Humans have developed the capability to teach relevant aspects of new or adapted tasks to a social peer with very few task demonstrations by making use of scaffolding strategies that leverage prior knowledge and importantly prior joint experience to yield a joint understanding and a joint execution of the required steps to solve the task. This process has been discovered and analyzed in parent-infant interaction and constitutes a ``co-construction'' as it allows both, the teacher and the learner, to jointly contribute to the task. We propose to focus research in robot interactive learning on this co-construction process to enable robots to learn from non-expert users in everyday situations. In the following, we will review current proposals for interactive task learning and discuss their main contributions with respect to the entailing interaction. We then discuss our notion of co-construction and summarize research insights from adult-child and human-robot interactions to elucidate its nature in more detail. From this overview we finally derive research desiderata that entail the dimensions architecture, representation, interaction and explainability.

翻译：人类已发展出通过利用支架策略（利用先验知识及重要的先前共同经验）向社交同伴教授新任务或改编任务的相关方面，且仅需极少量任务示范的能力，以达成对解决任务所需步骤的共同理解与共同执行。这一过程已在亲子互动中被发现并分析，构成了一种“共建”，因为它允许教师和学习者共同为任务做出贡献。我们建议将机器人交互学习研究聚焦于这一共建过程，以使机器人能够在日常情境中向非专家用户学习。下文将回顾当前交互式任务学习的代表性方案，并讨论它们在所涉及交互方面的主要贡献。随后我们阐述共建的概念，并总结来自成人与儿童以及人与机器人互动的研究见解，以更详细地阐明其本质。基于这一概述，我们最终得出涵盖架构、表示、交互和可解释性这四个维度的研究需求。