IMBUE: Improving Interpersonal Effectiveness through Simulation and
  Just-in-time Feedback with Human-Language Model Interaction
Inna Wanyin Lin Ashish Sharma Christopher Michael Rytting Adam S. Miner Jina Suh Tim Althoff
Navigating certain communication situations can be challenging due to
individuals' lack of skills and the interference of strong emotions. However,
effective learning opportunities are rarely accessible. In this work, we
conduct a human-centered study that uses language models to simulate bespoke
communication training and provide just-in-time feedback to support the
practice and learning of interpersonal effectiveness skills. We apply the
interpersonal effectiveness framework from Dialectical Behavioral Therapy
(DBT), DEAR MAN, which focuses on both conversational and emotional skills. We
present IMBUE, an interactive training system that provides feedback 25% more
similar to experts' feedback, compared to that generated by GPT-4. IMBUE is the
first to focus on communication skills and emotion management simultaneously,
incorporate experts' domain knowledge in providing feedback, and be grounded in
psychology theory. Through a randomized trial of 86 participants, we find that
IMBUE's simulation-only variant significantly improves participants'
self-efficacy (up to 17%) and reduces negative emotions (up to 25%). With
IMBUE's additional just-in-time feedback, participants demonstrate 17%
improvement in skill mastery, along with greater enhancements in self-efficacy
(27% more) and reduction of negative emotions (16% more) compared to
simulation-only. The improvement in skill mastery is the only measure that is
transferred to new and more difficult situations; situation specific training
is necessary for improving self-efficacy and emotion reduction.