Visible Learning for Literacy, Grades K-12

Implementing the Practices That Work Best to Accelerate Student Learning

Douglas Fisher, Nancy Frey, John Hattie

• Editorial: Corwin
• Año: 2016
• ISBN:
  9781506344034
• Edición: 1
• Categoría: Education
• Categoría: Teaching Languages

Ensure students demonstrate more than a year’s worth of learning during a school year

Renowned literacy experts Douglas Fisher and Nancy Frey work with John Hattie to apply his 15 years of research, identifying instructional routines that have the biggest impact on student learning, to literacy practices. These practices are “visible” because their purpose is clear, they are implemented at the right moment in a student’s learning, and their effect is tangible.

Through dozens of classroom scenarios, learn how to use the right approach at the right time for surface, deep, and transfer learning and which routines are most effective at each phase of learning.

1 Laying the Groundwork for Visible Learning for Literacy

© Hero Images/Corbis

Every student deserves a great teacher, not by chance, but by design.

Who can disagree with that? Who doesn’t believe that every student, in every classroom, deserves to be educated in ways that build his or her confidence and competence? Let’s take apart that sentence and explore some of the thinking behind each word or phrase.

• Every student (not just some students, such as those whose parents can afford it or those who are lucky enough to live on a street that allows them to attend an amazing school)
• deserves (yes, we believe that students have the right to a quality education)
• a great teacher (one who develops strong relationships, knows his or her content and how to teach it, and evaluates his or her impact. This is where a lot of debate enters the picture because people differ in their understanding of what great teachers do and how they think)
• not by chance (meaning that we have to move beyond the luck of the draw that permeates much of the educational landscape. Children’s education should not be left to chance, with one year being amazing and another average or awful. Further, children’s education should be left not to whatever sense of challenge or level of expectation a teacher may have, but to an appropriate high level of challenge and expectation)
• but by design (yes, there are learning designs that work, when used at the right time. In fact, the literature is awash with evidence of designs that work and those that do not work)

The design we’re talking about, the one that has great potential for impacting students’ learning and allowing all of us to be great teachers, is John Hattie’s Visible Learning (2009). So what do we mean by visible learning? In part, it’s about developing an understanding of the impact that instructional efforts have on students’ learning. Notice we didn’t limit that to teachers. Students, teachers, parents, administrators—everyone can determine if the learning is visible. To do so, students have to know what they are learning, why they are learning it, what it means to be “good” at this learning, and what it means to have learned. The adults also need to know what students are learning, why they are learning it, what it means to be “good” at this learning, and what it means to have learned. Some things are learned at the surface level, others at the deep level, and still other knowledge is available for transfer to new situations. Each of these surface, deep, and transfer levels of learning is important; each of these is the focus, in turn, of one of the following three chapters.

We believed that it was time to apply John’s previous work with visible learning to the world of literacy learning. We think that visible learning for literacy is important for several reasons:

1. Literacy is among the major antidotes for poverty.
2. Literacy makes your life better.
3. Literate people have more choices in their work and personal lives, leading to greater freedom.
4. Literacy is great at teaching you how to think successively—that is, making meaning one step at a time to then build a story.
5. Literacy soon becomes the currency of other learning.

Visible learning for literacy requires that teachers understand which strategies and instructional routines are useful in which teaching situations. There is no single right way to develop students’ literacy prowess. But there are wrong ways. In Chapter 5, we will turn our attention to a specific list of practices that do not work in the literacy classroom. For now, we will focus on those that do.

There are certain things that great teachers know:

• Great teachers understand that different approaches work more effectively at different times. For example, a great approach for developing students’ surface-level learning is not likely to ensure deep learning, much less transfer. But there are times when their surface-level learning is what students need.
• Great teachers know that different approaches work for some students better than for other students.
• Great teachers know that different approaches work differently depending on where in the learning process a student may be.
• Great teachers intervene in specific, meaningful, and calculated ways to increase students’ learning trajectories. This requires that they understand and share challenging, yet specific and appropriate, goals with students; monitor progress toward those goals; provide and receive feedback; alter their actions when learning is not occurring; and share in the joy that comes from working with students to meet the learning goals.

