Personalization: Pushing or Netflixlearning?

Personalization: Pushing or Netflixlearning?

What do we mean by Personalized Learning?

Personalized learning is not a goal in itself. It is rather a way to improve your learning motivation and engagement. You will improve your learning performance by better learning processes, without detours.  Personalization also implies being served exactly the content you need. Everyone is different, so everybody has it’s own learning preferences. The more this is acknowledged, the better it is for your learning.

But what is personalization? It can be seen as a container concept. It  has many dimensions, and because of this there is often debate and discussion about it. I will highlight a number of ways you can approach Personalized Learning. They are not limited.


Who is in charge?

First of all, let’s start by determining who is in charge of your learning. In a way learning is living, but what is the role or others? How is your instructor, coach, manager, co-student or instructor influencing you? In general, kids need more structure than adult learners. Of course this is not always the case. There are elementary schools, where a minimum of structure is provided. And there are adults, that prefer substantial guidance.


Differentiation: 'Personalized pedagogy with joint learning objectives'

Let's continue from this pedagogical perspective. We talk about Differentiation when the instruction is tailored to your learning preferences. The pedagogy - or learning methodology - that your instructor uses is focused on optimizing your learning process.  When using Differentiation, all fellow learners in a course or Programme are provided similar learning objectives, but every learner will be differentiated tot his or her own learning preferences.
For example, when getting insight into an abstract idea, maybe some of you learn best when exposed to many concrete examples before. Others learn best if they see the abstraction firts, before the concrete examples. If we are aware of distinctions like this, we can make a difference to learning impact. But there is no proven scientific theory of which methodology works best. So how to get somewhat nearer to know what works and what doesn't?
Fortunately IT can make a difference here. Learning algorithms can monitor your online learning activities. They can be visualized by a Dashboard. The term “Adaptive learning” is often used when online technology is applied. For example, you can analyze which activities a learner completes fast or slow. Subsequently you can provide a certain type of activity to a learner more often. As an instructor you will learn by doing and keep on varying those activities. In other words: fine-tuning  your understanding of the learner’s preference will be important.  This requires also effort to think about the key question: what is a meaningful intervention?  From a pedagogical view optimizing learning impact means also  providing challenge, struggle and stretching for the learners.

As a result of this the number of features we might attribute to each lesson can be big. That is not a problem for the learning algorithm, but may be a problem for creating learning arrangements. The larger the set of features, the longer it takes us to administer it and to get an idea of what’s a good fit. Learner Paul learns math best in a series of 5 brief lessons, with lots of fishes used as examples, with frequent review of previous concepts, and with the use of spatial metaphors, whereas another learner Rose learns math best in a series of 3 slightly longer lessons, with examples from the solar system, and a moderate amount of review of previous concepts, and the use of number line metaphors. Now suppose everyone has their own set of preferences. How are these specialized lessons going to be generated?

To wrap this up: With differentiation it is important all fellow learners in a course or programme are provided similar learning objectives. Despite this equal starting point, it will require special attention to the learning design of  the differentiated instruction. Begin with small steps of differentiation for specific groups and keep on monitoring which assignment of intervention works and which doesn't.

Individualization: “Different tempo, same pedagogy and learning objectives”

Individualization refers to instruction, which is tailored to your speed of learning. All your fellow learners have the same learning objectives. The learning methodology is also the same, but anyone can learn the content in his or her own pace. For example you will take more time to master a subject than your co-learner. Learners can skip activities or modules they already master. On the other hand, it is possible to repeat certain topics, asking for more instruction. There is no differentiation in pedagogy, but those who want or need more coaching or instruction will get it. From this perspective "Personalized" means "Personalized pace".


Personalization “Do it yourself learning”

Personalization refers to instruction that is paced to learning needs, tailored to learning preferences, and tailored to the specific interests of different learners. In an environment that is fully personalized, the learning objectives and content as well as the method and pace may all vary (so personalization encompasses differentiation and individualization). It may mean different content for different students, depending on their interests. "Personalized" here means 'Personalized Learning Journey'. An adventure with no predetermined but evolving learning objectives.


Content adjusting itself to you: “Netflix learning”

Leaving the pedagogical track of personalization, we quickly arrive in more general Personalization trends often used for consumers. It is the kind of Personalization companies like Netflix and Amazon are using. Algorithms determine your online behavior. Based on your online you are provided tailor made content to consume. This perspective of Personalization is completely learner centered. There is no real person guidance or coaching.  This form of personalization in education evokes strong debate. There are valid pedagogical arguments that will make you think about this. Especially when there is no real person instruction involved. First of all your learning impact often will be greater when you will be challenged, stretched and pushed by someone. Allow mistakes getting out of your comfort zone and so on. Secondly, algorithms might create a tunnel vision for you. You will be presented the "same" kind of content again and again. Would that make you a curious learner?

So, Differentiation and Individualization emphasize on the relationship between student and supervisor and the degree of structuring. Personalization is more learner centered but leaves all possibilities of co-working, instruction and coaching. "Netflix learning" is on the far end of the Personalization Slope.


Learning situation, context and learning technology

Also context, place and your specific online learning environment affect the degree of personalization. I will find another time to discuss these.


Inspiration and resources:

Personalization vs. Differentiation vs Individualization-Barbara Bray and Kathleen McClaskey
Personalized learning according to expert M Jackson
Ben Betts – What do we mean by Personalization?
Daniel Willingham – Three Versions of Personalized Learning, three challenges