Science of Reading: The Podcast

Science of Reading Essentials: The Science of learning

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On this Science of Reading Essentials episode we're diving into the science of learning to explore how memory, cognitive load, and knowledge building can transform your literacy instruction. Host Susan Lambert, Ed.D., weaves in the insights of our experts—Natalie Wexler; Nathaniel Swain, Ph.D.; Hugh Catts, Ph.D.; Daniel Willingham, Ph.D.; Peter C. Brown; Jamey Peavler, Ed.D.; and David Rapp, Ph.D. Susan reflects on: how memory works and why understanding its processes is foundational to effective teaching; why cognitive load theory and background knowledge are game-changers for literacy instruction; evidence-based strategies that make learning stick.

Show notes:

Quotes:

"Memory is a cognitive process. It's the way the brain encodes, stores, and retrieves information." —Susan Lambert

Timestamps*:
0:00 Introduction
05:00 Memory is a cognitive process
07:00 Cognitive load theory
10:00 Role of long-term memory for reading
15:00 Process of building knowledge in long-term memory
21:00 You can't learn something new if it doesn't connect to something you already know.
24:00 Applying learning science to the literacy classroom
30:00 Power of writing
31:00 Final advice
*Timestamps are approximate

[00:00:00] Hugh Catts: To build a meaningful memory of something, you have to think about it. One of my favorite quotes is from Daniel Willingham, where he said, "Memory is the residue of thought."

[00:00:15] Susan Lambert: This is Susan Lambert, and welcome to another edition of Science of Reading Essentials, a special series of Science of Reading: The Podcast from Amplify. On these Essentials episodes, we distill the information from our expert guests on a single topic so that you come away with the critical information you need to support students and educators in your community.

And today, we're focusing on the science of learning.

[00:00:41] Natalie Wexler: If you look at those things through the lens of cognitive load theory, we're making reading and writing much harder for kids than they need to be.

[00:00:48] Peter C. Brown: What we are intuitively drawn to do as a learning strategy, rereading material, practicing something over and over and over again, those strategies are pretty much labor in vain.

They don't stick.

[00:01:00] Nathaniel Swain: If it's important, we want to build in a retrieval schedule with anything that we teach our students.

[00:01:05] Susan Lambert: All of these concepts are part of the science of learning, an important foundation to actually understanding how learning happens in general. And whether you're learning a new hobby, a new concept in science, or learning how to read, all of these things help learning.

So on this episode, you're going to pick up some information that will help you more efficiently and effectively help students learn to read and write. So I think a really good place to start is by unpacking what exactly is the science of learning. And I'd like you to hear first from Dr. Nathaniel Swain, who joined us in 2025 to discuss his book Harnessing the Science of Learning: Success Stories to Help Kickstart Your School Improvement.

[00:01:56] Nathaniel Swain: Essentially, the science of learning is a body of knowledge that has been accumulated through thousands and thousands of research studies and is not dissimilar to how we think about the science of reading, perhaps. But really, instead of just talking about literacy and the proficiency in reading, it's talking about learning in general.

So what things can we learn from how learners operate in any subject or in any learning that they're trying to do? So it's an accumulation of wisdom, of insights that scientists have found through those research studies and tried to crystallize it into accessible principles that you can use.

[00:02:29] Susan Lambert: Natalie Wexler, frequent podcast guest, also wrote a book on this topic titled Beyond the Science of Reading: Connecting Literacy Instruction to the Science of Learning.

She got especially interested in the topic when she noticed that literacy wasn't a big part of these broader conversations about the science of learning. Here's what she said during a 2025 appearance.

[00:02:53] Natalie Wexler: One of the things I've noticed is that when I go to these conferences, et cetera, that the discussion of cognitive load and the science-of-learning-informed teaching really focuses on things like science, math, maybe history to some extent, but not so much on reading, and certainly not on reading comprehension or writing.

