Assessment literacy (AL) is essential for personalized education, yet difficult to cultivate in pre-service teachers. Conventional teacher preparation programs focus on theoretical knowledge, while digital assessment tools commonly provide opaque scores or parameters. These limitations hinder reflection and transfer, leaving AL underdeveloped. We propose XIA, an eXplainable Intelligent Assessment platform that extends statistics-informed support with visualized cognitive diagnostic reasoning, including contrastive and counterfactual explanations. In a pre-post controlled study with 21 pre-service teachers, we combined quantitative tasks and questionnaires with qualitative interviews. The findings offer preliminary evidence that XIA supported reflection, self-regulation, and assessment awareness, and helped reduce assessment errors. Interviews further showed a shift from score-based judgments toward evidence-based reasoning. This work contributes insights into the design of intelligent assessment tools, showing how explanatory scaffolding can bridge assessment theory and classroom practice and support the cultivation of AL in teacher education.

翻译：评估素养对于个性化教育至关重要，但在职前教师中难以培养。传统的教师培养项目侧重于理论知识，而数字化评估工具通常提供不透明的分数或参数。这些限制阻碍了反思与迁移，导致评估素养发展不足。我们提出了XIA（可解释智能评估）平台，该平台在基于统计的支持基础上，扩展了可视化的认知诊断推理，包括对比式与反事实解释。在一项包含21名职前教师的前后测对照研究中，我们结合了定量任务、问卷与定性访谈。研究结果提供了初步证据，表明XIA支持了反思、自我调节与评估意识，并有助于减少评估错误。访谈进一步揭示了从基于分数的判断向基于证据的推理的转变。这项工作为智能评估工具的设计提供了见解，展示了解释性支架如何能连接评估理论与课堂实践，并支持教师教育中评估素养的培养。