this post was submitted on 04 Sep 2024
908 points (98.2% liked)

Technology

59673 readers
3207 users here now

This is a most excellent place for technology news and articles.


Our Rules


  1. Follow the lemmy.world rules.
  2. Only tech related content.
  3. Be excellent to each another!
  4. Mod approved content bots can post up to 10 articles per day.
  5. Threads asking for personal tech support may be deleted.
  6. Politics threads may be removed.
  7. No memes allowed as posts, OK to post as comments.
  8. Only approved bots from the list below, to ask if your bot can be added please contact us.
  9. Check for duplicates before posting, duplicates may be removed

Approved Bots


founded 1 year ago
MODERATORS
 

Does AI actually help students learn? A recent experiment in a high school provides a cautionary tale. 

Researchers at the University of Pennsylvania found that Turkish high school students who had access to ChatGPT while doing practice math problems did worse on a math test compared with students who didn’t have access to ChatGPT. Those with ChatGPT solved 48 percent more of the practice problems correctly, but they ultimately scored 17 percent worse on a test of the topic that the students were learning.

A third group of students had access to a revised version of ChatGPT that functioned more like a tutor. This chatbot was programmed to provide hints without directly divulging the answer. The students who used it did spectacularly better on the practice problems, solving 127 percent more of them correctly compared with students who did their practice work without any high-tech aids. But on a test afterwards, these AI-tutored students did no better. Students who just did their practice problems the old fashioned way — on their own — matched their test scores.

you are viewing a single comment's thread
view the rest of the comments
[–] Buddahriffic@lemmy.world 0 points 2 months ago

It all depends on how and what you ask it, plus an element of randomness. Remember that it's essentially a massive text predictor. The same question asked in different ways can lead it into predicting text based on different conversations it trained on. There's a ton of people talking about python, some know it well, others not as well. And the LLM can end up giving some kind of hybrid of multiple other answers.

It doesn't understand anything, it's just built a massive network of correlations such that if you type "Python", it will "want" to "talk" about scripting or snakes (just tried it, it preferred the scripting language, even when I said "snake", it asked me if I wanted help implementing the snake game in Python 😂).

So it is very possible for it to give accurate responses sometimes and wildly different responses in other times. Like with the African countries that start with "K" question, I've seen reasonable responses and meme ones. It's even said there are none while also acknowledging Kenya in the same response.