Target-Period Goal Setting and Personalized Practice Recommendation
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Solution Overview
Problem
Individuals often struggle to set realistic goals and develop effective practice strategies for improving their physical or academic abilities without external guidance, leading to suboptimal training and learning outcomes.
Innovation Solution
An information processing method that determines a user's current ability, sets achievable goals based on a target period, and recommends personalized practice or learning methods using a database of past practices, allowing users to select the most suitable approach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If individuals set goals and develop practice strategies without external guidance, then autonomy and self-directed learning are improved, but goal realism and practice effectiveness deteriorate
Solution Approach 1:
The patent introduces an information processing system as an intermediary between the user and goal achievement. This system automatically determines realistic goals based on user ability and target periods, and recommends appropriate practice methods, thereby mediating the gap between user autonomy and goal realism without requiring external human guidance
Solution Approach 2:
The system enables users to set their own target periods and view their current ability levels, allowing them to participate in the goal-setting process. The computer then automatically determines realistic goals and practice strategies based on this self-provided information, combining user autonomy with algorithmic precision in goal realism
2Adaptability or versatility
If individuals develop practice strategies without external guidance, then independence is improved, but training effectiveness and outcome quality worsen
Solution Approach 1:
The information processing system acts as an intermediary that provides reliable practice method recommendations based on database queries. It matches user-specific parameters (ability, target period, goal) with proven practice strategies from the database, ensuring training effectiveness while maintaining user independence in the overall planning process
Solution Approach 2:
The system performs preliminary analysis of user ability and automatic determination of realistic goals before recommending practice methods. This preliminary action ensures that the practice strategies recommended are aligned with achievable goals, thereby guaranteeing training effectiveness before the user even begins their practice routine
3Device complexity
If generic training approaches are used, then simplicity is improved, but learning outcomes and ability improvement worsen
Solution Approach 1:
The patent applies local quality by providing practice method recommendations that are specifically tailored to each user's local conditions - their current ability level, target period, and determined goal. The database stores diverse practice strategies that can be locally selected and adapted to individual user needs, replacing generic one-size-fits-all approaches with personalized solutions
Solution Approach 2:
The system changes parameters by automatically adjusting goal difficulty and practice method recommendations based on user ability and target period. The information processing dynamically modifies training parameters to match individual user characteristics, thereby improving ability enhancement rates while maintaining simplicity for the user
Data Source
AI summary
An information processing method to be performed by a computer includes: obtaining a target period for goal achievement of a user; setting a goal, based on the target period and current ability of the user; and determining a practice method, based on the goal and the target period.