Online Gaming Group Assembly via Subpopulation Filtering
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Solution Overview
Problem
In self-paced online education environments, students face challenges in organizing and benefiting from group interactions due to differing start dates, progress rates, and completion times, which hinders social interaction and assessment opportunities.
Innovation Solution
A system and method that filters a subpopulation from a database to form groups based on criteria, offering group interactions, managing participant acceptance and opt-outs, and dynamically replacing absent members, using a filtering engine, offering module, and replacement engine on a non-transitory computer readable medium.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If students progress at different rates in a self-paced online environment, then individual learning flexibility is improved, but group interaction organization becomes more difficult
Solution Approach 1:
The system segments the student population into cohorts based on progress milestones and criteria rather than requiring all students to be at the same stage. This allows group interactions to be organized around shared achievements while maintaining individual pacing flexibility.
Solution Approach 2:
The system performs preliminary filtering and cohort assignment based on established criteria before group interactions occur. By pre-organizing students into appropriate groups based on their progress and characteristics, the system eliminates the need for complex real-time coordination while preserving learning flexibility.
2Adaptability or versatility
If students start on different days and complete coursework at different times, then self-paced learning is improved, but alignment for group interactions deteriorates
Solution Approach 1:
The system establishes periodic cohort formation cycles based on progress milestones rather than calendar time. Students are grouped periodically when they reach specific criteria, creating regular opportunities for group interaction that align with individual progress rates rather than requiring simultaneous participation.
Solution Approach 2:
The system changes the parameter for group formation from time-based (calendar dates) to progress-based (milestone achievement). This allows students to be aligned for group interactions based on their completion of coursework criteria rather than when they started, eliminating alignment time loss while preserving self-paced learning.
3Reliability
If group compositions are dynamically updated to replace absent members, then interaction quality is improved, but system complexity increases
Solution Approach 1:
The system implements automated replacement mechanisms that operate independently without manual intervention. When members are absent, the system automatically identifies and assigns replacements from the filtered population based on established criteria, maintaining interaction quality while minimizing the complexity burden on system managers.
Solution Approach 2:
The system continuously monitors group composition and member participation, using this feedback to trigger automated replacement actions. This closed-loop approach ensures interaction quality is maintained through dynamic updates while the complexity is managed through algorithmic rather than manual processes.
Data Source
AI summary
Methods and systems for assembling remote members of an online gaming environment are provided. The method includes a use of the system to filter a subpopulation from a population stored in a database, the population including members of the online gaming environment. The subpopulation can be selected to meet a first set of criteria for a grouping of the members for a group interaction. Additional criteria can be added to provide control over the selection of the members for the subpopulation and, thus, control over the design of groups to provide a desired group profile for the group interaction.