1. Supporting Cognitive and Emotional Empathic Writing of Students
- Author
-
Christina Niklaus, Matthias Söllner, Jan Marco Leimeister, Thiemo Wambsganss, and Siegfried Handschuh
- Subjects
FOS: Computer and information sciences ,Scheme (programming language) ,Information management ,Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer science ,media_common.quotation_subject ,Computer Science - Human-Computer Interaction ,computer science ,Empathy ,Business model ,Human-Computer Interaction (cs.HC) ,Machine Learning (cs.LG) ,Annotation ,Peer learning ,computer.programming_language ,media_common ,education ,Computer Science - Computation and Language ,information management ,Cognition ,Artificial Intelligence (cs.AI) ,Computation and Language (cs.CL) ,computer ,Cognitive psychology - Abstract
We present an annotation approach to capturing emotional and cognitive empathy in student-written peer reviews on business models in German. We propose an annotation scheme that allows us to model emotional and cognitive empathy scores based on three types of review components. Also, we conducted an annotation study with three annotators based on 92 student essays to evaluate our annotation scheme. The obtained inter-rater agreement of {\alpha}=0.79 for the components and the multi-{\pi}=0.41 for the empathy scores indicate that the proposed annotation scheme successfully guides annotators to a substantial to moderate agreement. Moreover, we trained predictive models to detect the annotated empathy structures and embedded them in an adaptive writing support system for students to receive individual empathy feedback independent of an instructor, time, and location. We evaluated our tool in a peer learning exercise with 58 students and found promising results for perceived empathy skill learning, perceived feedback accuracy, and intention to use. Finally, we present our freely available corpus of 500 empathy-annotated, student-written peer reviews on business models and our annotation guidelines to encourage future research on the design and development of empathy support systems., Comment: to be published in The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)
- Published
- 2021