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1 2024

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Automated feedback generation in an intelligent tutoring system for counselor education

Rudolph Eric, Seer Hanna, Mothes Carina, Albrecht Jens

Annals of Computer Science and Information Systems

2024

Vol. 39

501--512

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 different 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 acceptance of AI feedback among aspiring counselors, highlighting the influence of familiarity with AI on acceptance levels. Ethical considerations, 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.