TY - CHAP A1 - Rudolph, Eric A1 - Seer, Hanna A1 - Mothes, Carina A1 - Albrecht, Jens T1 - Automated feedback generation in an intelligent tutoring system for counselor education T2 - Annals of Computer Science and Information Systems N2 - This paper investigates the implementation of AI- driven feedback in an intelligent tutoring system (ITS) developed for training of counselors. By using LLMs, the study explores the automatic generation of feedback for communication-intensive tasks such as online counseling. The evaluation compares dif- ferent feedback methods, including the sandwich, WWW and STATE methods, and assesses their emotional and objective impact. The results show that AI-generated feedback fulfills objective criteria better than emotional ones. Fine-tuning an open source LLM can improve both the emotional and objective quality of feedback. Furthermore, the study examines the accep- tance of AI feedback among aspiring counselors, highlighting the influence of familiarity with AI on acceptance levels. Ethical con- siderations, including bias and hallucination, are addressed, with recommendations for risk mitigation through multi-feedback options and expert supervision. This research contributes to the understanding of the role of AI in improving digital counseling practices and highlights the need for continuous evaluation and ethical considerations. KW - Intelligent Tutoring System KW - Automated Feedback Generation KW - Artificial Intelligence KW - Counselling Y1 - 2024 U6 - https://doi.org/10.15439/2024F1649 SN - 2300-5963 VL - 39 SP - 501 EP - 512 PB - IEEE ER -