Authors - Frances Ysabelle D. Rebollido, Jaime D.L. Caro Abstract - The rapid development of artificial intelligence (AI) creates new opportunities and challenges in introductory programming education. Existing AI tools provide immediate support and feedback to students, but they have the tendency to generate inaccurate, biased, or pedagogically unsuitable responses. To address this, we introduce the Agentic Learning & Adaptation System (ALAS), an Agentic AI-based system designed to deliver tailored and educationally grounded support for students. Hence, with this process, ALAS generates responses that are adaptive, and pedagogically appropriate. This enables ALAS to provide personalized support to students. Its modular design provides a scalable foundation for integrating additional agents and functions. We present the conceptual design and early-stage prototype of ALAS to demonstrate its potential in enhancing students’ learning experiences and supporting the responsible use of AI in computing education. Future work will focus on implementing and evaluating ALAS in a classroom setting.
