Adaptive User Confusion Detection via Decision Time Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for detecting user confusion in navigating hierarchical menu structures rely on predefined thresholds, which fail to accurately account for individual differences in user skill, perception, and motivation, leading to inadequate confusion detection and support.
Innovation Solution
A user support device that judges user confusion based on an increase in decision-making time for input actions, using a confused state judging unit to analyze decision-making times and provide operation support tailored to each user's context.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a predefined threshold for dwell time is used to detect user confusion, then the detection method is simple and easy to implement, but it fails to accurately account for individual differences in user skill, perception, and motivation, leading to inaccurate confusion detection
Solution Approach 1:
The patent applies dynamics by making the confusion detection threshold adaptive rather than fixed. The system dynamically adjusts the threshold based on the user's operation history and characteristics, allowing the detection criterion to evolve and personalize for each user. This resolves the contradiction by enabling accurate detection of individual user confusion states without requiring overly complex predefined rules for each user profile.
Solution Approach 2:
The system implements feedback by continuously monitoring user operations and using the detected operation characteristics to adjust the confusion detection threshold. The operation history is fed back into the detection mechanism, allowing the system to learn from each user's behavior patterns and refine its confusion detection accuracy over time, thereby achieving high precision without excessive complexity.
2Reliability
If individualized confusion detection is implemented to account for user differences, then detection accuracy improves, but the system complexity and computational requirements increase
Solution Approach 1:
The system performs preliminary action by pre-processing and storing operation history data in an organized manner before confusion detection is needed. The operation history is accumulated and structured in advance, allowing the detection algorithm to efficiently access and analyze relevant data without requiring complex real-time processing, thus achieving reliable individualized detection with manageable system complexity.
Solution Approach 2:
The system applies self-service by enabling users to implicitly define their own confusion thresholds through their natural operation patterns. The system automatically learns each user's operational characteristics and uses this self-generated data to establish personalized detection criteria, eliminating the need for complex external configuration or manual threshold setting while maintaining high reliability.
3Ease of operation
If operation support is provided based on accurate confusion detection, then user guidance is appropriate and effective, but the processing time and computational resources increase
Solution Approach 1:
The system prepares operation support content in advance based on predicted confusion scenarios. By pre-processing and organizing support information before it is actually needed, the system can quickly retrieve and present appropriate guidance when confusion is detected, thereby maintaining high quality user support while minimizing the time loss during actual confusion events.
Data Source
AI summary
A user support device which accurately judges that a user is in a confused state and supports the user is provided. The user support device includes: a confused state judging unit which judges whether the user is in a confused state or not based on a tendency of variation in dwell time on which a decision making time until a next input action is executed is reflected in a sequence of input actions executed by the user who makes transitions between several menus arranged in a tree structure; and an operation support processing unit which provides operation support when the confused state judging unit makes a positive judgment that the user is in a confused state.