What does this mean? Teaching students to analyze graphs

Once students have learned how to correctly graph their data, the next step is for them to figure out what that graph is telling them about their data. In past years, I would talk to students about identifying trends, or looking at specific points on the graph, but I didn’t have a very robust lesson on graph analysis. That all changed in the summer of 2017 when my colleague and I went to the Stanford Academy for Excellence in Biology Teaching, a weeklong training offered by the Stanford Graduate School of Education Center to Support Excellence in Teaching (CSET) – whew, that’s a mouthful! The training incorporated a lot of information and strategies from the AP Biology Teacher Academy that was developed in partnership with BSCS, NABT, and HHMI Biointeractive. (If it’s offered in the future, consider doing this course – it was well worth it. I also participated in the year-long follow-up to earn graduate credit from Stanford.)

One of the lessons we learned was the BSCS Identify and Interpret (I2) Strategy. This strategy has students break down their analysis of a graph into two parts. The first is the Identify step, also known as “What I See”. In this step, students are identifying changes, trends or differences. The idea is that they are looking at the big picture, without a lot of specifics. They mark places on the graph where they see a particular change/trend and identify what the change or trend is. The second part is the “Interpret”, or “What It Means” step, where students assign meaning to their “What I See” observations. There is a final step in the BSCS strategy where students write a caption that summarizes the information and where students can demonstrate their understanding of the data. (Instead of having students write a caption, I had them write a supported conclusion.)

I did some direct instruction on the strategy, giving students the BSCS “What I See/What It Means” (WIS/WIM) examples, along with what they were supposed to do for each part of the strategy. Next, we looked at a sample graph – I had the graph projected on the board, so I started with an example where I identified a point, then wrote a WIS statement. I gave students a few minutes to mark their WIS points and make observations. Then I had students come up to the board, identify their WIS point, and wrote a WIS statement on the board. After all of the important points were identified, I wrote an example WIM statement for the WIS point I identified, then gave students time to come up with WIM statements for the WIS points we had on the board. Again, students came to the board and wrote WIM statements that corresponded to the WIM statements.

It seemed like they got it, so I gave students a handout with another graph for practice in the same class period. The handout* included a graph, a grid to write down their WIS and WIM statements, and a third page that gave them room to write a 3-4 sentence conclusion about how the presence or absence of soil fungus affected the growth of plants.

The WIS/WIM grid

When students finished their graph analysis, I collected the handouts. I wanted to give them a quick turnaround for feedback, so I graded them before the next class session. My feedback focused solely on their written conclusion. The assignment was worth 5 points, so I created a rubric and included student sample answers for each point value so students could see what each criteria looked like.

The basic rubric – see the handout for student sample answers

Honestly, the “What I See” step was the hardest part for my students. They could easily identify points on the graph that seemed to be important, but went right for explaining what it meant. Instead of saying “non-sterilized has a steeper slope compared to sterilized soil” for their WIS statement, they would say something like “plants grew better in non-sterilized soil than sterilized soil”. In general, though, their conclusions were pretty good, especially considering I hadn’t taught them anything about Claim-Evidence-Reasoning yet!

Later in the year, my colleague instructed students that the WIS statement should only identify a point/range on the X-axis and make an observation about what was happening at that point or range. She also instructed students that the WIM statement should describe how the X-axis affects the y-axis. I went back and had students add this information to their earlier notes, and this clarification seemed to help.

All told, this is a great strategy to help students learn how to thoroughly analyze their graphs. I think it helped them write solid conclusions, because they had identified specific parts of the graph that they could then incorporate into their conclusions. If I had reinforced the strategy more throughout the year, students would have been more comfortable with it. My goal for next year is to have a “What I See/What It Means” practice graph for each unit.

*When I print the handout for my students’ notebooks, I print it two sided, with two pages on each side. They can fold the handout in half to make a booklet that fits on one page in their composition book. My colleague joked about me making booklets, but when I taught in public school, I had to buy copy paper myself, so making booklets was an easy way to save paper.

