A district trying to compare NJSLA performance levels across two or more years runs into an obstacle before any actual comparison begins: the exported data files don't reliably use the same column header for the same field from one year to the next. Two files that both report performance level, subject, and school can still fail to line up automatically, because the field that held "performance level" in one year's export might be labeled differently in another year's.

This is a data-alignment problem, not a statistical one, and treating it as the latter is how comparisons go wrong before they start.

Why the columns don't match

Column naming in a state assessment export isn't a fixed contract across years. It can shift when the state revises a reporting template, when an administration adds or renames a field, or when the underlying testing platform changes. New Jersey's own testing vendor changed for the 2025–26 school year, when Cambium Assessment replaced Pearson as NJDOE's contracted vendor for NJSLA and NJSLA-Adaptive. A transition of that scale is exactly the kind of event that can plausibly change file formats, even when the underlying tested construct, a student's performance level in a subject for a given administration, hasn't changed at all.

None of this makes the data unusable across years. It means the alignment between years has to be established deliberately, once, rather than assumed.

What the alignment step actually looks like

Hypothetical example for illustration only: imagine a district's 2024 export lists a student's performance level under a column named "Performance Level," while its 2026 export uses a column named "Level." Both columns hold the same kind of value, on the same five-point scale, for the same construct. A valid multi-year comparison requires mapping "Performance Level" and "Level" to a single output field before any year-over-year analysis happens, not assuming that a similar name will be inferred correctly on its own.

The mapping decision belongs to a person who can check that both columns represent the same measured construct, not to a header-matching heuristic. A near-identical column name is a hint, not proof. A differently named column can still be the correct match once its contents are checked against a few known rows.

What alignment can't fix

Aligning two columns under a shared output field solves the naming problem. It doesn't guarantee the two years are comparable in every sense a reader might assume. If a testing-platform change affects scoring methodology, cut scores, or the item pool behind a performance level, the same header, holding the same five ordinal categories, may not represent quite the same measurement from one year to the next. Districts comparing across the recent vendor transition should treat the first post-transition comparison with more scrutiny than a routine year-over-year check, not less.

This is a limitation of the underlying data, not of the alignment process itself. Alignment gets two files speaking the same language. It doesn't certify that what they're saying means the same thing.

Where a tool fits, and where it doesn't

DataVot's "Compare across years" feature performs the mechanical part of this alignment: it lets a school map a column from each uploaded data set to a shared output field, so a district isn't manually re-keying or reformatting files before comparing them. It does not decide which columns represent the same construct, and it does not verify that a testing-platform change hasn't altered what a shared header actually measures. Those remain judgments for the person building the comparison.

A district evaluating any tool for this purpose, DataVot included, should ask the same question either way: does it require an explicit alignment decision, or does it make that decision invisibly on the district's behalf? The second approach is faster to set up and harder to defend later.

Districts sitting on two or more years of NJSLA exports gain more from mapping one pair of years by hand and checking that the mapped columns agree in a handful of sample rows than from trusting any tool's default behavior. That check, not the mapping itself, is what makes the resulting comparison something a district can stand behind in a board presentation.