Building a spreadsheet is a technical skill. Arguing from one is an academic skill.

THE PROBLEM

A teacher collects spreadsheet analyses. The formulas work. The charts are correct. The data is organized. When he asks students to explain their recommendation, most cannot. The spreadsheet shows what happened. The student has not decided what it means or what should be done about it. Technical accuracy was achieved. Academic argument was not attempted.

THE FOUR MOVES FROM DATA TO CLAIM

Identify a pattern worth arguing from. Not all patterns support claims equally. The student must judge which pattern is strong and specific enough to support a claim the audience should care about.

Construct a specific claim from the pattern. Not “lunch waste should be reduced” but “expanding menu choice on Mondays addresses the preference mismatch that drives the highest waste day.” The claim must be arguable.

Select which data points support the claim. Not every cell is evidence for the specific claim. Selecting the relevant subset is the academic work.

Explain the connection. “As you can see” is display. Explaining what the pattern establishes about the claim is argument. The data does not speak for itself.

WHY STUDENTS STOP AT DISPLAY

Rubrics that assess accuracy, formula use, and formatting do not assess whether a claim was made. Students produce what the rubric measures. When the claim is not on the rubric, the claim is not in the submission.

WHAT THIS LOOKS LIKE IN GUIDED SCHOLAR

Guided Scholar’s Teach Me mode delivers feedback on both the technical work and the communicative claim. When a submission describes the data without making a claim, the feedback asks: what does this data establish, and why should the audience act on it? The teacher sees what was submitted, what feedback was delivered, and how the analysis changed in response.

PRACTICAL STARTING POINTS
  • 1. Require a written claim with every submission. One sentence: what does this data establish, and why should the audience care? No claim, no analysis.
  • 2. Teach “shows” versus “establishes.” Shows describes the display. Establishes makes the claim. Teach students to move from one to the other.
  • 3. Ask students to identify the three data points that most support their claim. The selection forces relevance evaluation rather than inclusion of everything.
  • 4. Add a claim-plus-evidence criterion to the rubric. If the rubric does not require a claim, students will not make one. The criterion creates the expectation.

Sources: Harvard GSE Data Literacy Research (2019); Graham & Perin, Writing Next (2007); Mayer, Multimedia Learning (2001)