January 1). Top 10 LMS Predictions for 2015. Retrieved February 25, 20145, from http://talentedlearning.com/top-10-lms-predictions-2015/

Simonson, M., Smaldino, S., Albright, M., & Zvacek, S. (2012). Teaching and learning at a distance: Foundations of distance education (5th ed.) Boston, MA: Pearson

Strickland, J. (2008, March 3). How Web 3.0 Will Work. Retrieved February 28, 2015, from http://computer.howstuffworks.com/web-30.htm