这篇论文给考试设计开了个新脑洞：用多模态对话和动态评估测认知边界，比传统考试更看重进步而不是扣分。
这篇论文提出了Socratic Test的自动化计算机中介对话式评估框架，整合动态评估原则、多模态工作区、Bloom分类学实时监考和SOLO分类学结构评估。传统静态评估依赖减法扣分制，而面对面口试会引入表现焦虑和学术权力失衡等无关变量。Socratic Test通过渐进化支架量化最近发展区（ZPD），并采用非补偿性加法评分架构，优先衡量掌握程度而非惩罚错误。
The Theoretical Foundation of Socratic Tests: Dynamic, Multimodal, Conversational Examinations
Traditional static assessments rely on a subtractive, deficit-based grading model that often penalizes ambition and obscures diagnostic feedback. Conversely, traditional face-to-face oral examinations introduce severe construct-irrelevant variance by exacerbating performative anxiety and the sociological power imbalances inherent to academic hierarchies. This paper presents the theoretical foundation for the "Socratic Test," an automated, computer-mediated conversational assessment. By integrating Dynamic Assessment principles, multimodal workspaces, Bloom's Taxonomy for real-time proctoring, and the SOLO Taxonomy for structural evaluation, the Socratic Test actively maps a student's cognitive boundaries. This paper formalizes the use of graduated scaffolding to quantify the Zone of Proximal Development (ZPD) and details a non-compensatory, additive grading architecture that prioritizes mastery over penalty and human-AI alignment to ensure unprecedented measurement reliability.