[00:03:12] Susan Lambert: Similarly, Dr. Nathaniel Swain says that some literacy instructors haven't yet had the chance to benefit from the key tenets of the science of learning.

[00:03:21] Nathaniel Swain: Some of those principles that are just so core to how learning happens, but often missing from teacher training and from professional development that teachers might participate in. I've called them in some parts of the book unavoidable insights that you just can't not be considering when you're planning your instruction or thinking about how you put your teaching and learning together.

[00:03:41] Susan Lambert: So with the help of our amazing expert guests, let's first dive into those foundational principles of learning science, and then we'll explore how they can be applied specifically to literacy instruction.

So we're going to start our journey by talking about memory. And the reason I want to start with memory is to give you a overall understanding of the processes involved in that, and we're going to come back and review each piece of this as we go throughout this episode.

Memory is a cognitive process. It's the way the brain encodes, stores, and retrieves information, and there are a few really important stages. First, we take in and process information. All of our senses are actually involved in that, but we don't pay attention to all that information. This is all a temporary process, and it happens very, very, very quickly.

What we do pay attention to can be used by our working memory, that second stage in the process. This is where we're actively manipulating or processing that information, doing something with the information. So, for example, if we're reading a single sentence, we're actively making sense of each word we're reading, and we're processing how those words work together to communicate meaning.

We can only work with a limited set of information. And when there's too much happening in our working memory, we experience cognitive overload. After all the information is processed, it makes its way into that more permanent storage, where we can later retrieve that information for future use. This is long-term memory, and we often refer to this as background knowledge, which is critical for later learning.

This long-term memory is an ever-growing repository, so once that information goes into long-term memory, it's in a permanent storage place, and then we retrieve that information to use it later. That's that idea of activating our background knowledge. Right? So, we bring that out of long-term memory, and we use some of that information to connect it to the thing that we're learning right now.

So, memory isn't a single system, but it's a multiple interconnected process that allows us to learn from the past, function right now in the present, and also plan for the future. Essentially, memory is what enables us to retain knowledge, skills, and experiences, forming the foundation for all learning and cognition.

So, now that we've done that quick overview of memory, I want to dive a little deeper into the idea of cognitive overload by exploring the concept of cognitive load theory. Here's Natalie Wexler.

[00:06:42] Natalie Wexler: So there's something called cognitive load theory, which tells us that the aspect of our consciousness where we are taking in new information and trying to make sense of it, that's called working memory, is very limited in its capacity.

[00:06:55] Susan Lambert: Dr. Nathaniel Swain explains how students' working memory can become overwhelmed.

[00:07:00] Nathaniel Swain: We know that students get really overwhelmed when there's too much stuff coming at them, and that might be facts. It might be steps in a procedure. It might be environmental things that are happening in the classroom as well.

All of that extraneous load can contribute to an overwhelm of working memory limitations. But it's also the intrinsic load of the task as well, and students get overwhelmed if they don't have adequate knowledge.

[00:07:21] Susan Lambert: What Nathaniel Swain just said, that students get overwhelmed if they don't have adequate knowledge, brings us to a key science-of-learning takeaway.

Building students' knowledge is absolutely critical for helping them avoid cognitive overload. Here's Natalie Wexler with more on this.

[00:07:40] Natalie Wexler: And the way around that is to have relevant information stored in long-term memory, which is potentially infinite. If you have that information, you don't have to juggle it along with the new information in your working memory.

For example, if you're reading about baseball and you already know what a double play is, you don't have to think about that. You don't have to look it up. You can just attend to whatever the new information is in what you're reading.

[00:08:03] Susan Lambert: Natalie just gave us an example related to reading, but the key idea that relevant knowledge in long-term memory frees up space in working memory applies more broadly.

Here's Nathaniel Swain again.

