Graphic Representations of Student Achievement

Let’s interpret the data as it’s written: 80, 90, 0, check, check-minus, absent, 55, 87, absent, 77, one day late 90, check, 90, check, 12, 91, check, check, 88, absent, 84, check, check, check, check, check, absent, 3.5, B+, 3.8, 2.1, 4.0, 3.5, 3.5, check, check, check, 88.

A collection of unrelated data points helps no one. We can categorize the types of data here, of course, such as: formative versus summative, compliance versus mastery indicators. The real power, however, is to represent student learning progress graphically.

Adjust the vertical axis increments one way on a basic bar graph, and we see the scary-huge difference between the performances of two student sub-groups. Adjust them the other way, and we’re sure there is little difference and no cause for alarm. Prepare a line graph with an ascending pattern for a positive element of school climate, but then overlay a second, descending line for another positive element of school climate and watch the urgent conversations fly.

At the macro level, color-code a satellite image of a geographic region of earth in such a way as to emphasize its rich natural resources available for development, and money is made available to explore its possibilities. Color it another way, however, and natural resource development officers deny those same monies. Graphics move the world.

As a society, we like visuals. We summon deeper, personal responses to compelling data when it is presented graphically instead of symbolically. Percentages, letter grades, and rubric numbers are all symbolic: We have to translate them into what they really mean for the larger picture. By themselves, however, they mean nothing.

Seriously, what does an 86% in pre-Algebra on a final report card mean? That Stuart mastered 86% of the whole field of pre-Algebra? Was it just 86% of a sub-section, and if so, which parts of that section does he still need to learn? And does the 86% mean he carried it forward into long-term retention or only that he knew it temporarily in May but forgets it by August, or can’t apply it in varied situations?

Symbols stand in for something else, and we always have to find or create a “key” to translate them before we can use them wisely.

Communicate a low-calorie count per serving of a favorite snack symbolically (140 calories per serving), and we don’t pay it as much regard as when that single serving is pictured and we see that the company’s single-serving description is significantly smaller than our big appetite version. We are actually consuming three servings, heaping on 420 calories!

The Power of Graphics

Want to persuade those with the purse strings to support a new program? Voters to cast a vote a certain way? Consumers to choose one product over another? Create a convincing graphic.

Graphics instantly portray relationships: comparative, correlational, causal, hierarchical, sequential, proportional or inversely proportional, and patterned. With visual representations, we see trends, but we’re immediately aware of the outliers as well. We might have missed them if the data remained symbolic only. Our minds are dedicated to perceiving patterns and connections, so graphics that portray knowledge, relationships, and anomalies resonate vividly.

Figure 1. Gradual Release of Responsibility

Figure 1. Gradual Release of Responsibility

For example, notice the power of the graphic in Figure 1 to explain a teacher’s gradual release of responsibility as students build personal self-efficacy in their learning:

We quickly see that as the teacher plays the larger role at first, she whittles that down as the students’ role in the learning increases, and at each point, teacher and students have a specific, actionable statement to portray what’s happening. The lesson sequence releases of responsibility are clear, as is the relationship between the students and their learning and the teacher and her teaching.

Now that we see how things fit, we’re ready, even excited to pursue them. Without the graphic, however, this sequence might seem abstract and confusing to some teachers, and they wouldn’t engage in the ideas. Clear visualization kindles effective action.

Graphics, then, are stories quickly conveyed. There’s no heavy-lifting required—all the pieces relate and we are able to perceive the whole. As a result, we give graphic representations of student achievement and teachers’ impact more of our personal focus than we do symbolic representations, deservedly or not, and we put more energy into contemplating what they mean.

Graphics need to be clear, accurate, and user-friendly; they matter to student achievement. In Classroom Assessment and Grading that Work (2006), Robert Marzano reminds us that graphic representation of student progress and achievement is so motivating and helpful, it results in an increase of 26 percentile points in student achievement when used regularly: “Presumably, seeing a graphic representation of students’ scores provides teachers with a more precise and specific frame of reference for making decisions about next instructional steps.”

Other factors are at play, too. Data mining (the process of discovering models that fit studied data), data visualizations, and learning analytics are exploding fields of study. In addition, media/visual literacy has new currency for the 21st century consumer and policymaker, and the use of personal technology and learning apps are on the rise, so much so that many students find visual portrayal and manipulation of data everyday skills. Graphics help us interpret data quickly and compellingly.

Figure 2. Radial Graph of Linda Ronstadt's Math Performance

Figure 2. Radial Graph of Linda Ronstadt’s Math Performance

Consider the power of Figure 2’s graphic representation of a student’s progression in her learning goals not only to reveal patterns and evidence that lead to developmentally appropriate responses, but also to help all of us communicate progress clearly and contextually:

All electronic gradebooks and student records management systems now allow us to color code the data for quick pattern perception and organization. For example, we can shade data fields green when students meet a standard, yellow when they are progressing toward that standard, and red when serious intervention is required. We can post formative assessment scores in red fonts and summative scores in green. In a quick glance, we can see who is achieved each level of competence, or which standards are still a struggle for a class as a whole.

We can also represent student growth in disaggregated areas of our curriculum through multi-shaded symbols of that curriculum. In science, for example, we can depict achievement in different areas of at topic by coloring different components of a diagram a microscope, Period Table of Elements, barometer, magnet, or calipers. Or we can depict achievement through the successive attachments of pathways and switches to a master circuit design. In physical education, we can shade different systems of the body, a workout shoe, or a vertical rope climb. In English, it can be a multi-shaded shape symbolizing a style of argument, or perhaps a set of book spines set on a shelf on its way to a full “library” of knowledge and skills.

Can we perceive the change over time in student performance without the graphic representations of data? Sometimes, but it’s more efficient and compelling to work off a graphic representation of some sort. We can show great variability among one student’s skills or among students, or no variability with any of them, all of which is helpful, depending on what we’re seeking.

Figure 3. Learning Success Chart

Figure 3. Learning Success Chart

In all of this, we create robust fodder for professional analysis of our teaching and its impact on student learning, and our students get the visual representations they need to self-monitor, build executive function, and determine their next steps in learning. In short, the visuals lead to maturation, investment, and more effective reasoning. Let’s use them, and better yet, teach students to design and use graphic representations of their own learning regularly (Figure 3).