Back to search

Article

Exploring Large Language Models' Responses to Moral Reasoning Dilemmas

2025-06-17

Abstract excerpt

<title>Abstract</title> <p>This study investigates how various large language models (LLMs) generate responses to moral reasoning dilemmas. It specifically examines LLM-generated responses using the Defining Issues Test (DIT-2) and the Intermediate Concepts Measure (ICM) for Educational Leaders. Using a neo-Kohlbergian approach to moral reasoning, the study evaluates responses from multiple LLM platforms: ChatGPT...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
80a02484-a6b6-5781-aafb-55843df3294f
DOI
10.21203/rs.3.rs-6823916/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Exploring Large Language Models' Responses to Moral Reasoning DilemmasDOI 10.21203/rs.3.rs-6823916/v1
Select a neighboring publication to make it the new centre.