I’ve read and read. Trying to understand the basics of the research from the sciences of learning. Trying to integrate the research from the cognitive with the emotional domains. Trying to understand the path from research on how children, teens, and adults learn to specific practices and strategies educators can use in school design, instruction, learning activities, and assessing student learning.
One of the best sources I’ve found for understanding the cognitive and motivational domains is the Nature of Learning: Using Research to Inspire Practice published by OECD. In this article and the next, I’ll walk you through some of the highlights.
I’d probably skip the first chapter – you’ve heard it all before why change is needed. Chapter two offers a helpful review of the historical development of educational theory. For my own learning, the real value of the paper started in chapter three with these ten cornerstone findings of cognitive research:
1. Learning is an activity carried out by the learner. Teachers can’t just deliver curriculum and hope it sinks in. The trick is how to get learners to want to learn, to know how to learn, and to be mentally active. Then when teachers introduce new concepts and processes, the learners are ready to tackle it. Strategies to build make connections, student agency, motivation and engagement are all important.Teachers need to have content knowledge, pedagogical knowledge, and pedagogical content knowledge based on how students learn.
2. Optimal learning takes prior knowledge into account. Every educator knows this. However, it’s very hard to address if there is a push to cover the curriculum in preparation for tests. One big step of “meeting students where they are” is knowing where students are in terms of prior knowledge and helping them to move from there to the next step. Mistakes are important to help identify prior knowledge (and prior misconceptions). We have to ask ourselves, if we know this is important, why are we pushing so hard to cover the curriculum?
3. Learning requires the integration of knowledge structures. Children are getting information and ideas from all over the place, not just the classroom. They may be making sense of it in their own way, or it may just feel like a cluttered closet. One of the jobs of educators is to help them organize knowledge within domains and across domains. There are lots of implications for educational practice, but two jump out at me. First, competencies can be used to organize domain structures to have meaning. That’s what New Hampshire tried to do with their graduation competencies. Standards are just too small to be organizing structures. Second, interdisciplinary learning is important and schools need to be organized to support it. It’s likely that our domain silos, which often get more rigid in high school, are constraining learning.
4. Optimally, learning balances the acquisition of concepts, skills, and meta-cognitive competence. Next time someone argues that facts are all they care about and we shouldn’t be teaching concepts and meta-cognitive skills, it’s worth reminding them that if facts matter, we should turn to the facts of cognitive research. Understanding one of these without the others leaves students vulnerable when dealing with real problems in the real world. If you don’t have deep understanding of the concept, how do you know which process to use? If you can’t take a step back and see how you are dealing with a problem, how do you figure out what you need to change your behavior or build your knowledge to learn it? Being competent to take on the challenges of college and careers means having all three: concepts, skills, and meta-cognitive skills.
5. Learning optimally builds up complex knowledge structures by organizing more basic pieces of knowledge in a hierarchical way. Individuals have different knowledge structures based on individual preference and previous experiences. This is another thing educators will have to bear in mind in understanding the learner and their progression. This finding is particularly important for how students learn procedures and apply them to complex problems. We cluster what we know and need to be able to pull out the sections we need for problem-solving. I have to say, Idid wonder about this one — Is it always hierarchical? Does this finding hold true for every culture? Might culture shape how information is organized with webs, circles or other constructs possibly in place?
6. Optimally, learning can utilize structures in the external world for organizing knowledge structures in the mind. It all starts with explicit learning goals. The job of educators is to organize the learning activities and the learning environment to help students create structures to organize their learning. This is a huge topic and relates as much to school design (are schedules developed to support strong project- or problem-learning?) as it does to design of curriculum and how the classroom is organized. Remember, it’s not just content. Knowledge structures need to supporting concepts, skills, and meta-cognition.
7. Learning is constrained by capacity limitations of the human information-processing architecture. This finding is about working memory and how knowledge moves into long-term memory. Essentially, “working memory is a bottleneck” and we need to understand that and consider it in any design of schools, curriculum, and classroom practices. Getting knowledge firmly into long-term memory is critically important so that the working memory can be open to dealing with concepts and interdisciplinary learning when students go deeper. This finding is about equitably ensuring that all students have access to deeper learning. (FYI, chapter two in Breakthrough Leadership in the Digital Age by Hess and Saxberg has great information on this that could be helpful as a discussion tool.)
There are a number of practices that can help, including chunking, spacing over time so there is repetition, and simplifying learning materials. There are also a number of strategies based on students’ emotional learning that can help reduce the working memory bottleneck. Students feeling safe, warm relationships, the ability to have some control over their actions – these can help too.
8. Learning results from a dynamic interplay of emotion, motivation, and cognition. Students simply can’t be broken up into silos the way we can in organizations and domains of knowledge. Whenever we attempt to do so, we are going to be frustrated with the outcome. The problem is that researchers focus on specific areas, often pretty narrow in scope. Their professional environment demands this of them. Therefore, the demand for integrating the research and truly understanding the dynamics of emotion, motivation, and cognition is going to rest firmly in the world of educators and educator organizations.
9. Optimal learning builds up transferrable knowledge structures. I don’t think there has been much discussion in the world of competency education about what the learning sciences tell us about transferring knowledge. We want students to have flexible expertise in using what they know to solve real-world problems. The authors in the paper suggest that we can teach in ways to prepare students for transferring knowledge. For example, they state that a precondition for transfer of knowledge is that students understand “the common deep-structure underlying two problem situations rather than the superficial differences.” I don’t know enough about this to have any opinions about how we go forward. I do think we should spend more time on this cornerstone finding.
10. Learning requires time and effort. Jeff Howard explained to me a long, long time ago that efficacy is the ability to determine how much time and effort is needed to be successful and the willpower to apply it. It has stayed with me because students simply have to apply more time and effort to learn things in different domains. Students with gaps or places where knowledge never worked its way into long-term memory and can be accessed as routine are going to have to apply more time and effort. This is obviously rooted in what we now short-hand as the “growth mindset.” It’s one of the keys, along with other character traits, that we need to cultivate in students for them to be successful.
In the next article on learning sciences, I’ll highlight more from the paper The Nature of Learning.