The use of argumentation in education has been shown to improve critical thinking skills for end-users such as students, and computational models for argumentation have been developed to assist in this process. Although these models are useful for evaluating the quality of an argument, they oftentimes cannot explain why a particular argument is considered poor or not, which makes it difficult to provide constructive feedback to users to strengthen their critical thinking skills. In this survey, we aim to explore the different dimensions of feedback (Richness, Visualization, Interactivity, and Personalization) provided by the current computational models for argumentation, and the possibility of enhancing the power of explanations of such models, ultimately helping learners improve their critical thinking skills.

翻译：在教育领域使用论证已被证明能够提升学生等终端用户的批判性思维能力，为此人们开发了用于辅助该过程的论证计算模型。尽管这些模型在评估论证质量方面卓有成效，但它们往往无法解释为何特定论证被视为优劣，这使得难以向用户提供建设性反馈以增强其批判性思维能力。本综述旨在探究当前论证计算模型所提供的反馈的不同维度（丰富性、可视化、交互性与个性化），以及增强此类模型解释能力的可能性，最终帮助学习者提升其批判性思维能力。