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Research PaperResearchia:202608.03055

The Theoretical Foundation of Socratic Tests: Dynamic, Multimodal, Conversational Examinations

Ilya Mikhelson

Abstract

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 integrati...

Submitted: August 3, 2026Subjects: AI; Artificial Intelligence

Description / Details

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.


Source: arXiv:2607.29624v1 - http://arxiv.org/abs/2607.29624v1 PDF: https://arxiv.org/pdf/2607.29624v1 Original Link: http://arxiv.org/abs/2607.29624v1

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Date:
Aug 3, 2026
Topic:
Artificial Intelligence
Area:
AI
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