Why Students Struggle With CER and How to Actually Fix It
I've been helping teachers with science writing standards for long enough that I can spot the moment students disconnect from the material. CER worksheets are everywhere now, and most of them aren't working the way the creators intended. The Tiger Sharks data analysis piece is one of the more common ones I've seen assigned, and it comes with its own set of problems that repeat across classrooms. The worksheet typically presents students with a data set about tiger shark feeding behavior, migration patterns, or habitat preferences — usually a table or graph — and asks them to write a claim, back it with evidence from the data, and explain the reasoning that connects the two. That sounds straightforward on paper. In practice, students routinely blur the lines between evidence and reasoning, and they treat the claim like an opinion rather than a data-driven statement. The evidence section is where most kids lose points. They'll write something like "tiger sharks eat seals because the data shows it" — which isn't evidence, that's restating the claim in different words. Actual evidence is a specific data point, a number, a trend observed in the graph. "62% of tagged sharks were observed within 5 kilometers of the coast during months 3 through 7" is evidence. The teacher grading these can tell the difference immediately, and the rubric rewards specificity.
I ran into a real issue last year when a student submitted a worksheet where the entire reasoning paragraph was just copied from the textbook paragraph about tiger shark ecology. It was accurate information, technically correct, and had nothing to do with the data set provided. The student had confused background knowledge with reasoning. Reasoning isn't where you dump everything you know about the topic. It's where you explain why the evidence supports the claim — the logical bridge. The fix was simple: I had them rewrite the reasoning using only information present in the worksheet, forcing the connection rather than letting them drift into general knowledge. It cut their score from a 4 out of 12 to an 8 in one revision. The claim itself gets handled wrong most often because students write predictions or questions instead of statements. "Do tiger sharks prefer warmer water?" is not a claim. That's a question. A claim needs to be a declarative sentence that answers the prompt directly, like "Tiger sharks show a preference for warmer waters based on the temperature data collected at each tagging site." Claims that are too broad also fall apart under scrutiny. "Sharks are important to the ocean" can't be supported by a single data table about temperature preferences. Here's something most answer keys don't address: the reasoning section benefits enormously from using transition language that signals logical connection. Words like "therefore," "because," "this indicates," and "the data suggests" aren't fluff — they're functional markers that help graders see the student actually understands causation versus correlation. A reasoning paragraph without any of those connectors often reads like a list of facts rather than an argument.
The worksheet itself has a notable flaw I've seen cause consistent problems. The data set uses rounded percentages and small sample sizes, which means students who write overly precise claims get penalized for accuracy they can't justify. If the table says "approximately 58%" based on 25 observations, a claim stating "exactly 58%" is technically unsupported. I always tell students to use hedging language in their claims when the data is limited — "suggests," "indicates," "appears to" — rather than making definitive statements the numbers don't carry. Another thing that trips people up: the difference between describing the data and using it as evidence. Writing "the graph goes up from March to August" is description. Writing "the increase in coastal sightings from March to August suggests a seasonal feeding pattern tied to prey availability" is using the data as evidence. The distinction matters for grading, and it's one I see students struggle with repeatedly. If you're looking for answers to check your work, the most reliable approach is to first make sure your claim directly addresses whatever the prompt is asking. Then pull specific numbers or observations from the data set as evidence. Finally, connect them in the reasoning section by explaining the relationship between what the data shows and why it matters for the claim. That structure works regardless of the specific tiger shark data you're working with.
The worksheet is useful, but it's not a substitute for actually learning how to construct an argument from data. I've seen students memorize answer templates and still fail when the data presentation changes slightly. The skill here is transferable — it's not just about tiger sharks. Once you can read a graph, extract a specific data point, and explain how that point supports a statement, you can do this with any CER worksheet that comes after it.
