Recently, computer scientists have developed large language models (LLMs) by
training prediction models with large-scale language corpora and human
reinforcements. The LLMs have become one promising way to implement artificial
intelligence with accuracy in various fields. Interestingly, recent LLMs
possess emergent functional features that emulate sophisticated human
cognition, especially in-context learning and the chain of thought, which were
unavailable in previous prediction models. In this paper, I will examine how
LLMs might contribute to moral education and development research. To achieve
this goal, I will review the most recently published conference papers and
ArXiv preprints to overview the novel functional features implemented in LLMs.
I also intend to conduct brief experiments with ChatGPT to investigate how LLMs
behave while addressing ethical dilemmas and external feedback. The results
suggest that LLMs might be capable of solving dilemmas based on reasoning and
revising their reasoning process with external input. I will discuss the
potential implications of LLMs on research on moral education and development
with the results.

本文回顾了最近发表的关于 LLMs 在道德教育和发展研究中的问题，涵盖了 LLMs 的新功能特性，如情境学习和思维链以及在解决伦理困境时的表现及其潜在意义和影响。