Adaptive Empathy Learning Support in Peer Review Scenarios


Advances in Natural Language Processing offer techniques to detect the empathy level in texts. To test if individual feedback on certain students’ empathy level in their peer review writing process will help them to write more empathic reviews, we developed ELEA, an adaptive writing support system that provides students with feedback on the cognitive and emotional empathy structures. We compared ELEA to a proven empathy support tool in a peer review setting with 119 students. We found students using ELEA wrote more empathic peer reviews with a higher level of emotional empathy compared to the control group. The high perceived skill learning, the technology acceptance, and the level of enjoyment provide promising results to use such an approach as a feedback application in traditional learning settings. Our results indicate that learning applications based on NLP are able to foster empathic writing skills of students in peer review scenarios.

Thiemo Wambsganss
University of St. Gallen, Sankt Gallen, Switzerland
Matthias Soellner
University of Kassel, Kassel, Germany
Kenneth R. Koedinger
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Jan Marco Leimeister
University of St. Gallen, St. Gallen, Switzerland


会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (

セッション: Interactive Learning Support Systems

4 件の発表
2022-05-02 23:15:00
2022-05-03 00:30:00