An agile-inspired learner model for conversational AI in education

Conversational agents are increasingly used in education, yet most educational chatbots remain content-centric and rely on learner models that represent knowledge states while leaving the learning process itself implicit. This paper introduces a process-oriented learner model that embeds principles from Agile methodology directly into the internal state of an AI-driven educational chatbot to support students' independent learning. In this model, learning objectives are represented as epics, study cycles as competence-driven sprints, and micro-level goals as user stories governed by explicit definitions of done. We implement the approach in a multi-agent Telegram chatbot used in an introductory university programming course. An exploratory feasibility study with 16 university students and recent graduates (N=16) provides preliminary evidence of the approach's pedagogical promise. Participants reported that the Agile-structured interaction improved goal clarity, step-by-step progressio n, and reflective engagement, though technical limitations in response latency and explanation depth were identified. This paper shows the feasibility of embedding explicit process models within conversational AI for education and motivates further investigation with larger samples and controlled evaluations.