Automated Incorrectly-Answered Question Collection via Image Recognition
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Solution Overview
Problem
The existing methods for generating a collection of incorrectly-answered questions are inefficient, requiring students to manually copy these questions, which is time-consuming and burdensome, affecting their study and grades.
Innovation Solution
A method and device that utilize pre-trained region recognition models to identify incorrectly-answered questions on a marked test paper, storing them in a database for automatic collection, including image acquisition, region recognition, marking symbol analysis, and association with student information and knowledge points, allowing for efficient generation of incorrectly-answered question collections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If students manually copy incorrectly-answered questions into notebooks, then the collection of incorrectly-answered questions is created, but the process is time-consuming and reduces study efficiency
Solution Approach 1:
The patent replaces the manual mechanical copying process with an automated image processing system. The system captures images of marked test papers, uses OCR technology to recognize questions and marking symbols, automatically identifies incorrectly-answered questions, and generates digital collections, thereby eliminating the need for manual handwriting and significantly improving efficiency.
Solution Approach 2:
The patent creates digital copies of incorrectly-answered questions from test paper images. Instead of manually transcribing questions into notebooks, the system automatically extracts and stores digital representations of the questions and their marking information in a database, enabling efficient storage, retrieval, and analysis without manual copying effort.
2Ease of operation
If students spend time and energy on handwriting incorrectly-answered questions, then the collection is generated, but students may be unwilling to invest effort, affecting study and grades
Solution Approach 1:
The system performs self-service by automatically completing the entire process of identifying and collecting incorrectly-answered questions without requiring student intervention. The system autonomously captures test paper images, recognizes content, identifies incorrect answers based on marking symbols, and organizes the collection, making the process effortless for students while preserving their study time for more valuable activities.
3Productivity
If automated recognition models are used to identify incorrectly-answered questions, then efficiency is improved, but system complexity increases
Solution Approach 1:
The patent divides the complex automated recognition system into distinct functional modules: an image acquisition module for capturing test paper images, an OCR recognition module for extracting text and marking symbols, an analysis module for identifying incorrect answers, and a collection generation module for organizing results. This segmentation allows each module to be independently optimized and managed, reducing overall system complexity while maintaining high automation efficiency.
Data Source
AI summary
A method and a device for generating a collection of incorrectly-answered questions are provided. The method includes: acquiring an image of a marked test paper (S101); recognizing regions of respective questions in the marked test paper according to a pre-trained first region recognition model (S102); recognizing a question whose marking result is incorrect in the marked test paper as an incorrectly-answered question according to a pre-trained incorrectly-answered question recognition model (S103); and storing the region of the incorrectly-answered question in an incorrectly-answered question database to generate the collection of incorrectly-answered questions (S104). The above solution may solve the problem of low efficiency in generating the collection of incorrectly-answered questions in the prior art.