[00:08:16] Nathaniel Swain: When we have knowledge in our long-term memory, all of these limitations suddenly disappear. So once we've learnt it, once we've got it through that narrow passage of working memory and it's in our long-term, students aren't overwhelmed by those little bits and pieces. This is how experts automatically and efficiently and almost without conscious effort are able to solve really complicated and really interesting problems.

If you see like a group of really excited sixth graders attempt a maths problem and they really are confident in their algorithms and they can't wait to unpack what the next problem is, they are ravenous for more maths problems, if you like. So they are just attacking it because it all comes from long-term memory, and it's all built upon that knowledge that they have about that problem, about similar problems, about the maths facts that allows them to see the patterns before they even need to solve the problem.

All of this essentially links back to that idea that when we have knowledge at our fingertips, or in this case, in our synapses ready to be used, we can overcome all these limitations that cognitive load theory talks about.

[00:09:15] Susan Lambert: Dr. Daniel Willingham, researcher and author of several books, including Outsmart Your Brain, Raising Kids Who Read, and The Reading Mind, spoke to us in 2025 about the particularly critical role of long-term memory for reading.

He explained that information in long-term memory supports reading even without our realizing it.

[00:09:40] Daniel Willingham: It's inherent in communication, whether it's spoken communication or written communication, that we omit a great deal of the information that's actually needed to understand our message.

The example I use in The Reading Mind is the following two sentences: "Tricia spilled her coffee. Dan jumped up to get a rag." So the thing that you'll note about that, I'm sure all listeners immediately perceive there's a causal connection between those two sentences. And indeed, almost certainly the writer would not hope that you understand just those two acts, but that Dan jumped up to get a rag because Tricia spilled her coffee.

Now, that's nowhere in the two sentences. Right? There's no hint that you're supposed to draw a causal connection, but nevertheless, you do. And in order to understand how those sentences are linked, you need to have information in memory. You need to know that spilled coffee makes a mess. You need to know that people generally don't like a mess on the floor, and you need to know that rags can clean a mess.

So your mind is very, very good at bringing up from memory the necessary facts, the facts that will help you, given the context, to connect these sentences which the writer has not explicitly connected for you.

[00:11:06] Susan Lambert: Here's more from Dan on the importance of knowledge.

[00:11:09] Daniel Willingham: Walter Kintsch, a wonderful reading researcher, had a great metaphor for this, I think.

He said, "When you have all the right knowledge, reading is like seeing, in that all of the work is happening in the background, and you're just appreciating the view."

[00:11:24] Susan Lambert: Wow.

[00:11:25] Daniel Willingham: And so in the same way, when you're reading, you're not having to do the work of figuring out, "Well, how does ... What do they mean? How did that link to this?"

You're enjoying the story.

[00:11:36] Susan Lambert: Northwestern University's David Rapp shared another way of appreciating the power of long-term memory. Using something called the resonance model of comprehension, he described how difficult it is to overcome any incorrect information that's been encoded in long-term memory.

[00:11:53] David Rapp: The resonance model of comprehension suggests when someone asks a question, lots of ideas get activated automatically in memory. So, if you were to ask me a question about Northwestern University, lots of concepts I have about Northwestern become activated.

[00:12:08] Susan Lambert: Hmm.

[00:12:08] David Rapp: Regardless of whether they're accurate or not, all of the related concepts in memory are being activated.

[00:12:13] Susan Lambert: Wow.

[00:12:14] David Rapp: So you can see how that might be a problem, because the hope would be I have activated correct information, but everything resonates this idea that related memories are resonating in response to what someone asks, and regardless of whether they're accurate or not. And if they're inaccurate, there's problems there.

Most information that you've got encoded that's relevant is going to be retrieved, and some of that could be wrong. There's lots of opportunity for people to make mistakes, sometimes based on just the way our cognitive system operates during comprehension.

[00:12:44] Susan Lambert: In sum, the foundational principle here is that storing knowledge, specifically correct knowledge, in our long-term memory is the force for reading and for freeing up space for our working memory.

