Do Chains-of-Thoughts of Large Language Models Suffer from Hallucinations, Cognitive Biases, or Phobias in Bayesian Reasoning?

Understand

Learning to reason and carefully explain arguments is central to students' cognitive, mathematical, and computational thinking development.

• This is particularly challenging in problems under uncertainty and in Bayesian reasoning.
• With the new generation of large language models (LLMs) capable of reasoning using Chain-of-Thought (CoT), there is an excellent opportunity to learn with them as they explain their reasoning through a dialogue with their artificial internal voice.
• It is an engaging and excellent opportunity to learn Bayesian reasoning.