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Making Sense of Your Projected Data

What a Projection Is

Between the preliminary Spring MAAP data drop (usually June) and the official results (usually late August), TKG Analytics shows you projected accountability grades. A projection is TKG Analytics's best estimate of where your district, schools, and teachers are heading, built from the data available so far. It is not the official grade.

That "so far" is something you can shape. Through the summer, if you want a more complete picture, you can add any missing SLAIF scores and update your readiness standards, and each one brings the projection closer to your district's reality. A projection that shifts as the data fills in is not a mistake, it is the estimate getting sharper.

For how the underlying numbers are built, see How Impacts Are Created.

A Missing SLAIF Score Can Move the Needle

The biggest lever on a projection is usually the completeness of your scores, and the most common gap is a missing SLAIF score. Until a student's SLAIF score is added, they are not yet reflected in your projection, so an estimate built on partial data can still move as those gaps close. The more of them you close, the more the projection reflects your actual students, and the more you can trust where it lands.

You can fill those gaps yourself. On the Adding SLAIF Scores page, district admins enter official state results for students who are missing them. Once you have added all of the missing scores you have on hand, open a Helpdesk Ticket to let us know, and the TKG Analytics team re-runs your data so the projection reflects the complete set.

Add every missing score you can from your official state reports before you open the ticket, so we re-run against your full roster in one pass rather than piecemeal.

Adjusting Readiness Standards

Your readiness standards (graduation, acceleration, assessment, and achievement rate targets) feed directly into how impacts are scored. If those targets do not yet reflect your district's real expectations, the projection is measuring you against the wrong bar.

District admins can review and update the current year's targets on the Readiness Standards page, and changes are reflected in your impacts right away. It is worth confirming these early in the window so everything else you read is measured against the right standard.

Students Who Meet FAY but Tested Elsewhere

A student can be Full Academic Year (FAY) in your district, enrolled long enough to count, while they tested in another Mississippi public district. This one is outside your control: the score sits with the other district, so it is not a gap you can simply fill.

It is still worth knowing about, because a student like this can move your LPS, growth, and proficiency projections. When a projection looks different from what you expect, a case like this can be part of the reason, even when the fix is not in your hands.

When a Projected Grade Is Sitting on the Fence

Some projected grades sit comfortably in the middle of a letter. Others sit right on the fence, a point or two from the next grade up or down. A grade on the fence is the most sensitive to data: a few added scores, a corrected record, or an updated readiness target can be enough to tip it either way.

If a projection is borderline, treat it as a signal to make sure the data behind it is complete before you read too much into the letter. This is where adding your missing SLAIF scores and confirming your readiness targets matters most, though depending on what those turn out to be, a fence-sitting grade can settle either up or down.

The Big Picture

Your projection reflects the data you have shared so far, and it becomes more dependable as that picture fills in. TKG Analytics always gives you the most accurate estimate it can from what has been uploaded, and as your scores, rosters, and readiness targets come together over the summer, the grade you see settles and gets easier to trust.

If a projection is not quite where you expected, start with the data behind it. Sometimes there are scores or readiness targets still to add, and sometimes what is already there needs correcting. Getting that data complete and accurate is what lets you trust the projection, whatever it ends up showing.

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Questions about a projection or the data behind it?