The top experts in any professional field have something in common; an insatiable urge to continue learning. The leading figures in any discipline aren’t just masters, but perpetual students who are dedicated to expanding the scope of their knowledge; naturally, they’ll want to pass this down to those on their teams as well.
Personal learning networks are the full realization of how important it is for organizations to continue learning. Organizations that don’t rest on their laurels and work to continue learning will be those that have the best potential for developing and evolving. The world is constantly changing, and because of that, the need for organizations to continue learning is unending.
In essence, personal learning networks are essential to making sure that professional people can remain capable of adapting to constant changes brought upon by shifts in technology and globalization. These informal learning networks are all built upon communication that is specially geared towards high-quality education.
History of personal learning
Long before any official personal learning networks were formalized, the concept of personal learning was already a longstanding concept. The use of term “personalized learning” can be traced as far back as the 1960s.
Since the concept’s inception, there have been a number of different ideas presented for a “concrete” definition of the term, and there’s yet to be an official consensus; at the same time, just about all would agree that personalized learning opens up opportunities that impersonal learning environments aren’t able to.
The closest thing to an objective definition that can be applied to personalized learning applies only to the pace and approach of the instructor. According to the US Department of Education’s National Educational Technology Plan, the instructor’s pace is referred to as “individualization,” and the approach can be referred to as “differentiation.”
The ideal personal learning network will be geared to maximizing each learner’s learning retention by individualizing the pace of information fed to them. The pace itself should be differentiated enough for retention to be optimized across the majority of the class. A perfect outcome would see every learner being able to retain all of the lessons imparted unto them, though naturally, results may vary depending on the skill of the instructor and the nature of the content.
The roots of personalized learning networks are deeply ingrained in connectivism, a learning theory for the age of digital information sharing. The original learning theories, such as cognitivism, were originally created in a time where technology wasn’t a dominant force in the way that most people learned new information.
Siemens developed connectivism as a learning theory that could be made applicable to the modern social environment, in which technology has shaped people’s lives and communication in a manner that’s too significant to be ignored.
In the past, the speed with which people developed their base of information was comparatively slow. The acceleration of learning speed is more than double than what was considered to be the standard just two decades ago.
Whereas the learning of yesteryear was largely confined to static capsules of books and academic buildings, the learning environment of today is nebulous and demands a more dynamic range of options for retention; every company must be an elearning company. This is the foundation of connectivism at its core.
Personalization for and by the learner
In the year 2005, Dan Buckley described personal learning environments as being divisible by two ends of a “spectrum”: one end being focused on personalization for the learner, and another being based in personalization by the user themselves.
Personalization for the learner happens when the teacher specifically adjusts their learning program for the unique needs of their pupils, and personalization by the user is made possible after pupils are given the skills to calibrate their own learning experience.
In the year 2006, Buckley’s spectrum of personal learning specialization was adopted by Microsoft’s Practical Guide to Envisioning and Transforming education. The choice between which end of the spectrum to design a personalized learning program for will generally come down to a stylistic choice, and naturally, it will depend upon the unique needs who are involved in the program.
Connectivism works through interlinking all of the different, modern information sources at our disposal. Personal learning networks take the principles of connectivism and apply them into an education model that is geared towards maximizing retention and relevance for each individual learner. A learner’s potential to know more is recognized and prioritized over the limits of what they already understand at any point in time. This quality over quantity education vehicle, a teaching model that is more K-selected than r-selected, should continue to be the dominant force in furthering education for both children and adults like in the digital age.