Towards an Agile Approach to Adapting Dynamic Collaboration Support to Student Needs
Towards an Agile Approach to Adapting Dynamic Collaboration Support to Student Needs
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DOI：
10.1007/s40593-013-0012-6
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发表时间：
2014-01-01
影响因子：
4.9
通讯作者：
Rose, Carolyn Penstein
中科院分区：
文献类型：
--
作者：
Adamson, David;Dyke, Gregory;Rose, Carolyn Penstein
本文通过一种称为学术生产性谈话(APT)的方法，研究了使用会话代理来搭建在线协作学习讨论的方法。与过去关于协作学习的动态支持的工作不同，在协作学习的动态支持方面，代理被用来通过引导学生通过定向推理来提高概念深度(Kumar&Ros，IEEE学习技术会刊，4(1)，2011)，与之相反，这种基于APT的方法使用通用提示，鼓励学生阐明和阐述他们自己的推理路线，并挑战和扩展他们队友的推理。这篇论文综合了内容领域(生物、化学、工程设计)、年级水平(高中、本科)和促进策略的一系列研究结果。基于APT的策略与简单地提供积极反馈是不同的，当学生自己在他们彼此之间的互动中使用APT促进动作时，我们称之为APT参与的积极反馈。结果表明，基于APT的协作学习支持能显著提高学习效率，但具体的APT促进策略的效果因情境而异。看来，每种策略的有效性取决于材料的难度(就是新概念材料还是复习材料而言)，以及学习者的技能水平(城市公立高中与有选择的私立大学)。相比之下，对APT参与度的反馈并不会对学习产生积极影响。除了基于学习收益的分析之外，还提出了一种自动会话分析技术，该技术可以有效地预测哪些策略在特定上下文中成功运行。讨论了设计更灵活的协作学习动态支持形式的意义。
This paper investigates the use of conversational agents to scaffold on-line collaborative learning discussions through an approach called Academically Productive Talk (APT). In contrast to past work on dynamic support for collaborative learning, where agents were used to elevate conceptual depth by leading students through directed lines of reasoning (Kumar & Ros,, IEEE Transactions on Learning Technologies, 4(1), 2011), this APT-based approach uses generic prompts that encourage students to articulate and elaborate their own lines of reasoning, and to challenge and extend the reasoning of their teammates. This paper integrates findings from a series of studies across content domains (biology, chemistry, engineering design), grade levels (high school, undergraduate), and facilitation strategies. APT based strategies are contrasted with simply offering positive feedback when the students themselves employ APT facilitation moves in their interactions with one another, an intervention we term Positive Feedback for APT engagement. The pattern of results demonstrates that APT based support for collaborative learning can significantly increase learning, but that the effect of specific APT facilitation strategies is context specific. It appears the effectiveness of each strategy depends upon factors such as the difficulty of the material (in terms of being new conceptual material versus review) and the skill level of the learner (urban public high school vs. selective private university). In contrast, Feedback for APT engagement does not positively impact learning. In addition to an analysis based on learning gains, an automated conversation analysis technique is presented that effectively predicts which strategies are successfully operating in specific contexts. Implications for design of more agile forms of dynamic support for collaborative learning are discussed.