Time-Adjusted Virtual World Video for Adaptive Learning Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing educational systems lack the ability to effectively integrate real-world environments and interactive learning experiences, limiting the engagement and comprehension of learners in virtual and augmented reality educational platforms.
Innovation Solution
A computing system that integrates environment sensor modules to capture real-world data, combines it with modeled environment information, and instructor inputs to create immersive learning experiences, allowing for the production of time-adjusted video in virtual worlds, enabling interactive and assessment-driven learning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional educational systems are used, then system simplicity is maintained, but learner engagement and comprehension are limited
Solution Approach 1:
The patent merges virtual reality environments with real-world sensor data and instructor inputs into a unified educational platform. This integration combines multiple data sources (environment sensors, learner devices, instructor annotations) to create an immersive learning experience that adapts to individual learner needs while maintaining system manageability through centralized coordination.
Solution Approach 2:
The educational system is designed to serve multiple functions simultaneously: it provides immersive virtual reality experiences, captures real-world environmental data, processes learner interactions, enables instructor annotations, and delivers adaptive content. This multi-functional approach increases adaptability without proportionally increasing complexity, as the system handles diverse tasks through integrated modules.
2Reliability
If real-time feedback and assessment are implemented, then learning effectiveness is improved, but system complexity increases
Solution Approach 1:
The system implements continuous feedback loops where learner interactions with virtual objects and environments are automatically tracked, assessed, and used to provide real-time guidance. Instructor annotations and environmental sensor data also feed into the assessment process, creating a comprehensive feedback mechanism that enhances learning effectiveness while distributing complexity across automated and human elements.
Solution Approach 2:
The system prepares assessment criteria and feedback mechanisms in advance through instructor-defined learning objectives and pre-configured virtual environment parameters. This preliminary setup allows real-time feedback to be delivered efficiently during learning activities without requiring complex on-the-fly decision-making, thereby reducing operational complexity while maintaining reliability.
3Loss of information
If immersive virtual reality environments are created, then learner comprehension is enhanced, but data processing requirements increase
Solution Approach 1:
The virtual reality environment is divided into discrete interactive objects and spatial zones, each with specific data collection and processing requirements. This segmentation allows the system to process only relevant data for each learner's current focus area rather than continuously processing all environmental data, reducing energy consumption while maintaining comprehensive comprehension support.
Solution Approach 2:
The system processes environmental and interaction data at varying levels of detail based on learner needs and context. Not all virtual objects require the same level of data processing simultaneously; the system adjusts processing intensity dynamically, applying full processing only where necessary for comprehension while using simplified processing for peripheral elements, thereby reducing overall energy requirements.
Data Source
AI summary
A method for execution by a computer to produce video in a virtual world environment includes selecting a lesson package based on a learner affinity for a learner to produce a selected lesson package. The method further includes selecting an active virtual world environment of a set of active virtual world environments to produce a selected virtual world environment. The method further includes determining a learner perception approach for the learner based on the learner affinity, where the learner perception approach maps a baseline four dimensional model of the selected virtual world environment to a learner specific four dimensional model of the selected virtual world environment. The method further includes rendering updated first descriptive asset video frames of a first descriptive asset and updated second descriptive asset video frames of a second descriptive asset within the learner specific four dimensional model to produce a new video stream for the learner.