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This research investigates the dynamics of coupling between human teachers and robot learners, proposing a new scale to classify interactions based on how real-time data sharing influences teaching effectiveness. By analyzing mismatches between human mental models and actual robot learning systems, the study aims to optimize human-robot collaboration for non-expert users without relying on hype or marketing fluff.
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Bridging Teacher Expectations and Robot Learning via Coupling Dynamics

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2608.23994v1 Announce Type: new Abstract: 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

Abstract: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

Robotics (cs.RO); Human-Computer Interaction (cs.HC)

arXiv:2608.23994 [cs.RO]

(or arXiv:2608.23994v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2608.23994 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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