December 2025 through February 2026 was the 2nd warmest winter on record for the Contiguous U.S. according to Prism climate data. The widespread record to near record warmth in the west easily outweighed the cool temps in the east. 🔥🔥🔥
From a century ago!
The March Calendar of Problems is here! Enjoy some #ProblemSolving yourself or with students. Let us know your thoughts & working-out here or on post.
#MTBoS #iTeachMath #T3Learns #RecreationalMath #MathSky #MathsToday
karendcampe.wordpress.com/2026/03/01/m...
The 7yo looking out the window as we are driving.
7yo: "The moon is moving so fast!"
Me: "Actually, parallax is..."
7yo: "Ooooh you don't think 2300 miles per hour is fast?!"
They just haven't asked it to play Tic Tac Toe yet.
Book cover of "Weapons of Math Destruction" by Cathy O'Neil.
Weapons of Math Destruction, by Cathy O’Neil Chapter 3 - Arms Race, Going to College 1. What are the pros and cons of college rankings, and do they ultimately offer a net benefit? 2. What is measured and what is not? • What variables did U.S. News include in its college ranking formula? • What aspects of educational quality were excluded or difficult to measure? • What are the consequences of building a model that accounts only for what can be easily mea- sured? 3. O’Neil writes about systems that can be gamed. Who benefits from these systems and who is harmed? 4. The major theme from first semester was feedback loops. • What feedback loops are created by college rankings. Model these loops with a system diagram. • What consequences of rankings are due specifically to feedback loops? • Are the looping systems of college rankings chaotic, or do they converge toward cycles or fixed points? 5. The output of algorithms is often presented as neutral. There are numerous tropes about how “the numbers don’t lie”, “the data speaks for itself”, and ”you can’t argue with the math”. However, O’Neil describes how those creating the models have great power. To what extent is a model a representation of the values of the modeler? Or, what choices is the modeler in a position to make that influence the model? 6. You are more than your data, yet your grades, applications, resume, etc. are variables in algorithms. What aspects of being human are systematically excluded from data-driven systems?
In #MathsToday we read Chapter 3: Arms Race - Going to College, from Weapons of Math Destruction by Cathy O'Neil.
Students annotated, discussed in groups, and will share some reflections in writing.
Gaslighting only exists if gaslighting doesn't exist
Oh this has always been an issue to be aware of in teaching (particularly in physics).
Like, avoid saying "happy electron" or talking about what charged particles "want" to do.
Honestly, this is the kind of organic messaging @prisonculture.bsky.social was talking about earlier. We don't have to wait for the media to take up these issues on their own. Make it all about these issues.
Of course I understand there can be a scenario where your students benefit from experience with a particular technology.
Duty of care for students includes opposing systems of surveillance and oppression. It includes opposing technologies that do harm at scale.
Rage against the machine.
I can understand this! Depending on the context.
Big picture is that AI adoption is largely uncritical and many AI products are doing more harm than good. "No AI" seems like a very reasonable position to hold. And there are *so many* ethical pitfalls that we are repeatedly falling into.
Ah yes, but that gets back to accepting the inevitability.
I want my students to be prepared! But what that preparation looks like doesn't include AI unless there is a good reason for it.
So I don't think teachers are sticking their heads in the sand with AI, I think that there aren't really good AI products for students and companies are co-opting teachers into unpaid labor to try and find uses for their non-products.
The list of cons is severely long, and I don't hear a lot of pros. I spend a lot of time attending conferences and listening to speakers talk about how AI is revolutionizing education, but they never actually get to describing how that is. But they want me to "experiment, explore" and find uses.
Companies have tunneled AI in through established platforms. It popped up in Google Classroom, docs, mail, etc. My PDF reader wants to give me an AI summary instead of letting me read the PDF I opened. My recommendation platform wants to generate letters of rec for me, etc.
I am open-minded about applications for "AI", but education speakers in K12 are unquestionably uncritical about the adoption of AI. Many even promote illegal uses, in violation of laws regarding privacy and surveillance. The applications they recommend are just bad.
It sounds like the opposite, that *any* tech use should be justified and non-use shouldn't require justification given the lack of justification in favor.
Of course "meaningful" depends very much on the course, the students, and more.
I had one of these beautiful shapes hanging in my old classroom for years!
