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This paper investigates the impact of coupling dynamics between human teachers and robot learners on the effectiveness of human-robot teaching interactions. By proposing a new classification scale informed by human learning theories, the authors analyze existing literature to reveal how discrepancies between teachers' mental models and the robot's learning capabilities influence both teaching outcomes and perceptions. The key finding indicates that misalignments in these dynamics can significantly hinder teaching effectiveness, emphasizing the need for better alignment in human-robot interactions.
Misalignments in teacher mental models and robot learning can drastically reduce the effectiveness of human-robot teaching interactions.
Human-robot teaching focuses on enabling nontechnical experts to customize robots according to their needs after deployment. With recent advances in machine learning, human-robot teaching is no longer confined to offline learning where the data gathering step from a human teacher is separated from when the robot learns. Instead, more recent approaches for human-robot teaching focus on coupling human teaching with robot learning. This coupling impacts the structure, timing, and content of the teaching and learning interaction. However, it is currently unclear how such coupling dynamics affect humanrobot teaching effectiveness and human perceptions towards the teaching process. Informed by human learning theories, in this paper we propose a new scale for classifying human-robot teaching interactions according to coupling dynamics present between the human teacher and robot learner. We apply this scale to a subset of the human-robot teaching literature to identify how coupling dynamics and human teacher mental model mismatches with the ground truth robot learning system affect teaching effectiveness and human perceptions towards the teaching process