Information Processing for Ability-Based Practice Planning
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Solution Overview
Problem
Individuals often struggle to effectively improve their abilities without external guidance, as they rely on self-directed practices using magazines, internet information, and word-of-mouth, leading to inconsistent progress and unmet goals in physical and academic skills.
Innovation Solution
An information processing method that includes obtaining a target period for goal achievement, setting a goal based on user ability, and determining a practice method using a computer system to provide personalized practice plans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If people practice on their own without external guidance, then they can freely choose their practice methods, but they struggle to gauge their level of improvement and may not reach their goals
Solution Approach 1:
The system provides feedback to users by comparing their current ability (measured through practice results) with the target goal. It generates practice plans based on this comparison, allowing users to see their progress and adjust their practices accordingly. This feedback loop enables self-directed practice while maintaining reliability of goal achievement.
Solution Approach 2:
The system enables users to create their own practice plans without requiring external trainers or coaches. Users input their current ability and target goal, and the system automatically generates personalized practice recommendations. This self-service approach maintains freedom of choice while improving goal achievement reliability through systematic planning.
2Adaptability or versatility
If people rely on self-directed practices using magazines and internet information, then they can access practice methods freely, but their progress becomes inconsistent and goals remain unmet
Solution Approach 1:
The system changes the parameters of practice methods based on the user's current ability and target goal. Instead of providing generic practice advice, it dynamically adjusts practice recommendations to match the user's specific situation, improving productivity while maintaining adaptability to individual needs.
Solution Approach 2:
The system performs preliminary analysis of the user's current ability and target goal before generating practice plans. This preliminary action ensures that the practice methods are pre-tailored to the user's specific needs, improving effectiveness from the start while maintaining versatility in approach.
3Productivity
If a personalized practice plan is created based on user ability and goals, then practice effectiveness improves, but the system complexity increases
Solution Approach 1:
The system reduces its own complexity by enabling users to input their own ability and goal information, which automatically triggers the personalized practice plan generation. This self-service mechanism eliminates the need for complex manual assessment processes while maintaining high practice effectiveness.
Solution Approach 2:
The system replaces complex manual assessment and planning mechanisms with automated computational processes. Instead of requiring human trainers to analyze abilities and create plans, the system uses algorithms to process user input and generate personalized recommendations, reducing system complexity while improving effectiveness.
Data Source
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Figure 2A~2B
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AI summary
An information processing method to be performed by a computer (4, 7, 4a, 7a) 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.