A Prompt-Engineering Approach to Develop Scalable, Flexible, and Real-Time Hybrid Micro-Level Personalization in a General Purpose AI Teaching Assistant

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prompt-engineeringpersonalizationAI teaching assistantslearner profiling

2609.03402

Builder Relevance

80%

1h ago

Abstract

This study presents a prompt-engineering-based framework for personalizing AI teaching assistants across academic disciplines and courses.

Reality Card

Core Claim

The framework enables personalization of AI teaching assistants using six learner-specific dimensions, resulting in 96 distinct learner profiles without requiring model retraining.

Method / Result

The framework was evaluated through experiments, showing perceived differences in response style and structure across personalization conditions.

Limitations

The study involved a small human participant group (five participants), which may limit the generalizability of the findings.

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