Adapting Software Instructional Videos Across Versions
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Solution Overview
Problem
Users face difficulties in understanding software application instructional videos when the video is prepared for a different software application version than the one they are using, due to interface layout differences, which prevents them from resolving issues effectively.
Innovation Solution
A computer-implemented method and system that analyzes an instructional video to learn the steps required for a specific software application function, then adapts these steps to create a new instructional video or augment an existing one for a different software application version, using virtual machines, neural networks, and natural language processing to ensure compatibility and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If instructional videos are created for specific software application versions, then the videos provide accurate guidance for that version, but the videos become outdated and incompatible when software is updated to a new version
Solution Approach 1:
The system performs preliminary analysis of the original instructional video to extract method steps, software application information, and interface element descriptions before the software version changes. This advance preparation enables rapid adaptation when version updates occur, as the core method steps can be reused and only the interface elements need updating.
Solution Approach 2:
The system changes the parameter of software version compatibility by using machine learning models to identify and update interface element mappings between different software versions. The method steps remain constant while the interface element parameters are adapted to match the new version's layout and terminology.
2Measurement precision
If instructional videos are manually updated for each software version, then the videos remain accurate, but the time and resources required increase significantly
Solution Approach 1:
The system enables self-service updating of instructional videos by using machine learning models to automatically analyze software interface changes and adapt the video content. The system autonomously extracts method steps, identifies interface elements, and generates updated videos without requiring manual intervention from instructional designers.
Solution Approach 2:
The patent replaces the mechanical process of manual video updating with an automated machine learning-based system. Instead of manually reviewing and editing videos for each software version, the system uses neural networks and natural language processing to automatically adapt the content, dramatically reducing the time and labor required.
3Adaptability or versatility
If generic instructional videos are created to cover multiple software versions, then the videos remain relevant across versions, but the videos lack specificity and fail to provide accurate guidance for version-specific interface changes
Solution Approach 1:
The system applies local quality by maintaining generic method steps that are version-agnostic while automatically updating the specific interface element descriptions to match each software version. This allows the video to have both broad applicability and version-specific accuracy, with different levels of detail applied to different parts of the content.
Data Source
AI summary
Aspects of the invention include receiving a first instructional video describing a first method of using a function of a first software application; determining each step of the first method described in the first instructional video; determining, by the processor, a second method of using a first function of a second software application, wherein the first function of the first software application is substantially the same as the first function of the second software application; and creating a second instructional video describing each step of the second method.