Dynamic Content Path Selection for Personalized E-Learning
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Solution Overview
Problem
Existing e-learning systems have static content that is difficult to customize for individual users, limiting personalized learning experiences.
Innovation Solution
A system that stores content graph information and path graph information to select and present individual items of content to users based on their access patterns, using a rules-based approach that considers social ties, biographical information, and user profiles to recommend personalized content paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static content is used in e-learning systems, then content delivery is simple and straightforward, but the system cannot be customized for individual users
Solution Approach 1:
The patent implements dynamic content selection by tracking user access paths and using this information to adapt content delivery. The system transitions from static content delivery to dynamic content recommendation based on actual user behavior patterns, allowing the system to adjust and evolve based on individual user needs.
Solution Approach 2:
The system incorporates feedback mechanisms by monitoring and storing path graph information about user access patterns. This feedback is used to refine future content selections, creating a closed-loop system that continuously improves its ability to customize content based on actual user interactions.
2Reliability
If personalized content paths are implemented, then learning effectiveness is improved, but data storage and processing requirements increase
Solution Approach 1:
The patent extracts and stores only the essential path graph information - the sequence of content access paths - rather than storing complete user interaction data. This selective extraction approach reduces data storage requirements while maintaining the information needed for effective personalization.
Solution Approach 2:
The system performs preliminary data collection and path tracking during normal operation, storing access patterns in advance. This preliminary action allows the system to prepare personalized content paths without requiring additional real-time processing resources, reducing the burden on storage and processing systems.
Data Source
AI summary
A method includes storing content graph information regarding individual items of content accessed by one or more users of a system, storing path graph information comprising the order in which each of the one or more users accessed individual items of content, and selecting individual items of content to be presented to a subsequent user of the system and an order in which such individual items of content are presented to the subsequent user based on the stored content graph information and the stored path graph information.