arXiv:2605.30187v1 Announce Type: new Abstract: The widespread adoption of AI chatbots in education will drastically change learning, making responsible deployment a critical concern. While large language models (LLMs) might have access to sources discussing insights from educational sciences, they are not particularly inclined to adhere to pedagogical concepts, risking negative effects on the learning process, such as a loss of transfer capabilities, critical thinking, or creativity. In this paper, we introduce an agentic AI chatbot architecture assisting students with exercise solving, speci
The rapid advancement and widespread adoption of LLMs necessitate immediate focus on responsible integration into critical sectors like education, preventing adverse effects on core learning outcomes.
This paper highlights the critical need for pedagogical oversight in AI educational tools, directly addressing concerns about the erosion of critical thinking and creativity in students who rely on unguided LLMs.
The proposed modular, agentic AI chatbot architecture moves beyond simple information retrieval, aiming for a more pedagogically sound and responsible application of LLMs in learning assistance.
- · Educational technology providers focused on responsible AI
- · Students with access to well-designed AI learning assistants
- · Researchers in AI ethics and education
- · Academic institutions implementing modular AI solutions
- · Developers of undifferentiated or pedagogically unsound LLMs for education
- · Traditional educational models resistant to guided AI integration
- · Students relying solely on unmoderated generative AI for learning
- · Educational publishers slow to adapt to AI-driven learning tools
Educational curricula will likely begin to integrate specific modules teaching interaction with and critical evaluation of AI learning assistants.
This could lead to a bifurcation in educational outcomes, where students with access to responsible AI tools gain an advantage over those using unguided or poorly designed systems.
The successful implementation of agentic educational LLMs could inform the development of similar modular and responsible AI agents in other sensitive sectors, such as healthcare or finance.
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Read at arXiv cs.AI