The Socrates Project: Assessment Redesign in the Age of AI

Small Wars Journal | Anthony A. Joyce

The US Army Command and General Staff College implemented the Socrates Project across two cohorts of over 120 students in its AI Basic Course to combat academic dishonesty driven by generative artificial intelligence. Built on the GenAI.mil platform using Google Gemini, Socrates forces officers into guided Socratic dialogues that measure real-time cognitive reasoning and Bloom's Taxonomy comprehension levels rather than evaluating static essay submissions.

This shift from grading finished written artifacts to evaluating observable thought processes addresses vulnerabilities exposed by earlier automated grading experiments like Project Athena. The platform employs an autonomous multi-agent structure featuring an evaluator sub-agent and a report compiler to generate objective percentage scores and track student engagement transparently. By incorporating real-time feedback modeled on the Army Fitness Test standard, the system converts generative tools from ghostwriters into developmental editors. PME institutions deploying agentic ecosystems face evolving requirements to balance automated cognitive assessment with human faculty oversight during officer professional development.

Comment

Integrating conversational sub-agents on the Department of War's GenAI.mil platform alters the evaluation vector for professional military education by targeting cognitive methodology rather than output artifacts. By replacing static term papers with continuous interaction logs at the Command and General Staff College, the architecture exposes whether an officer comprehends tactical and operational concepts or merely prompts a large language model. This structural transition creates a granular diagnostic record of staff officer analytical fluency before those officers assume planning responsibilities within operational headquarters.

Downstream, this diagnostic shift affects how military learning management systems archive and evaluate cognitive readiness across an officer's career. Intelligence and staff directorates within the Combined Arms Center gain direct oversight into staff officer reasoning patterns under timed, adversarial questioning. Consequently, the Command and General Staff College's agentic evaluation framework establishes a data baseline for predicting how future staff officers process complex operational environments in real-time planning cells.

Strategic Question for Discussion

If the Command and General Staff College expands conversational AI evaluation across its broader curriculum, which factor presents a greater bottleneck to officer development — the risk of students gaming the agent's evaluation rubric, or the potential loss of traditional faculty mentorship during deep analytical writing?

The available evidence points toward the erosion of direct faculty mentorship as the primary long-term operational friction point for the Command and General Staff College. While sub-agent evaluators on GenAI.mil effectively standardize grading consistency, relying on automated dialogue risks reducing officer development to algorithmic rubric-satisfaction unless human instructors actively intervene during complex operational scenarios.

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