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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.

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