And given that learning science demonstrates the importance of having knowledge stored in our long-term memory, it's not surprising that a critical part of learning-science research focuses on how to most effectively build that knowledge in long-term memory. Here's how Natalie Wexler summarizes this connection between the principles of the science of learning and the importance of building knowledge in long-term memory.

[00:13:23] Natalie Wexler: I'd say that overall what these principles of cognitive science depend on is knowledge. I mean, they're all sort of geared to enabling students to retain information in long-term memory, be able to retrieve it easily so that they can analyze it and think about it in various ways. And so, that's the basics of cognitive science as applied to teaching and learning.

[00:13:48] Susan Lambert: So how do we actually build that knowledge in our long-term memory? A lot of educators have experience with the first step. When a student is learning something new, we do a lot of practice on, let's say, a particular skill.

For example, if you're learning the sound-letter combination of T-H, "th," we're going to have students practice that. We're going to do it in what we call the gradual release of responsibility. I'm sure many of you have heard that before in terms of a high-impact instructional strategy. That means that as a teacher, I'm going to model it, I'm going to model it again, I'm going to model it again. We're going to do it together as a group over and over and over again.

And then I want to have each individual student practice that. This gradual release of responsibility model is a blocked practice model, meaning that we're practicing the same skill over and over again. Really important when we're learning a new concept. But that's not the only thing that helps us really secure the knowledge of that particular skill.

Let's dive into that a bit more by turning to Peter C. Brown, co-author of the book Make It Stick: The Science of Successful Learning. He gave us lots of fantastic information about the process of building knowledge in our long-term memory.

[00:15:18] Peter C. Brown: For something to be learned and retained, you need to help the brain do that by practicing retrieving it from memory.

Practicing explaining it in your own words, asking yourself, "How does this relate to something I already know?" There are certain things that cognitive psychologists call desirable difficulties that help make learning stick. One is practice at retrieving it from memory.

[00:15:42] Susan Lambert: So once you've taught a new skill, and you have helped students practice it over and over and over again, you're hoping that some of that block practice learning will be retained in long-term memory.

Then your students are able to bring that information out of long-term memory or retrieve that information, and the more that you practice retrieving that information, the stronger the learning is going to be. Peter provided a great example of what that retrieval practice looks like and how it can be beneficial.

[00:16:20] Peter C. Brown: That practice is most effective if it's spaced out over time. So instead of practicing your 20-foot putt over and over and over again, and going home thinking, "I've got that thing. I'm really much better at it." If you practice that at different times, different courses, that practice will be harder, but the improvement will be better because you're drawing on what you learned earlier, and you're reactivating that and building on it.

[00:16:48] Susan Lambert: And so what Peter just described is something we call spaced practice, doing it at different times, in different locations, in different contexts, and it may get a little hard, but it's a great strategy to facilitate learning. Another key strategy is called mixed practice, which we also call interleaved practice.

Let's hear Peter explain more about that.

[00:17:15] Peter C. Brown: You learn better when you mix up the practice types in the domain you're trying to master. Let's say you're trying to learn how to find the volumes of different geometric solids, like a sphere and a wedge and a cone.

The usual way math books have presented that: You learn the formula for each of those. You learn the formula for a cone, then you get 10 problems to find the volume of a cone. You get really good at it. Then you have the formula for a wedge, and then you have a formula for a sphere, and you do those in a blocked fashion, blocked by the type of problem.

[00:17:49] Susan Lambert: Mm-hmm.

[00:17:49] Peter C. Brown: You can do very well during practice, and if you're tested later, you forget a very large percentage.

The better method is to mix up those problems, have them come at you at random so that each time you get a problem, you have to identify the problem correctly and recall the formula correctly and apply it. That's more difficult. So during practice, you don't see as much improvement as you do when you block it.

So you think, "I'm not learning it as well," but when you're tested later, it sticks. You're good at identifying the correct formula and applying it. So there's three really big ideas: Retrieve it. Space it out. Mix it up.