Tangent: this picture was the data from a pendulum lab. I ask students to:
1. Measure the period of a pendulum
2. Measure 10 swings then divide by 10
3. Measure 10 swings again, but this time do a good job
Never fails.
This is a tough one! But to help narrow it down, "artificial teaching scheme" is referring to computer based ed tech. The author argues that it always fails and is destined to always fail.
So it could be the 60s or last week!!
CAI = Computer-Assisted Instruction
PI = Programmed Instruction
because the Skinnerians do not.) There are two fundamental and intractable troubles with CAI and PI. Every conception of pedagogy is based on a concept of knowledge, and CAI and PI are based on a falsified concept: that knowledge is the ability to respond in the expected way. For reasons I dis- cussed earlier, the use of this idea produces cognitive knowledge-at least for the moment-at the price of psychic intelligence. When advocates of CAI or PI are exuberant, they claim that their methods supersede other teaching styles. When challenged, they sometimes retreat to the position that their methods replace various kinds of drill that do not deserve the attention of a human teacher; but these retreats are instances of the Law of
the Conservation of Bologna under Thin Slicing. The trouble is that CAI and PI are based on naive misconceptions of the psychology of learning and retention. Every artificial teaching scheme is predicated on the idea that learning processes work best when they are carefully designed and controlled. This might be true if learning processes were understood, but they are not. The notion that we understand how mental capacities develop well enough to dare to control their development is not just an exaggeration; it is a pack of nonsense, and we rely on it at our students' peril. It is equally naive to suppose that people understand and remember the things that are explained or told to them clearly. In practice, people under-
But some very prevalent teaching schemes bear strong resemblances to CAI and PI and have much the same vices. One of their distinguishing features is that they neither require nor produce functional literacy. The literate may skim a paragraph or a page to get its general drift. The question is whether they expect to get more than the general drift. When they do not understand exactly what the paragraph says, do they reexamine it until it comes into sharp focus? If so, they have half of functional literacy (and evidently this half is largely a trait of temperament rather than a purely cognitive skill); the other half is the ability to write exactly what one means. Any education that does not include functional literacy is deficient. The trouble is that once formal education is over, we have nobody to feed us knowledge out of spoons, and so we must read with care to add to our knowledge or even to preserve it. Moreover, inarticulate knowledge is adequate only for people who work in isolation (if, indeed, for them); and in
A text that is great for #GuessTheYear!
"The notion that we understand how mental capacities develop well enough to dare to control their development is not just an exaggeration; it is a pack of nonsense, and we rely on it at our students' peril."
#mtbos #ITeachMath #NCTM
Normalize laughing derisively in men's faces when they deserve it.
Then your friend Chelsea, also from twenty-eight thousand years ago, notices another connection: sometimes she can combine two arrangements from Pattern 2 to get a bigger arrangement also in Pattern 2, but it doesn’t always work. She finds this one: 9 with 16 makes 25
Pattern 3 1 rock, 8 rocks, 27 rocks Chelsea, who is rightly proud of her discovery about combinations in Pattern 2, searches for similar combinations in Pattern 3. She wants to find two piles in Pattern 3 that can combine together to get another pile in Pattern 3, but this last format is challenging and it will be quite a wiles before someone figures it out.
Really stretching hard to make the math jokes work in this chapter on Number...
My HS science teachers were absolute bosses.
Mr. Hall, Dr. Hall, Dr. Leverault, Mr. Bennett, and Dr. Estabrooks.
Thanks to a semester system, I was able to take 10 years of science in HS. Hall and Bennett invented new classes for me: An electrical engineering lab, and an advanced chem lab.
Teachers are great.
Had an awesome PD day today. Every teacher there was simply a generous kind-hearted person dedicating a career to encouraging and supporting young people in exploring their interests, doing their best, and leading happy lives.
In today’s #404DeepDive, @jasonkoebler.bsky.social gets into Ring’s new feature Search Party which was advertised at the Super Bowl which essentially turns the entire neighborhood into a security dragnet.
Read more: www.404media.co/with-ring-am...
Oh no, that's very online with my categories of bad! Happy to add any recommended links. What isn't really on here is much research or books. And there are great instances of both.
It's just because my presentations have a flow like:
"Ok, here's example #103 of someone overestimating the capability of mathematical modeling, using an inappropriate model poorly, lying about the results, losing money, and deploying tech that causes harm. Ok, here's example #104 of..."
