Rightly hailed as alchemical gold for public education, Personalized Learning is failing to realize its potential. This should worry us because the fault is not in the principles of Personalized Learning, but in our failure to grasp its meaning and therefore to do the groundwork to lay a proper foundation.
To understand this, let’s define Personalized Learning as the organization, presentation, and scaffolding of learning experiences that meet the deepest needs of students. This means that the curriculum addresses learner concerns and supports agency, and autonomy; it empowers students in making meaning and addressing problems while discovering knowledge, skills, maturity, and satisfying relationships.
This is a tall order in a huge system that history has shaped around didactically teaching separate academic subjects from textbooks, worksheets, and lectures, at relatively shallow levels to prepare for tests. So Personalized Learning challenges us to think beyond testable subject knowledge and technical skills, though both these areas can be addressed in a Personalized Learning focus.
How can we move beyond a narrowly prescriptive approach to academic and technical knowledge and skills?
Personalized Learning starts with the individual learner and therefore it asks us to understand human diversities. The plural is used here because unlike the diversity of fingerprints or even blood types, in the realm of what people want to learn, how they will learn, at what rate, and for what reasons we find people are much more diverse than we can fully grasp. In fact, the combination of character and learner traits appears to be endless!
Here’s an example: two students are motivated to learn to read but are struggling. Are their difficulties at a visual or auditory perceptual or short or long-term memory level? Or is there a deficit in linguistic memory or background knowledge? Or should we be looking for cultural or personality factors or a combination of all of these?
In this example what appears as the same learning problem may occur for entirely different reasons. If we think in biological terms, we might say that at the phenotype level the problem is the same, the presenting symptoms are the same, slow development of reading skills, but at the genotype level there are a number of possible differences.
A simple example: At the genotype level one student may have poor visual or left to right acuity while the other may not hear the differences in similar letter sounds. At a more complex level, the difference may relate to a failure to develop background knowledge or narrative skills needed for comprehension.
This takes us to the crux of our failure to make good progress in Personalized Learning. While Personalized Learning says it wishes to address the unique individual differences and create learner success, in truth we have stayed at the phenotype, or surface level; we have not begun to look at learner genotypes, or the combination of learner-traits that are predictive of what, how, when, with whom, and for how long a learning experience should be undertaken. Even at the phenotype level we’ve failed to respond to obvious learner needs, like the need for immersive social support through interactions with others.
Why? Because the tools for diagnosing learning at the genotype level have just arrived via digital systems and we have not fully grasped how the vast realms of developmental psychology can be used to address learner traits on multiple continuums that range from perceptual acuity, to personality needs, affective, social, and intellectual interests and concerns.
Being able to see into people’s inner worlds to explore diversity is a vast new realm that can be compared with using the digitally enabled Hubble and Webb telescopes to peer into space. Similar hardware, whether tracking the birth of stars or a student’s visual or auditory acuity, oral or written narrative skills, or moods and enthusiasms, has delivered us to the cusp of developing a personalized pedagogy to support personalized learning.
However, to do this we need to think about what data we want to gather from psychometrics and observation in new and coordinated ways. We must see beyond categorizing in ways that risk stigmatizing or stagnating learning to ways that view people along dynamic developmental continuums where learning experiences are meaningful and are built on solid scaffolds that promote growth..
To date, STEM has been our focus along with Personalized Learning, but the Science part of STEM has been limited to our hard science, and our human sciences have been ignored. We have focused on building a knowledge economy based on hard sciences, technology, math, and engineering while ignoring our sciences of human development, learning, collaboration, culture and meaningful problem solving.
This is a costly oversight because our learning and social sciences have so much to tell us about what matters most to whom and these sciences can guide our curriculum design processes in ways that digital systems are now able to support.
To build the knowledge economy, we must broaden our definition of STEM (STEAM), not by adding more letters, like SEL, but by defining science much more broadly. We must see that we want to build a knowledge culture, which means building a learning culture within our schools.
Within our schools is a key concept. Currently most of our curriculum, including our STEM curriculum, comes from people working in offices. Likewise, the engineers creating educational software are seldom in schools. Currently marketing directs curriculum design by analyzing government policy and buyer focus groups. Teachers and learner sensitivities get little air.
If we wish to achieve Personalized Learning, we need to link our research to a new design philosophy that understands how digital systems can support an in-residence project-based design process that includes students, teachers and a diversity of curriculum artists in-residence. This system will support continuous improvement and diversification of learning resources.
The Internet was first invented to enable scientists to see what was happening in particle accelerators so they could observe and collaborate in building understanding about subatomic events. What will happen now if we build a knowledge development platform to help us observe and collaborate to build the most engaging Personalized Learning for students?