National University of Kaohsiung /  Prof. Chian-Hsueng Chao

 Pain Points Solved 

To solve the dilemma of learning 'where to start,' our AI-Customized Learning Roadmap System leverages a massive database of millions of book catalogs to map out precise knowledge points. By analyzing hierarchical structures and node relationships, we’ve built a robust Knowledge Graph that serves as the system's core. Using Dijkstra’s algorithm and smart weighting, the system crafts the most efficient, personalized learning route for every user. Combined with an interactive gamification design, we ensure a learning experience that is not only personalized but also highly engaging and habit-forming

 Technology Introduction 

Core Technical Features & Market Potential
1. Knowledge Graph Construction Technology
Constructs associations and hierarchical structures of knowledge points based on large-scale book directory data. This ensures that learning content is delivered with high systematic rigor and logical coherence.

2. Personalized Path Recommendation Mechanism
Integrates Dijkstra’s algorithm with a weighted scoring system to generate customized learning paths tailored to the specific needs and individual differences of each learner.

3. Enhanced Learning Efficiency
Unlike traditional linear learning models, this system helps learners quickly identify the optimal starting point and progression. This minimizes the "trial-and-error" cost and significantly streamlines the learning process.

4. Gamification for Increased Engagement
Utilizes a gamified interface and incentive mechanisms to boost learners' motivation, long-term retention (stickiness), and overall course completion rates.
5.Application Potential
The system holds significant promise for expansion into various academic disciplines, digital learning platforms, and Intelligent Tutoring Systems (ITS).

Module 1: Topic Selection & Curriculum
User Entry: The "Departure" Module Upon logging in, users enter the "Departure" module, where learning topics (e.g., Python, JavaScript) are presented in a card-based interface. Each card displays the course title, estimated duration, and number of units.
•    Available Topics: Can be accessed directly to begin learning.
•    Locked Topics: Marked as "LOCKED"; these require specific prerequisites to unlock.
•    Action: Clicking "Start Multi-Path Adventure" initializes the course map and triggers the learning workflow.

Figure 1: Main Interface

Module 2: Course Map & Learning Progress
Interactive Knowledge Structure After entering a course, the system visualizes the knowledge structure and learning routes through an interactive hexagonal map.
•    Node Layout: Each node represents a specific Knowledge Unit.
•    Multi-Path Design: Offers flexibility for learners to choose their own learning sequence.
•    Status Indicators:
o    Completed: Indicated by dark shading.
o    In Progress: Highlighted/Glowing.
o    Locked: Greyscale/Grey.

Figure 2: Learning Course Map Interface

Module 3: Career Matching System 
Bridging Learning Outcomes and Career Goals This system translates learning progress into career directions, providing job recommendations and Skill Gap Analysis.
•    Current Market Value: Displays proficiency levels in "Monthly Salary (TWD 10k/month)" with an upgrade progress bar to make growth tangible.
•    Job Matching: Filters job openings by salary and location. Each card displays the Match Rate and identifies specific Skill Gaps, sorted by relevance.
•    Growth Loop: The system utilizes a "Learn → Feedback → Re-learn" cycle to guide users in bridging their skill gaps and ensuring continuous improvement.

Figure 3: Career Matching System Interface
 

 Application Examples 

1.Education Technology (EdTech) Industry
2.Digital Learning Platforms
3.Online Course Recommendation Systems
4.Intelligent Tutoring Support Systems
5.Corporate Training Platforms
6.Personalized Learning and Knowledge Management Products

 Related Links 

None

 Patent Name and Number 

None

 Industry-Academia / Tech Transfer Partner 

None

 Honors and Awards  

None

 Technical Contact  

Vivian Lee, Administrative Assistant 

National University of Kaohsiung
Tel: +886 7-5916639
Email: vivianlee@nuk.edu.tw