Thesis Description & Objectives
Problem:
Students often struggle to engage deeply with complex topics, and most study tools do not support the cognitive benefits of learning-by-teaching. Without a system that lets learners explain and refine knowledge for a “novice,” they miss a powerful mechanism for strengthening understanding.
Objective:
Study and develop a platform where students “teach” an agent that simulates progressive learning. Using structured memory and adaptive dialogue, the system will tailor future interactions based on what the student has explained.
Approach:
Select a suitable topic; design and develop an agent (e.g., a chatbot) that builds knowledge from student input through adaptive memory. Validate the tool and compare it to a static, non-adaptive chatbot.
Expected Impact:
A more engaging learning environment that leverages the learning-by-teaching paradigm to improve comprehension, metacognition, and student motivation.
