Dynamic Choice Reference for Digital Survey Relevance
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Solution Overview
Problem
Conventional digital survey systems face inefficiencies and inflexibility due to compounding branches of questions and answer choices, leading to increased data storage, processing requirements, and limitations in providing relevant surveys to users, resulting in inaccurate and irrelevant responses.
Innovation Solution
A dynamic choice reference system that selects answer choices for digital survey questions based on user responses and embedded data, eliminating the need for compounding branches by dynamically generating surveys with relevant options, reducing computational resources and improving survey relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional digital survey systems use compounding branches of questions and answer choices to provide relevant surveys to individual users, then survey relevance to individual users is improved, but data storage requirements and computational processing increase significantly
Solution Approach 1:
The system dynamically generates answer choices at runtime based on user responses to previous questions, rather than pre-defining all possible branches. This allows the survey to adapt to individual users while maintaining a compact core question set, resolving the contradiction between survey personalization and data storage requirements
Solution Approach 2:
The survey is divided into core questions that remain static and answer choices that are dynamically generated. This segmentation allows the system to store only essential question data while generating specific answer options on-demand, reducing overall data storage needs while maintaining individualized survey relevance
2Adaptability or versatility
If conventional digital survey systems create compounding branches of digital survey questions to provide relevant surveys, then individual user relevance is improved, but device complexity and processing requirements increase
Solution Approach 1:
The system uses dynamic answer choice generation where answer options are created based on user responses rather than pre-programming all branches. This reduces the complexity of the survey logic while maintaining the ability to provide personalized surveys, as the system only needs to process one question at a time and generate answers on-demand
Solution Approach 2:
The system automatically generates answer choices based on user responses without requiring manual configuration of complex branching logic. This self-service approach reduces the complexity burden on the survey administrator and simplifies the overall system architecture while maintaining individualized survey capability
3Stability of the object's composition
If conventional digital survey systems use rigid compounding branches, then survey structure is maintained, but flexibility in providing relevant answer choices is reduced
Solution Approach 1:
The system maintains a stable core survey structure with defined questions while dynamically generating answer choices that adapt to user responses. This allows the survey to preserve its fundamental structure and flow while providing flexible, relevant answer options tailored to each user's previous responses, resolving the contradiction between structural stability and answer choice flexibility
4Reliability
If conventional digital survey systems store logic for each individual response, then complete response tracking is achieved, but computational overhead and processing time increase
Solution Approach 1:
The system pre-defines the core question structure and answer choice generation rules before survey administration. This preliminary preparation allows the system to efficiently process user responses in real-time without requiring complex computational logic during survey taking, maintaining response tracking accuracy while reducing computational overhead during actual survey administration
Data Source
AI summary
This disclosure covers methods, systems, and computer-readable media that select answer choices from potential answer choices for a digital question based on responses to other digital questions and/or embedded user data. In certain embodiments, the disclosed systems select answer choices from potential answer choices for a digital question based on a multiple choice response. Furthermore, in some embodiments, the disclosed systems select answer choices from potential answer choices for a digital question based on keywords and/or sentiment values identified by analyzing a text response. In some embodiments, the disclosed systems select answer choices for a digital question from a dynamic choice reference dataset that comprises potential answer choices. Additionally, in one or more embodiments, the disclosed systems train and/or utilize a machine-learning model to select answer choices from potential answer choices for a digital question based on a response.