User-Centric Learning Object Snapshot Generation
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Solution Overview
Problem
Conventional methods for generating a 'snapshot' of a learning object are inconvenient for providers and do not provide adequate information for users, as they are composed from the provider's viewpoint and lack relevance to user interests.
Innovation Solution
A system and method that utilize an interface, learning object database, script preview unit, and multimedia preview unit to generate a 'snapshot' by selecting relevant sentences and multimedia data based on a user's historical learning record, combining them to create a user-centric snapshot.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a provider generates a snapshot by composing an abstract and combining it with pictures, then the snapshot is created from the provider's viewpoint, but the contents do not provide adequate information for users to determine their interest
Solution Approach 1:
The patent inverts the conventional approach by switching from provider-centric snapshot generation to user-centric generation. Instead of the provider composing snapshots based on their own perspective, the system automatically generates snapshots tailored to each user's interests by analyzing their historical learning records and preferences. This inversion resolves the contradiction by maintaining ease of automated generation while significantly improving user-relevant information content.
Solution Approach 2:
The system dynamically changes the parameters of snapshot generation based on user characteristics. By analyzing user profiles, historical learning records, and preferences, the system adjusts the content selection, wording, and presentation of snapshots to match each user's specific interests and needs. This parameter change enables automated generation to produce highly relevant information for each user.
2Ease of manufacture
If conventional methods are used to generate snapshots, then the process is simple for providers, but it is inconvenient for users to use the snapshots effectively
Solution Approach 1:
The system implements self-service by automatically generating personalized snapshots without requiring user intervention in the composition process. Users simply access their customized snapshots that are automatically tailored to their interests based on their historical learning records. This eliminates the inconvenience for users while maintaining simple generation processes through automated intelligent selection of content.
Solution Approach 2:
The system performs preliminary actions by pre-analyzing user profiles and historical learning records to prepare personalized snapshot content before users request it. This preliminary customization ensures that when users access snapshots, they immediately receive relevant, tailored information without needing to perform any additional work or configuration, thereby improving ease of operation.
3Device complexity
If snapshots are composed from the provider's viewpoint, then the generation process is straightforward, but the snapshots do not adequately meet user requirements
Solution Approach 1:
The patent transforms the static, provider-centric snapshot generation into a dynamic, user-adaptive process. The system continuously analyzes user interactions, historical learning records, and preferences to dynamically adjust snapshot content for each user. This dynamic approach maintains relatively simple generation processes while achieving high adaptability to individual user needs and interests.
Solution Approach 2:
The system changes generation parameters based on user characteristics by analyzing historical learning records, user profiles, and preferences. This allows the same generation mechanism to produce highly customized snapshots for different users without requiring complex manual intervention, thereby maintaining process simplicity while achieving high user-specific adaptability.
Data Source
AI summary
A system for generating a ‘snapshot’ of a learning object is provided. An interface receives a target object and a user identification number. The target object corresponds to a category, comprising a plurality of sentences and multimedia data, wherein the sentences comprise at least one keyword. A learning object database comprises a plurality of learning objects and a user's historical learning record. Each of the learning objects corresponds to at least one category, and comprises at least one keyword. The user's historical learning record comprises a track record of learning objects used corresponding to the user identification number. A script preview unit selects at least one of the sentences of the target object according to the user's historical learning record corresponding to the user identification number. A multimedia preview unit selects one of the multimedia data of the target object, wherein the selected multimedia data is highly related to the selected sentence. A ‘snapshot’ generator generates a ‘snapshot’ of the target object by combining the selected sentence and the selected multimedia data, and directs a display device to display the ‘snapshot’.