[00:18:26] Susan Lambert: Here's Dr. Nathaniel Swain elaborating a bit on retrieval.

[00:18:30] Nathaniel Swain: That retrieval strength and the storage strength becomes stronger every time you're forced to retrieve.

So ideally, you're teaching in a systematic way where you're introducing things, but then also giving students a little bit of time to forget stuff because as they start to forget but then are asked to remember, that retrieval process does really strengthen.

And then this applies to teachers so much. If you think about great PDs that you've gone to and all these great insights, you remember all these fantastic things, you felt good about your practice, these amazing ideas you're going to implement in your classroom. If there was a big break between you doing that PD and then you going back to your classroom and trying to implement it, and potentially too big a break, you might not remember much at all.

[00:19:08] Susan Lambert: Yeah.

[00:19:08] Nathaniel Swain: And therefore, all of that learning was lost, and that's the reality. It's an occupational risk for all learners everywhere, is one of the things I say in the book, is forgetting. It's just part of it.

[00:19:19] Susan Lambert: I forget really well these days.

[00:19:21] Nathaniel Swain: Well, I think we have to. You're pruning away so much stuff that's coming at you. It's a logical thing that our brains do, but we don't want the brains to prune away things that are going to be really helpful for our learning.

So if it's important, we want to build in a retrieval schedule with anything that we teach our students so that they're exposed systematically to that before they forget all those great insights, facts, skills, procedures, whatever it might be.

[00:19:44] Susan Lambert: So those are some key strategies for new learning: retrieval practice, spaced repetition, and interleaved practice. Here's another foundational concept that Peter C. Brown shared with us.

[00:19:56] Peter C. Brown: You can't learn something new if it doesn't connect to something you already know.

[00:20:01] Susan Lambert: Dr. Hugh Catts from Florida State University elaborated on this during Season 9.

[00:20:07] Hugh Catts: To build a meaningful memory of something that you can hold on and use, you have to think about it.

One of my favorite quotes is from Daniel Willingham, where he said that "Memory is the residue of thought."

[00:20:21] Susan Lambert: I love that.

[00:20:22] Hugh Catts: If you want to remember something, you have to think about it. So, if you don't know very much information, how do you think about it? Well, you read about it in the text. But the problem is you can only get so much of the information in that text into your memory.

The advantage to having background knowledge is when you're thinking about the new information, you can retrieve knowledge that you have that's chunked into bigger bits of information so it doesn't take up as much room, if you will, in your working memory.

[00:20:55] Susan Lambert: Mm.

[00:20:56] Hugh Catts: You can use that to help you make sense of that incoming information and build a bigger memory. That knowledge gives you a place to put information, so when you read about something, it gives you a storage for the information. It's like a cubby hole that you put the mail in.

New bits of information fit into that old schema, if you will, or understanding of a particular topic. Some people refer to that as mental Velcro. I think it was Marilyn Adams who said that. It just sticks better if you already know it.

[00:21:27] Susan Lambert: Here’s Nathaniel Swain again.

[00:21:29] Nathaniel Swain: When students know a lot about a topic, it means that they've got a really enriched schema in their long-term memory, and that means an organizing system for that body of knowledge or for that concept or skill.

And schemas don't just hold facts and boring things like dates and the stereotypified view of history teaching, for example. They hold rich understandings. Schemas also hold nuances between one concept and how it blurs into another concept because brains are a pretty amazing thing.

And when you give them rich input and get students to listen to knowledgeable others—whether it's peers or reading books or listening to their teachers—they can do amazing things to enrich their schemas about many, many different topics and many different ideas.

[00:22:10] Susan Lambert: So now we understand some of the key tenets of learning science.

We’ve explored how memory works. We have discussed cognitive load theory and the limits of working memory. We’ve talked about the absolute necessity of building knowledge in long-term memory for freeing up our working memory for supporting reading and facilitating new learning. And just now, we touched on several best practices for learning and building long-term memory: retrieval practice, spaced repetition, varied practice, and the importance of building on existing knowledge.

