The CDE recently released the first batch of growth scores for schools and districts across California. Growth scores measure the performance of schools and districts by calculating by how much their students’ SBAC scores differ from what was expected given their prior SBAC scores. By design, the average growth score across all students should be zero (or very close to it). Growth scores are given in the same units as SBAC scores. A growth score of -5 doesn’t mean that students scored five points worse than they did the year before. It means that their SBAC score grew by 5 points less than expected. Perhaps they scored 2500 last year and were expected to score 2523 this year but only scored 2518.

A previous post went into more detail about how growth scores are calculated and what the limitations are of the CDE’s chosen algorithm. The key points to remember come from these two charts, which I’ve lifted from that previous post:

Observe that students who stay in the 70th percentile gain about 150 SBAC points between 3rd grade and 8th grade while students who stay in the 20th percentile gain only about 130. In general, students in higher percentiles tend to increase their SBAC scores by more than students in lower percentiles. The gap between them gets wider over time.

Observe here that the pattern is even more extreme for Math: students in higher percentiles gain a lot more points than students in lower percentiles.

The growth model is based on a linear regression whose only independent variables are a student’s ELA and Math scores in the previous year. In particular, the student’s grade is not a variable in the model. A student who scores 2500 in 3rd grade will be predicted to grow as much as a student who scores 2500 in 7th grade even though the 3rd grade student will be in a much higher percentile. The charts showed that students in higher percentiles gained more SBAC points than students in lower percentiles. Since they both receive the same prediction, the higher percentile student will tend to exceed that prediction and thus get a growth score greater than zero while the lower percentile student will tend to get a growth score less than zero.

A district whose students start and finish the year in the 25th percentile has done just as good a job, no better and no worse, than a district whose students start and finish the year in the 75th percentile. But, due to the way the growth scores are calculated, a district whose students stay in the 25th percentile will tend to have a lower growth score than a district whose students stay in the 75th percentile.

For this reason, when we look at growth scores, we are always going to look at them in the context of the prior year’s SBAC scores, specifically the average Distance from Standard1 (DFS) of the students. This will enable us to see if a district’s performance is truly outstanding. Note that the Distance from Standard and the growth score are in the same units.

ELA Growth Scores

The chart below shows the ELA growth scores for the 114 districts that had at least 4,000 students with growth scores.

The diagonal line is the best-fit line based on a linear regression against each district’s average distance from standard in 2024. The R-squared is 0.36 indicating that, while there’s clearly a relationship, there’s a lot of scope for districts with similar prior achievement scores to achieve very different growth scores. Hayward and West Contra Costa both had weak SBAC scores in 2024 (both were around 60 points below standard) but Hayward’s growth score of 0 was a lot better than West Contra Costa’s –11. Los Angeles and Compton both had 2024 SBAC scores 25-28 points below standard but Compton’s growth score of 12 was much better than Los Angeles’s still-creditable +1. In fact, Compton’s growth score was better than any other district in the sample. San Francisco, meanwhile, had a growth score of -1, which is meh. It’s a bit below what would be expected but not egregiously so.

Math Growth Scores

The analogous chart for Math growth scores is different in two ways.

• the relationship between the prior year SBAC scores and the current year growth score is much stronger (R-squared = 0.81)

• the range of growth score values is significantly wider. Growth score values of +20 or higher are found.

Both are a consequence of the phenomenon we saw in the first charts, namely that the gap between the average score gain in higher and lower percentiles is much greater for Math than ELA.

Nevertheless, Compton still excels. Its growth score of +13 is less than that of districts like Cupertino and Irvine and San Ramon Valley (all of which are at +20 or higher) but, given that its students started the year 39 points below standard, it surpassed expectations by more than any of these other districts.

So, which is the best performing district?

There are nearly 700 districts with growth scores and only the 114 largest are shown on the charts above. Those 114 districts represent about 63% of all students but there are districts too small to show on the charts which had even higher growth scores than Compton in both ELA and Math. The largest of these districts was Orinda, in Contra Costa, which had growth scores of 13 (ELA) and 16 (Math). But Orinda had only 1,350 students, far less than Compton’s 5,900, and its prior achievement scores were 88 points above standard (ELA) and 72 above standard (Math) so its high growth scores are not as impressive. The highest growth scores of all belong to Scotia Union Elementary in Humboldt County (24 in ELA; 42 in Math) but Scotia Union had only 104 students with growth scores, fewer than many schools. Similarly, the absolute worst growth scores belong to Geyserville Unified in Sonoma (-17 in ELA; -44 in Math) but Geyserville had only 73 students. The worst performing district of any size was Barstow Unified in San Bernardino, whose 1,900 students had growth scores of -32 in ELA and -24 in Math.

