Learning is, well, kinda complex
Learning is, well, kinda complex
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Since the knowledge management industry emerged in the 80′s there has been great stall put on encouraging and enabling employees to learn and share knowledge with one another. Central to this of course is understanding how that whole process works. Probably the most popular methodology was Nonaka and Takeuchi’s knowledge management cycle shown on the right.
A big part of the appeal of the model was its basic simplicity. It made the learning process seem rather straightforward to understand.
Some research by Carnegie Mellon does rather shatter that illusion however. It unearthed an impressive 205 trillion instructional options available when it comes to teaching something.
The study, published in Science, underlines just how complex learning is, and therefore of course how complex trying to encourage it in the workplace is when considering the combination of different dimensions—spacing of practice, studying examples or practicing procedures, to name a few—with variations in ideal dosage and in student needs as they learn.
“There are not just two ways to teach, as our education debates often seem to indicate,” says lead author Ken Koedinger, professor of human-computer interaction at Carnegie Mellon, director of the Pittsburgh Science of Learning Center (PSLC).
“There are trillions of possible ways to teach. Part of the instructional complexity challenge is that education is not ‘one size fits all,’ and optimal forms of instruction depend on details, such as how much a learner already knows and whether a fact, concept, or thinking skill is being targeted.”
Suffice to say, with several trillion possible ways of learning, the conclusions of such a paper can appear rather ominous, so the researchers thankfully provided five recommendations to help avoid brain explosions amongst knowledge and learning type folks:
- Because trying more than 205 trillion educational options to find out what works best is impossible, research should focus on how different forms of instruction meet different functional needs, such as which methods are best for learning to remember facts, which are best for learning to induce general skills, and which are best for learning to make sense of concepts and principles.
- More experiments are needed to determine how different instructional techniques enhance different learning functions. For example, the optimal way to memorize facts may be a poor way to learn to induce general skills.
- Take advantage of educational technology to further understand how people learn and which instructional dimensions can or cannot be treated independently by conducting massive online studies, which use thousands of students and test hundreds of variations of instruction at the same time.
- To understand impact, build a national data infrastructure in which data collected at a moment-by-moment basis (i.e., cognitive tutors tracking daily how a student learns algebra over a school year) can be linked with longer-term results, such as state exams and performances in a next class.
- Create more permanent school and research partnerships to facilitate interaction between education, administration and researchers. For example, the PSLC, funded by the National Science Foundation (NSF), gives teachers immediate feedback and allows researchers to explore only relevant theories.
“These recommendations are just one of the many steps needed to nail down what’s necessary to really improve education and to expand our knowledge of how students learn and how to best teach them,” says Klahr, professor of psychology at Carnegie Mellon.Original post
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