Teaching basic graphing skills

One of the first lessons I teach each year is graphing. Now I don’t know about you, but for my students (9th grade), everything is a bar graph. EVERYTHING. I don’t know where this idea gets embedded in their brains, but it’s probably one of the hardest habits to break. I start early, reinforce it often, and grade consistently throughout the year. And, what do you know, by the end of last year, all of my students were using the appropriate type of graph!

For my biology students (regular level, 9th graders), I keep it simple. I’m only going to teach them to differentiate between line graphs, bar graphs, and pie charts. I’m teaching them the foundation and leaving it to other teachers (their math or future science teachers) to get more detailed, with concepts like scatterplots, lines of best fit, error bars, etc.

I’ve always taught scientific graphing, even before I was fully immersed in NGSS, but seeing how this fit into the Crosscutting Concepts (I’m going to abbreviate it as CCC from here) just reinforces the importance of graphing. The best fit of graphing in to the CCC is in Patterns, Cause and Effect, and Scale, Proportion and Quantity. (In addition, NSTA has prepared a great matrix of the CCC.) In the Grades 6-8 Patterns section, the matrix explicitly says that “graphs . . . can be used to identify patterns in data.” A well-plotted graph can show the relationship between a manipulated/independent variable and the responding/dependent variable. From there, students can infer cause and effect.

I have students take notes on graphing on a foldable that gets glued in their notebooks. During the presentation, we discuss what a “good” graph includes, and when to use each kind of graph.

Graphing foldable for student note-taking

There are a couple of useful acronyms that I give my students to help them remember how to properly graph their data. The first is “DRY MIX” – “DRY” means that the Dependent/Responding variable goes on the Y-axis, and “MIX” means that the Manipulated/Independent variable goes on the X-axis. I like this acronym because some textbooks or teachers will use the terms manipulated and responding to refer to variables, while others will use independent and dependent, so this acronym covers both of those bases.

The second acronym I give my students is “TAILS”. I wish I remembered where I first found this acronym, because it is so useful!

  • T stands for Title – I teach my students that their title should explain the relationship between the independent variable the the dependent variable. (I ask them to make a title that explicitly states the relationship – if they’re at a total loss, I give them a standard template of “Effect of -IV- on -DV-“.)
  • A stands for Axes – this incorporates the DRY MIX acronym to make sure the variables are on the correct axes.
  • I stands for Intervals – the number intervals on the axes should be evenly spaced.
  • L stands for Labels – the axes should be labeled with the variable and units, and there must be a key/legend if there are multiple lines or categories.
  • S stands for Scale – I tell students that their graph should take up as much space on the graph paper as possible, usually at least 2/3 or 3/4 of the space. No teeny-tiny graphs, and no graphs that go outside the boundaries of the grid (which means don’t draw your own lines at the top or right of the grid).

At the bottom of the foldable, I explain when each type of graph is appropriate. With line graphs, I struggled with how to explain it to students in a general enough way that they got it. “Tracking continuous changes in the independent variable” was confusing and not exactly correct. When I looked at the CCC, the light finally came on – a line graph is used to show the cause and effect relationship between the variables. To state it as a question, “As the scientist changes the independent variable, how does that affect the dependent variable?” I will still keep the “continuous data” part of it to help students see that if there is a continuum of the units for the independent variable, then a line graph is the best choice.

The categories of the TAILS acronym get incorporated into a 10-point grading rubric (which I won’t post because it’s not my own work product). Students get a copy of the grading rubric at the beginning of the year, and it is glued into the reference section of their science notebook. I also made a mini-rubric summary (just the categories and point values) that I print out – when I grade, I can just circle the point awarded for each category. I staple the mini-rubric to their paper so students can see where they lost points.

What I noticed last year was that by explicitly teaching graphing skills AND consistently using the graph grading rubric all year, students quickly developed their graphing skills. Most students were graphing at the 9.5-10 point level by the end of the first semester. The biggest challenges seemed to be in crafting a graph title, and in figuring out the intervals on the axes. By the end of the school year, when students were crunching data for their final projects, every student was using the appropriate graph for their data, and was correctly graphing their data.