Content Curation with User-Selected Learning Criteria
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Solution Overview
Problem
Existing electronic content curation systems fail to adequately reflect individual user needs and preferences, often presenting content that is a poor match due to reliance on criteria that do not capture specific user criteria such as learning styles, job relevance, and content length.
Innovation Solution
A computer-based process for curating content, such as e-learning content, that allows users to select criteria like pictorial representations, verbal expression, content summaries, positive/negative reviews, job market relevance, and content length to tailor content presentation to individual preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If content is sorted according to reviews from other users, then content popularity is improved, but individual user needs and preferences are not adequately reflected
Solution Approach 1:
The patent segments the monolithic review-based sorting system into multiple independent sorting dimensions (pictorial content, verbal content, job market relevance, content length, etc.). Each dimension can be independently weighted and combined based on individual user preferences, allowing the system to maintain popularity metrics while adapting to diverse user needs through customizable sorting profiles.
2Device complexity
If content is sorted according to generic criteria, then system simplicity is improved, but content recommendation accuracy for individual users deteriorates
Solution Approach 1:
The patent implements dynamic sorting where the sorting criteria and weights are not fixed but can be adjusted based on individual user preferences and characteristics. The system adapts the sorting algorithm in real-time based on user-selected dimensions (such as pictorial vs. verbal content preference, job market relevance weight, content length preferences), transforming a static generic sorting system into a dynamic personalized recommendation system.
3Measurement precision
If multiple sorting criteria are added to reflect individual preferences, then content recommendation accuracy is improved, but system complexity increases
Solution Approach 1:
The patent creates a universal sorting framework that handles multiple sorting criteria through a unified algorithmic structure. Rather than implementing separate sorting systems for each criterion (pictorial content, verbal content, job market relevance, content length), the system uses a single multi-functional sorting mechanism that can process and weight multiple dimensions simultaneously, reducing overall system complexity while maintaining high recommendation accuracy.
Data Source
AI summary
Systems and methods for curation of content, such as e-learning content or online instructional materials, according to particular criteria such as the amount of pictorial representations contained therein, the amount of verbal expression contained therein, and whether the content contains a summary. Other criteria may also be employed. Users may select any one or more of these and other criteria. Content is then sorted according to the selected criteria and presented as an ordered list of content that users can select for viewing.