Neural Network Scoring System for Automated Homework Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for correcting tasks such as scoring homework, sports actions, or intellectual project steps are subjective, low in precision, and time-consuming, delaying valuable time for teachers or coaches.
Innovation Solution
An information processing device and method that includes a storage module for acquiring and storing key features, an operational circuit to determine predicted confidence using a neural network, and a controlling circuit to modify key features based on confidence thresholds, enabling automatic and precise scoring and feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If artificial methods (manual correcting, checking) are used to correct homework, sports actions, or intellectual projects, then the process can be performed with simple tools and no complex system, but the method has strong subjectivity, low precision, and is time-consuming
Solution Approach 1:
The patent replaces manual mechanical correction methods with an automated neural network-based system. The neural network model processes input data (images, videos, or other data types) to automatically generate correction results, eliminating the need for human reviewers and their associated subjectivity and time constraints.
Solution Approach 2:
The system enables self-service correction where the neural network automatically evaluates and corrects homework, sports actions, or intellectual projects without requiring human intervention. The model independently performs the correction function, allowing users to simply input data and receive automated feedback.
2Productivity
If manual correcting methods are used, then the system remains simple and easy to operate, but it is time-consuming and delays valuable time for teachers or coaches
Solution Approach 1:
The neural network system operates continuously and automatically, processing correction tasks without interruption. Unlike manual methods that require discrete human intervention, the system can process multiple corrections simultaneously and continuously, dramatically increasing productivity and eliminating time delays.
Solution Approach 2:
The patent replaces time-consuming manual correction processes with automated neural network inference, which can rapidly process data and generate corrections in seconds. This substitution eliminates the time loss associated with human review while maintaining or improving correction quality.
3Reliability
If artificial correction methods are used, then the system is simple and requires no complex infrastructure, but it introduces strong subjectivity and low precision
Solution Approach 1:
The system incorporates feedback mechanisms where the neural network compares its correction predictions against ground truth data during training and can provide feedback loops for continuous improvement. This feedback process enhances reliability by allowing the model to learn from errors and refine its correction accuracy over time.
Solution Approach 2:
The patent utilizes parameter changes in the neural network model (such as adjusting network architecture, training data characteristics, and model parameters) to optimize correction reliability. By carefully selecting and tuning model parameters, the system achieves high precision and reliability while managing processing complexity through efficient model design.
Data Source
AI summary
The disclosure provides an information processing device and method. The information processing device includes a storage module a storage module configured to acquire information data, wherein the information data including at least one key feature and the storage module pre-storing true confidence corresponding to the key feature; an operational circuit configured to determine predicted confidence corresponding to the key feature according to the information data and judge whether the predicted confidence of the key feature exceeds a preset threshold value range of the true confidence corresponding to the key feature or not; a controlling circuit configured to control the storage module to modify the key feature or send out a modification signal to the outside when the predicted confidence exceeds the preset threshold value of the true confidence. The information processing device of the disclosure can automatically correct and modify handwriting, text, image or video actions instead of artificial method.