Impressive as its scores are, it is far too early to blithely declare that Compton is the best school district in California. During the development of the growth scores model, the CDE published what the test scores would have been using the last pre-pandemic SBAC data. At that time, Compton’s growth scores were the equivalent of -1 in ELA and +3 in Math. Has Compton improved significantly in the intervening five years or are its high scores just a statistical artifact?

SFUSD’s preferred benchmark has long been Long Beach Unified. Years ago, when I first started analyzing student achievement data, I identified Clovis Unified in Fresno and ABC Unified in Los Angeles as districts that seemed to do particularly well after adjusting for their demographics. How are these three rated by the growth scores method? Long Beach scored +2 in ELA and -3 in Math; ABC scored +5 in ELA and +3 in Math; Clovis scored +9 in ELA and +4 in Math. Good scores, but not as good as Compton. In the test data from the pre-pandemic era, those districts were all stronger than Compton. Long Beach was +5 and +2, ABC was +6 and +6, and Clovis was +9 and +3. Even San Francisco was +5 and +2.

It will take multiple years of data to know whether Compton’s high scores are an indicator of true excellence or just a blip.

Physicist Sean Carroll leads off this video with this line:

I like to say that Einstein is, if anything, underrated as a physicist, which is hard to imagine given how highly he is rated.

And then leads us through a history of modern physics and quantum mechanics that, Einstein and Newton aside, is much more collaborative than you often hear about.

This idea that there are many people contributing and many different parts of the pieces need to put together is actually much more characteristic of how physics is usually done than the single person inventing everything all by themselves.

Tags: Albert Einstein · physics · science · Sean Carroll · video

I keep thinking about this very good 11-minute Not Just Bikes video about traffic calming. In it, a simple argument is made: the posted speed limit of any given street or road doesn’t really matter. What matters is how the street feels. Generously wide and separated lanes, sparse traffic lights, and the road being straight past the horizon will make you unconsciously speed up. Reducing the posted speed limit or adding flashing YOUR SPEED signs won’t help:

The truth is that many drivers will not slow down because of signs or speed limits. They’ll slow down either because they don’t feel safe, or because they’re afraid of damaging their car.

The only answer is redesigning the street for the desired speed limit – narrowing the lanes or joining them, creating choke points and speed bumps, adding posts and planting trees close to the road, and even adding visual cues like “dragon’s teeth.”

One of the great thing about driving in the Netherlands is that it’s rarely necessary to look at the speed limit. The road design takes care of that for you.

There is an app I use a lot called Forklift, a suped up Finder, with one of its functions being syncing files to a remote server.

In its version 3, the syncing window looked like this:

This is a pretty straightforward and dependable function – and I’ve depended on it for years.

I recently updated to version 4 to check it out, particularly since it promised faster syncing. But I was thrown aback by how it randomly deteriorated:

It’s not that there seem to be some UI challenges: the new icons make it harder to understand hierarchy, and one of the switches starts with “Don’t” in contravence of rules of avoiding double negatives.

No, the worst part is this:

This is a new temporary state that meant to help me understand the details of what’s changing.

On the surface, it’s a thoughtful thing. But it’s done in the worst possible way for this kind of a power-user interface: It’s very slow to invoke and slow to cancel. I often activate it by accident – it makes large swaths of UI a minefield where you can no longer rest your cursor safely. It also changes the hierarchy of the output in a way that’s confusing – and it even animates the text wrapping in a distracting way. Then, if you press Esc instinctively to get rid of whatever happens, the window closes altogether.

It’s a “delightful,” luscious transition that is completely out of place. I think this is how many people misunderstand craft – that it’s only about “high polish” without any thought underneath. Here, the effort was spent on executing something that couldn’t be saved this way and needed a more serious rethink. It seems like its creators forgot who’s using the app and for what, and embarked on accidental UI calming.

There are other challenges along the same lines, both downgrades from version 3:

• when the app analyzes the differences, I can no longer press the Sync button and walk away
• even when the button becomes active, I can no longer press Enter to activate it – I have to use the mouse

In version 3, I could invoke Sync, immediately press Enter, and get on my merry way, with syncing continuing in the background. It was exactly what I wanted. Version 4 slows me down by requiring me to pay constant attention to the interface: it matters where I rest my mouse, it matters when I click the button, it matters what input device I use to commit.

It’s okay to think of friction and sometimes transitions are indeed very helpful for UI calming to avoid drastic movements or accidental activations. But here, this isn’t great at all; the creators of Forklift promised me faster syncing and achieved the opposite.

A Meta employee who works on AI safety let an AI agent named OpenClaw loose on her inbox and it deleted all her email. (This tracks; companies like Meta actually don’t care about AI safety and hire accordingly.)

Just over half of U.S. teens say they've used chatbots for help with schoolwork, and 12% say they’ve gotten emotional support from these tools. Teens tend to view AI's future impact on their lives more positively than negatively.

The post How Teens Use and View AI appeared first on Pew Research Center.