AI Tutor: An AI Learning Assistant Embedded in Digital Textbook
Services
Web Design
Client
Dong-A Publishing
Date
February 2025
Project Overview
AI Tutor is a conversational learning assistant embedded in AI-powered digital textbooks, designed to guide students through their educational journey with empathy and clarity.
By modeling contextual dialogues, structuring intuitive interfaces, and aligning with school curricula, AI Classmate offers supportive, real-time interactions that help students build confidence, stay curious, and learn independently.
Project Highlights
Goal
AIDT aims to design an AI-based chatbot for digital textbooks with intuitive and user-friendly interfaces and conversational experiences that enable teachers and students to explore actively and maintain curiosity. This was achieved by developing conversation logic tailored to various scenarios encountered during learning.
Outcome
The main challenge was to provide consistent and intuitive responses through context-aware conversation logic across various learning scenarios. Additionally, efforts were made to ensure that AI responses align with the curriculum without causing confusion for learners.
Challenge
The final deliverable provided a natural conversational experience based on context-aware dialogue logic tailored to Dong-A Publishing's specific requirements. It proposed a solution capable of offering immediate and accurate support for users' challenges during learning.
Project Timeline
Service Policy
Reflecting the internal needs of the client, we clearly defined the terminology used in the specification and systematically organized service-related policies. This approach aimed to deliver a precise and easily understandable policy document.
UI Wireframe
The chatbot’s layout, structure, and conversation flow were designed to clearly convey key elements and naturally adapt to various situations, providing an intuitive and seamless experience that supports uninterrupted learning.
Dialogue Modeling
Dialogue scenarios were structured by priority and exposure conditions, and the conversation logic and UI elements were systematized to deliver a natural and consistent chatbot experience across diverse learning situations.
