Nasir Jauwairia, Bruno Barbara, Dillenbourg Pierre
Chair of Human-Centered Artificial Intelligence, University of Augsburg, Augsburg, Germany.
Computer Human Interaction for Learning and Instruction Lab, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Front Robot AI. 2024 Aug 22;11:1385780. doi: 10.3389/frobt.2024.1385780. eCollection 2024.
When designing social robots for educational settings, there is often an emphasis on domain knowledge. This presents challenges: 1) Either robots must autonomously acquire domain knowledge, a currently unsolved problem in HRI, or 2) the designers provide this knowledge implying re-programming the robot for new contexts. Recent research explores alternative, relatively easier to port, knowledge areas like student rapport, engagement, and synchrony though these constructs are typically treated as the ultimate goals, when the final goal should be students' learning. Our aim is to propose a shift in how engagement is considered, aligning it naturally with learning. We introduce the notion of a skilled ignorant peer robot: a robot peer that has little to no domain knowledge but possesses knowledge of student behaviours conducive to learning, i.e., behaviours indicative of productive engagement as extracted from student behavioral profiles. We formally investigate how such a robot's interventions manipulate the children's engagement conducive to learning. Specifically, we evaluate two versions of the proposed robot, namely, Harry and Hermione, in a user study with 136 students where each version differs in terms of the intervention strategy. Harry focuses on which suggestions to intervene with from a pool of communication, exploration, and reflection inducing suggestions, while Hermione also carefully considers when and why to intervene. While the teams interacting with Harry have higher productive engagement correlated to learning, this engagement is not affected by the robot's intervention scheme. In contrast, Hermione's well-timed interventions, deemed more useful, correlate with productive engagement though engagement is not correlated to learning. These results highlight the potential of a social educational robot as a skilled ignorant peer and stress the importance of precisely timing the robot interventions in a learning environment to be able to manipulate moderating variable of interest such as productive engagement.
在为教育环境设计社交机器人时,人们往往强调领域知识。这带来了一些挑战:1)要么机器人必须自主获取领域知识,这在人机交互中仍是一个未解决的问题;要么2)设计者提供这些知识,这意味着要为新情境重新对机器人进行编程。最近的研究探索了一些替代性的、相对更容易移植的知识领域,如与学生的融洽关系、参与度和同步性,尽管这些概念通常被视为最终目标,而最终目标应该是学生的学习。我们的目标是提议改变对参与度的考量方式,使其与学习自然地结合起来。我们引入了一个技术娴熟的无知同伴机器人的概念:一个几乎没有领域知识但拥有有助于学习的学生行为知识的机器人同伴,即从学生行为档案中提取的表明有效参与的行为。我们正式研究了这样一个机器人的干预如何操纵有利于学习的儿童参与度。具体来说,我们在一项有136名学生参与的用户研究中评估了所提议的机器人的两个版本,即哈利和赫敏,每个版本在干预策略上有所不同。哈利专注于从一系列沟通、探索和反思诱导建议中选择哪些建议进行干预,而赫敏还会仔细考虑何时以及为何进行干预。虽然与哈利互动的小组有更高的与学习相关的有效参与度,但这种参与度不受机器人干预方案的影响。相比之下,赫敏适时的干预被认为更有用,它与有效参与度相关,尽管参与度与学习无关。这些结果凸显了社交教育机器人作为技术娴熟的无知同伴的潜力,并强调了在学习环境中精确安排机器人干预时间的重要性,以便能够操纵诸如有效参与度等感兴趣的调节变量。