We investigate personalizing the explanations that an Intelligent Tutoring System generates to justify the hints it provides to students to foster their learning. The personalization targets students with low levels of two traits, Need for Cognition and Conscientiousness, and aims to enhance these students' engagement with the explanations, based on prior findings that these students do not naturally engage with the explanations but they would benefit from them if they do. To evaluate the effectiveness of the personalization, we conducted a user study where we found that our proposed personalization significantly increases our target users' interaction with the hint explanations, their understanding of the hints and their learning. Hence, this work provides valuable insights into effectively personalizing AI-driven explanations for cognitively demanding tasks such as learning.

翻译：我们研究了如何个性化智能辅导系统生成的解释，以证明其为帮助学生促进学习而提供的提示的合理性。个性化针对的是在“认知需求”和“尽责性”两个特质上得分较低的学生，其目的是增强这些学生对解释的参与度，依据是此前的发现：这些学生自然状态下不会参与解释，但如果参与则能从中获益。为评估个性化的有效性，我们进行了一项用户研究，发现我们提出的个性化方法显著提高了目标用户与提示解释的互动、对提示的理解以及学习效果。因此，这项工作为有效个性化针对认知要求较高任务（如学习）的AI驱动解释提供了有价值的见解。