Building Blocks of Personalized Learning
The term “personalized learning” has skyrocketed in popularity in the last few years. Some in the education community see it as the silver bullet for improving student learning.
Its promise--that learning and instruction can be varied based on the individual--makes the concept so appealing. But actually answering the question “What should I do next?” in the classroom is much more complicated.
“If learning is to be tailored to each student, we need to first ask: what do we know about learners and learning?” says Kristen DiCerbo, VP of Education Research at Pearson. She studies how education research can guide personalized learning and improve student outcomes.
She divides the evidence about what works for personalized learning into four main building blocks.
- How do students progress from novice to expert in a particular learning topic?
- How do we assess where a student is in the progression process defined in Part 1?
- What should a student do next to move forward in the progression process?
- What are the best ways to provide feedback to students, teachers and parents?
Building Block 1: The Map
How do students progress from novice to expert in a particular learning topic?
No decision about where to go next can be made without knowing the path to mastery. Whether it is students who could be learning calculus, how to compute area, or the best way to apply critical thinking skills to a passage in literature, what does a novice look like? What does an expert look like? And what does the path look like as students move from being a novice to an expert? In some fields, there is existing research on what are called “learning progressions” and “learning trajectories.” In other fields there are novice-expert studies. There are some fields, however, for which this is a new way of thinking about describing skills and attributes.
Building Block 2: The "You Are Here Sticker"
What is the best way to assess where a student is in the progression process defined by Building Block 1?
Where are students in their progression? Without knowing a student’s current state, it is difficult to know what to advise. Right now, many courseware products use end of chapter quizzes and tests. However, Pearson is evolving how evidence is gathered. Pearson is researching ways to understand a student’s position without having to test them all the time using things like unobtrusive data collection from simulations.
Building Block 3: The Map Offers Directions
What should a student do next to move forward in the progression process?
What should a student do next? What are the next activities and then the next activities and then the next activities to help a student learn? This might be at the objective level, an activity level, or a problem-solving step level. It might be based just on what is known about the student’s achievement, but could also be based on what is known about motivation, memory, and attention. Learning science already has a large body of evidence about what works in timing, when to review information, and when to move to another topic. Pearson integrates those findings into product design.
Building Block 4: Trip Review
What are the best ways to provide feedback to students, teachers, and parents?
How should information be relayed to students in a way that helps them make good instructional decisions? And, when? For example, common advice is that immediate feedback is best, but in certain situations, for example, when students are already at an intermediate level and are building conceptual knowledge, sometimes a delay for reflection is better.
Part of personalized learning is often empowering learners in taking the next step. Giving feedback that isn’t just reporting scores, but communicating results to support individual decisions is an important change. Research gives important insights that Pearson integrates into our products to assist educators and students in making these decisions.
As Pearson builds out personalized learning models for designing and developing capabilities like cognitive tutoring, and other analytical, adaptive, and implementation components of the model, we are digging deeper into each of these building blocks. This means our technological capabilities that we develop contribute to, rather than detract from, a theory of teaching and learning that will truly enable educators to personalise learning for their students.