# Chatting with an LLM-based AI elicits affective and cognitive processes in education for sustainable development

## TL;DR

Chatting with AI that has different personalities can influence emotions and learning in sustainability education.

## Contribution

This study explores how AI personality traits affect emotional and cognitive learning outcomes in education for sustainable development.

## Key findings

- Chatting with an empathic AI elicits stronger emotions like empathy and distress compared to a compassionate AI or reading text.
- All groups showed knowledge gains, but there were no differences in cognitive outcomes between the groups.
- The emotional tone of AI chatbots may influence affective processes in learning.

## Abstract

Personalized interactions have been discussed as beneficial for learning for decades. Now, with the rise of generative artificial intelligence (GenAI), personalized artificial human-like conversations may impact the quality of learning. Manipulating system prompts to design personalities has the potential to enhance the quality of conversation with Large Language Model (LLM)-based AI. However, it is still uncertain exactly to what extent the emotional tone of a generative AI chatbot is relevant for learning. Hence, the current study evaluates the impact of a chat-based conversation with an LLM-based AI on relevant affective (empathy, compassion, distress) and cognitive (perspective-taking, reflection, knowledge) processes in education for sustainable development. Here, the focus is on both the general impact and the particular impact of two different system prompts that assign the AI’s specific personality traits (empathic vs. compassionate). Comparing these two groups and one control group reading a text (N = 122) indicates that chatting with an empathic AI can elicit stronger emotions (e.g., empathy, compassion, distress) compared to chatting with a compassionate AI, and compared to the control. Although all groups gained knowledge, we found no group differences. Further research is necessary to ensure reliable and contextually appropriate conversations in the context of education.

The online version contains supplementary material available at 10.1038/s41598-026-39317-6.