I'm not sure what features people consider important, as I've never used Spotify or other common podcast apps, but I've had a good experience getting podcasts through Patreon and then adding them to AntennaPod through their rss feed.
"Dumbing down" is an imprecise and inaccurate description of the most recent changes to the SAT.
The Collegeboard did indeed adjust the test to better appeal to students, but this was primarily done by shortening the length of the exam from ~ 3 hours to ~2 hours. To compensate for this, the test was updated to an adaptive format to present students with more questions of appropriate difficulty levels based on their performance.
The other main change, which the article highlights, was to shorten the reading passages. Yes, there are skills no longer being tested because of this change, but it's also allowed for a broader array of passages to be included. The new version of the test introduced poetry and novel question types involving logical reasoning and use of data. Which of these skills are more important for success in college and future careers is a worthwhile question to ask, but not one with an obvious answer.
This looks fantastic! I work in test preparation myself (though not for the LSAT) and this ticks all the boxes for the best approaches. I also really appreciate it being direct and opinionated without the obnoxious tendency of a lot of guides to denigrate alternatives.
Yes, you do need to press white keys further back sometimes. Imagine trying to play on black keys with your thumb and pinky finger while playing a white key with your middle finger. You won't be pressing all the way at the back, but your finger will have to press between the black keys.
I'll have to go through this with my family; we have a number of terms we use that we're never sure if they're Canadian, non-regional uncommon words, or just things our family say.
My grandpa called toonies "bearbucks", which isn't listed, but is in one of the quotes on the toonie entry. No listing for "reef" as in yanking on something, though I don't know if that's a Canadianism or not.
I've been increasingly concerned by packaged CS curricula that includes an overabundance of guidance and tooling. I've seen too many students complete a course (successfully!) and leave without any ability to start building projects of their own.
I don't want to end up as a curmudgeon griping about how "back in my day we didn't have an IDE!", as I'm in favor of giving students real world tools early, but I'm worried that we're filtering out some level of independence by sandboxing their learning so strictly.
I work teaching CS to a variety of age levels (admittedly mostly teenagers and older), and one thing I would recommend is broadening your consideration about what CS fundamentals might include. Picking up language syntax or new tools is easy enough at whatever age, but problem solving and planning skills are very tough to rebuild as they grow into adolescence.
One of my personal favorite resources is CS Unplugged. [1] It sidesteps any particular language or toolset in favor of pen-and-paper interaction.
I plan to begin and I grew up before the nineties. I probably know less than your kids. Paper is my native go-to. Thank you for this! Advice please: Can I get started using my now-antique Win 98 and Win7 hardware, while using phone or Win11 for online lookups?
It looks to me like there is consensus for Minecraft and Godot. I expect Minecraft to work on old hardware. How about Godot? Can it be used offline?
Going further, it seems like Language Aptitude was primarily significant in explaining variance in learning rate, measured by how many Codecademy lessons they completed in the allotted time, but wasn't explanatory for learning outcomes based on writing code or answering multiple-choice questions.
Seeing as Codecademy lessons are written in English, I would think this may just be a result of participants with higher Language Aptitude being faster readers.
I do think that language skills are undervalued for programming, if only for their impact on your ability to read and write documentations or specifications, but I'm not sure this study is demonstrating that link in a meaningful way.
Useful feedback - thanks. The content you're seeing may be misleading for what the platform really does. Let me explain.
The "hot topic" thing is just chatgpt creating conversation starters. Sometimes, its' leaning left, sometimes right, sometimes it's not political. We're tuning it up (mainly to just be more engaging).
The post you saw about Elon Musk ... Everyone is talking about whatever they feel like talking about. If Musk isn't your cup of tea, mute this anonymous person and you don't see each other for a week. It's only a week because maybe one of you was having a bad day. But with repeated muting, they're completely gone. Also nudges the system to group you with people you're going to like better. After enough respects and mutes, you should see the people you enjoy.
The bigger point is what happens once you bring your friends. You guys can talk about anything without getting angry at each other. If they irritate, mute 'em. If you enjoy the conversation, respect them. Enough mutual respect and you can see real names.
I work with students learning to code, some of whom use AI in various ways. I can definitely see AI becoming a valuable tool for them in the future, but most students are currently ill-equipped to take advantage of it.
The most common error I observe from students is not providing sufficient information to get useful results. They'll omit what language or libraries they're intending to use, or restrictions on the set of language features they are or are not familiar with. Because of this, they'll get confident, often correct, responses, which are entirely unhelpful for the work they're doing.
The other issue they'll run into is over- or underestimating the capabilities of tools like ChatGPT. The first time they run into a problem which it isn't immediately able to solve they often give up on using AI as a tool entirely.
I do think AI has value for learners, primarily in an "explainer" role. Allowing students to take a piece of code and ask "what does this do" to get a plain English explanation is extremely powerful. It also can act as a substitute for documentation, as new learners are often disinclined to parse through official documentation, which is rarely beginner-friendly.
The mechanisms in improving LLM code output do not correlate to better understanding of systems or even LLMs for that matter. For language I think you're more correct in your view for sure.