Visible learning asks teachers to go even a step further. It asks us to create the conditions necessary for students to become their own teachers. We mean not that classrooms should be surrendered and the students be told to teach themselves, but rather that the expectation of the instruction students receive involves student engagement to the degree that they want to, and do, learn more and better—even beyond the classroom walls. This requires that teachers become learners of their own teaching, which is the major focus of this book.

The Evidence Base

Meta-Analyses

The starting point for our exploration of literacy learning is John Hattie’s books, Visible Learning (2009) and Visible Learning for Teachers (2012). At the time these books were published, his work was based on over 800 meta-analyses conducted by researchers all over the world, which included over 50,000 individual studies that included over 250 million students. It has been claimed to be the most comprehensive review of literature ever conducted. And the thing is, it’s still going on. At the time of this writing, the database included 1,200 meta-analyses, with over 70,000 studies and 300 million students. A lot of data, right? But the story underlying the data is the critical matter.

Before we explore the findings and discuss what we don’t cover in this book, we should discuss the idea of a meta-analysis because it is the basic building block for the recommendations in this book. At its root, a meta-analysis is a statistical tool for combining findings from different studies with the goal of identifying patterns that can inform practice. It’s the old preponderance of evidence that we’re looking for, because individual studies have a hard time making a compelling case for change. But a meta-analysis synthesizes what is currently known about a given topic and can result in strong recommendations about the impact or effect of a specific practice. For example, there was competing evidence about periodontitis (inflammation of the tissue around the teeth) and whether or not it is associated with increased risk of coronary heart disease. The published evidence contained some conflicts, and recommendations about treatment were piecemeal. A meta-analysis of 5 prospective studies with 86,092 patients suggested that individuals with periodontitis had a 1.14 times higher risk of developing coronary heart disease than the controls (Bahekar, Singh, Saha, Molnar, & Arora, 2007). The result of the meta-analysis was a set of clear recommendations for treatment of periodontitis, with the potential of significantly reducing the incidence of heart disease. We won’t tell you too many other stories about health care or business, but we hope that the value of meta-analyses in changing practice is clear.

The statistical approach for conducting meta-analyses is beyond the scope of this book, but it is important to note that this tool allows researchers to identify trends across many different studies and their participants.

Effect Sizes

In addition to the meta-analyses, the largest summary of educational research ever conducted (Visible Learning) contains effect sizes for each practice (see Appendix, pages 169–173). An effect size is the magnitude, or size, of a given effect. But defining a phrase by using the same terms isn’t that helpful. So we’ll try again. You might remember from your statistics class that studies report statistical significance. Researchers make the case that something “worked” when chance is reduced to 5% (as in p < 0.05) or 1% (as in p < 0.01)—what they really mean is that the effect found in the study was unlikely to be zero: something happened (but there’s no hint of the size of the effect, or whether it was worthwhile!). One way to increase the likelihood that statistical significance is reached is to increase the number of people in the study, also known as sample size. We’re not saying that researchers inflate the size of the research group to obtain significant findings. We are saying that simply because something is statistically significant doesn’t mean it’s worth implementing. For example, say the sample size is 1,000. In this case, a correlation only needs to exceed 0.044 to be “statistically significant”; if 10,000, then 0.014, and if 100,000, then 0.004—yes, you can be confident that these values are greater than zero, but are they of any practical value?

That’s where effect size comes in.

Say, for example, that this amazing writing program was found to be statistically significant in changing student achievement. Sounds good, you say to yourself, and you consider purchasing or adopting it. But then you learn that it only increased students’ writing performance by 0.3 on a 5-point rubric (and the research team had data from 9,000 students). If it were free and easy to implement this change, it might be worth it to have students get a tiny bit better as writers. But if it were time-consuming, difficult, or expensive, you should ask yourself if it’s worth it to go to all of this trouble for such a small gain. That’s effect size—it represents the magnitude of the impact that a given approach has.

Visible Learning provides readers with effect sizes for many influences under investigation. As an example, direct instruction has a reasonably strong effect size at 0.59 (we’ll talk more about what the effect size number tells us in the next section). The effect sizes can be ranked from those with the highest impact to those with the lowest. But that doesn’t mean that teachers should just take the top 10 or 20 and try to implement them immediately. Rather, as we will discuss later in this book, some of the highly useful practices are more effective when focused on surface-level learning while others work better for deep learning and still others work to encourag...