Teaching · For Teachers

Every change from raw to clean, written down so it can be repeated.

Record each cleaning step with the rule you applied and how many records it touched. The summary totals the changes by kind, checks that the raw count minus removals matches the cleaned file, and points to any change made without a stated rule.

Start a change logWhat you get
$19one-time · every device you sign in on
Buy · $19

Included with Caveat Classroom and Whole-school licenses. Or get it in the For Teachers toolkit, $79 for 72 items.

The change log

One log per dataset. Describe changes only; never paste student records here. The example is made up.

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What you get

Teaching · For Teachers$19 · included with Classroom and Whole-school licenses

What you finish with
For each dataset, a dated record of every cleaning change with its rule and size, and a reconciliation of raw and cleaned record counts.
Who it is for
Teacher researchers, district data and assessment staff, graduate students and evaluators preparing school data for analysis.
Format
Browser log with a changes table. Several saved records; printed with the summary or as a blank log; CSV of the changes table to keep beside the cleaned file; export and import a file.
Access
$19 one-time, yours on every device you sign in on; the tool opens once you are signed in with it. Included with Caveat Classroom and Whole-school licenses. Also in the For Teachers toolkit ($79) and the Teaching Suite pass ($199), and 1 more bundle. Everything you type stays in this browser; nothing is sent to Caveat.
Where it lives
The For Teachers space in Caveat Teaching.
Support
Questions about an order, access or a correction: team@caveatacademic.com.
Drawn for this page. Every change from the raw grid to the clean one is written down, so anyone can get from one to the other again.

How to use it

  1. Start a log with a dataset code.
  2. Describe the data, the raw record count, and confirm the raw file is kept read-only.
  3. For each cleaning step, add a row with the variable, kind, rule and records affected.
  4. Enter the cleaned record count when you finish.
  5. Fix what the summary flags, then save the CSV with the cleaned file.

Start a change log

What the log is for

Why log cleaning

Cleaning decisions change results: dropping students with too few scores, treating a 999 as missing, merging categories. Writing down each rule, in order, lets a colleague or reviewer rebuild the cleaned file from the raw one and judge whether the choices were reasonable. Keeping the raw file untouched makes that possible.

Counts should reconcile

The raw count minus the records removed should equal the cleaned count. When it does not, some change went unlogged. The summary does that arithmetic so the gap shows before analysis starts.

What this log is not

It records changes; it does not clean data or store it. Keep student data where your district or protocol requires. Logs stay in this browser.

Sources

  1. Broman, K. W., & Woo, K. H. (2018). Data organization in spreadsheets. The American Statistician, 72(1), 2–10.
  2. Wilson, G., Bryan, J., Cranston, K., Kitzes, J., Nederbragt, L., & Teal, T. K. (2017). Good enough practices in scientific computing. PLOS Computational Biology, 13(6), e1005510.
  3. Institute of Education Sciences. Standards for Excellence in Education Research (SEER), on transparent and reproducible methods (ies.ed.gov/seer).
  4. Family Educational Rights and Privacy Act, 34 CFR Part 99.

The example dataset is made up. The log documents cleaning decisions; it does not store or process data. Support: team@caveatacademic.com.