How can these concepts be applied in the literacy classroom? Our guests have had a lot to say about that too, and we're going to use the rest of this episode to share as many of these ideas as possible. Here's how Dr. Jamie Peavler explained applying cognitive load theory to intervention work.

[00:23:05] Jamey Peavler: So, a lot of our students that are having difficulty are experiencing cognitive overload. And so, the first thing we need to think about is how are we going to minimize that for them.

And so introducing a new program is just adding to the cognitive overload, and that's because there's usually a different scope and sequence. There's usually different instructional routines. Sometimes even the language of the skill is different.

So if we can set aside the idea of introducing a new program and instead focus our core instruction on how that language and how those routines could actually be intensified in that small-group setting, we're going to minimize that cognitive overload. So the way that we want to approach that small group is: I'm just focusing very specifically on what it is that brought this child to the teacher table at this moment.

Is it a prerequisite skill that I need to go back and firm up that's standing in their way? Is it more feedback and structured practice that they need that's standing in their way? And again, if I can pinpoint what's holding them up, that becomes my lesson that I'm working on with that student or that group of students.

[00:24:14] Susan Lambert: Author Peter C. Brown described one simple shift to help bring more retrieval practice into the classroom.

[00:24:21] Peter C. Brown: Typical example is a teacher will come in and say, "Okay, last time we were together, we did these things. Today we're going to do these other things that are related to that." Here's what's better. You walk into the classroom and you say, "What did we do last time?"

[00:24:35] Susan Lambert: Mm.

[00:24:36] Peter C. Brown: "Can you tell me, what did we talk about? And what did we learn from that? Oh, good. Okay. Well, that's close, but it's a little more like that."

[00:24:43] Susan Lambert: Yeah.

[00:24:44] Peter C. Brown: "And here's how we're going to go forward today." It's a very simple shift: asking them to recall and maybe even be able to explain it to someone else in the room.

[00:24:54] Susan Lambert: Natalie Wexler offered strategies for transferring information to long-term memory and for supporting the retrieval of information.

[00:25:02] Natalie Wexler: There are two crucial tricks involved here to make this work. One is you've got to transfer information initially, new information from working memory to long-term memory. You also have to be able to retrieve it when you need it.

So to transfer it, what really helps is to attach meaning to it, and that's why talking about it or writing about it is so important, especially if you do this in your own words. It's very powerful for retrieval to ensure you can retrieve an item of information when you need it, which as I get older, I realize is not always possible. Right?

But the more you practice retrieving an item of information, the more likely you are to be able to retrieve it when you need it. So, writing is both a powerful way of transferring information to long-term memory and of retrieving it.

[00:25:48] Susan Lambert: Mm. That's, yes. You have recently been talking a lot about the impact writing can have, not just on helping retain and retrieve information, but for kids to actually process information and learn about how the structures of these things actually work.

Can you talk a little bit about that?

[00:26:08] Natalie Wexler: Yes, and I'm glad you raised that point, that it's not just about retrieving information. It is also, in the process of writing, we deepen our understanding, come to new insights, maybe realize that what we thought we understood we didn't really understand or that we have to change our mind.

So there's a distinction between what is sometimes called knowledge-telling forms of writing and knowledge-transforming forms of writing.

[00:26:35] Susan Lambert: So writing can be incredibly powerful. However, Natalie Wexler offered one learning-science-based caution about writing.

[00:26:44] Natalie Wexler: Here's the catch about writing. It's hugely important. It can help cement knowledge in long-term memory, deepen knowledge, et cetera, all these potential benefits.

But it is also really hard. It's, I'd say, the hardest thing we ask kids to do in school, so it's very easy for kids, if you're an inexperienced writer, it's very easy for your working memory to become so overwhelmed that you don't get all those benefits of writing, and you probably don't learn to write well either.

