Personalized learning is now a buzzword in the Education industry. Almost every month, one hears of a new technology company that has devised yet another way (mostly an algorithm) to personalize learning. Technology, especially cognitive computing, certainly has enormous potential to deliver personalized learning at scale. But we will defer a discussion on how to achieve this for later. For now, let us reflect on the following questions: what exactly is personalized learning? And, why should we strive to personalize learning?
What is personalized Learning?
Given all the excitement around personalized learning, it is interesting to note that there is no single, commonly accepted definition of what constitutes personalized learning. A recent report by the US Department of Education defines personalized learning as follows: "Personalized learning refers to instruction in which the pace of learning and the instructional approach are optimized for the needs of each learner. Learning objectives, instructional approaches, and instructional content (and its sequencing) may all vary based on learner needs. In addition, learning activities are meaningful and relevant to learners, driven by their interests, and often self-initiated."
However, at the core of any personalized learning approach are two central tenets:
- Understanding the learner deeply – In terms of learning abilities, prior knowledge, interests, goals and contexts (collectively, the learner's "profile"), which shape his/her learning needs at any point.
- Determining a learning pathway tailored to the learner's needs – In terms of selection and sequencing of learning objectives, instructional approaches, learning activities, content or assessments.
But, why do we need personalized learning in the first place? We can approach this question from two directions the innate differences between individual learners that call for personalization, and the failure of the traditional one-size-fits-all model of education to deliver satisfactory outcomes.
Why personalize? Nature and nurture in learning
The key reason why we need personalized learning is that each learner is unique. This is intuitively understood from the wide variation in learning outcomes that one observes amongst almost any group of learners placed within the same learning context. Traditionally, educators have attempted to explain this in terms of differences in environmental factors (e.g. a learner's social-economic condition), or learner behaviour (e.g. lack of engagement or effort). However, recent research in genetics suggests that there is something more fundamental going on a replay of the classical nature vs. nurture debate from psychology, but in the context of an individual's learning abilities. New light is being shed on what has traditionally been a little understood, or even a taboo subject.
In an insightful study, researchers analyzed genetic data and standardized assessment results of 12,632 sixteen-year-old twins, with an equal proportion of identical twins (100 percent genetic similarity) and fraternal twins (sharing on average 50 percent genes that differ between people). The analysis revealed that genetic differences explain a substantial proportion between 54 percent to 65 percent- of the variation in academic performance between individuals, with environmental factors (school and family combined), explaining 14 percent -21 percent. Interestingly, researchers found that academic achievement across all subjects were highly correlated, with a common gene pool (yet to be pinpointed) contributing to this. Moreover, intelligence (IQ scores) seemed to account for slightly less than half of the genetic component, which suggests that other inheritable traits (some which can also be stimulated or weakened by the environment) such as curiosity, determination and memory may play a significant role.
These results at the intersection of genetics and learning are important for several reasons. First, the findings provide a biological basis to explain the difference in learning abilities across individuals and offer scientific evidences that genetics has a key role to play in a person's innate learning proficiencies. Second, they reinforce that environmental influences that "nurture" a learner are important in shaping learning abilities, but indicate that "nature" the innate abilities an individual is born with may be playing an even more influential role.
Most tellingly, such research suggests that it is time to do away with the traditional notions of "good" students and "bad" students, and especially the stigma associated with poor academic performance. Instead, we must acknowledge that individuals are naturally endowed with unique learning abilities and therefore they require highly tailored approaches to reach similar levels of mastery (just as they need healthcare approaches tailored to their unique physical conditions and not averaged over their neighbors').
Personalized learning is thus not a merely good-to-have approach to learning; much like education itself, it should be viewed as a fundamental right of every individual to reach his or her fullest potential irrespective of the starting point.
The limitations of one-size-fits-all in today's world
If personalized learning is a vision, one-size-fits-all is the reality that we have lived with for centuries. We have all experienced this nightmarish antithesis of personalization large groups of learners with widely varying needs and interests being packed into one room, all being instructed in exactly the same way, using the same set of content in an identical sequence, for the same duration of time, in an assembly-like approach to education with the hope that at the end of it, like the products churned out by a factory, they will all accomplish the same levels of mastery and demonstrate comparable outcomes. Little wonder then, that a commonly held view on the origins of this model suggests that it was inspired by the needs of the industrial age the necessity to train large numbers of people on a very standard skill set, with time spent on the factory floor, adherence to operating procedures and deference to authorities, being metrics of success that naturally found a reflection in the school system. To be fair, this model also drove economies of scale that for the first time, made education available to large sections of the society, instead of a privileged few.
The industrial revolution is long behind us. We are now at the dawn of the knowledge age that requires a completely different set of competencies for the workplace the ability to learn quickly and continuously, the ability to think independently and critically, to question, to assimilate and analyze, to innovate and solve problems; to excel in team work and collaboration, communication, personal management and organization. Unfortunately, our education systems have barely evolved in the past few centuries. Our pedagogy remains rooted in the industry age, but we demand individuals who are ready for the age of knowledge. This is a classic case of misplaced expectations, the first victims of which are the learners as evidenced from the high drop our rates worldwide, frequently motivated by factors that point to a disillusionment with the school system "I was bored", "I was failing too many classes", "School was not relevant to my life" being amongst the top causes as reported by a survey. Industry data showing large sections of graduates unsuitable for jobs, or positions left vacant by employers for want of skills provide further credence that there is a wide gulf now between education and employment.
Personalized learning by itself will not address all the needs of the new age significant changes are necessary in policy, curriculum, content and assessment methods to make learning relevant, effective, engaging and to align with employment needs. However, if one-size-fits-all was meant to power the industrial age with a largely static body of knowledge, personalized learning with its focus on the learner as a unique individual, with existing skills, interests, abilities and distinct needs that shape personalized pathways is highly suited for the knowledge age that will require navigating through a sea of rapidly evolving information and content, and the need to acquire new skills quickly, as part of a lifelong learning journey. Early results from personalized learning practices in K-12 provide promising evidence of its efficacy.
Bikram Sengupta holds Ph.D. and MS degrees in Computer Science from Stony Brook University, NY, USA, and a Bachelor of Computer Science and Engineering from Jadavpur University, India. Sengupta joined IBM Research in 2003 where he leads the Smarter Education group that develops technologies for transforming education through deep analytics and personalization in support of blended and adaptive learning. Prior to joining Education research, he led the Services Analytics group at IBM Research India during 2008-12.