So, it is crucial to both embed writing in the content that kids are learning, both because it's going to make writing easier for them and because they'll have some information. You've got to start with some information to write about it. They will also be cementing and deepening that knowledge, but we have to make it easier.

We have to modulate that cognitive load, and one way to do that, if this is what kids need, no matter what grade level they're in, is to start instruction at the sentence level. Because if writing is hard, asking kids to write at length only makes it harder.

[00:27:45] Susan Lambert: And before we close out, I'd like to share a couple of my own ideas for bringing retrieval practice, spaced practice, and mixed practice into the literacy classroom.

Let's go back to the example of learning foundational skills or learning sound-spelling patterns. So, if I'm learning again that the letters T and H represent the "th" sound or the "th" sound, like two different ways, the idea is to practice that over and over and over again, and then another day come back and have to retrieve that information or remember that information.

"Oh, hey, do you remember what two sounds the spelling pattern T-H makes?" And then apply it in a decodable reader, for example, and read a story that uses those two sounds, that sound-spelling pattern, in two different ways. And then we can also mix it up by practicing writing those sounds or writing words with those sounds in two different ways.

And then we come back to it and do it again another day. And then maybe we mix up the sound-spelling pattern T-H with the sound-spelling pattern S-H. Different letter combination makes the different sounds, and so it's like the students won't expect what's coming next because we're mixing that practice up.

And when you do that as an adult, if you're learning something new, a new hobby or something like that, and you think about mixing up these things that you're learning. Maybe you're learning Spanish and you start to mix up some of these concepts. It's like, "Oh, my gosh. When I practiced just that one thing, it was super easy. But when I'm mixing it with other concepts that I know or just learned and I'm not quite sure, it makes it a lot harder."

And the thing is, when it's hard like that, that's when learning actually happens. That's what makes learning sticky because you're using energy or cognitive resources to actually think through and apply those things that you're learning.

So we've just shared a lot of information about foundational science-of-learning principles and also strategies for applying those ideas to literacy instruction. I know it's a lot, which brings me to something that Natalie Wexler shared toward the end of our conversation about her book Beyond the Science of Reading.

She said, "It shouldn't fall on individual educators to know everything about the science of reading and now the science of learning."

[00:30:21] Natalie Wexler: I'm not necessarily saying we should tell teachers, "Okay, you've heard about the science of reading. You have to figure that out, in addition to science of learning, and here are all these principles, and you need to figure them, understand them, and figure out how to apply them in your classroom."

That is, I think, a crushing burden, and I would not be surprised if teachers ran screaming from a room where anybody told them that.

[00:30:41] Susan Lambert: I don't want you to run screaming from your classroom, and I don't want you to be overwhelmed or overloaded with all of this information. But what I do hope you can do is go back and review each one of these concepts, and, again, apply them and think about them to what the instruction you're doing already.

What are you already doing in the classroom? And what's one or two things that I can change to make sure that I'm applying the principles of the science of learning to the instruction within my classroom to ensure that students are learning efficiently, effectively, and successfully?

Thanks for listening to the latest edition of Science of Reading Essentials, a special series of Science of Reading: The Podcast from Amplify. We've done three of these special episodes already on writing, comprehension, and dyslexia. You can find all of those episodes in our podcast feed and on our resource site, amplify.com/soressentials. Check it out for some free resources specially curated to complement these episodes.

Next time around, we're kicking off a special miniseries on adolescent literacy. First up, I'll be joined by Dr. Douglas Fisher.

[00:32:07] Douglas Fisher: If you're going to look at the body of research on adolescents and literacy, self-efficacy agency is huge.

There's a huge amount of work being done in this area: agentic beliefs, like, "If I put forth effort, are good things going to happen to me?"

[00:32:20] Susan Lambert: That's next time. Science of Reading: The Podcast is brought to you by Amplify. I'm Susan Lambert. Thank you so much for listening.