Automated Question Generation from Training Material
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Solution Overview
Problem
The education system faces limitations in conducting frequent and flexible assessments due to manual examination processes and challenges in maintaining question quality and difficulty levels in e-learning systems.
Innovation Solution
A system and method for active user assessment that involves obtaining training material, classifying it, applying content-to-text construction techniques, performing semantic analysis to generate questions, and presenting a test script with correct and incorrect answers to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual examination processes are used, then question quality and difficulty level can be maintained through lecturer expertise, but the frequency and flexibility of assessments are restricted
Solution Approach 1:
The system enables self-service by automatically generating assessment questions from training material without requiring manual lecturer intervention. The automated question generation system processes training content and produces test questions independently, allowing frequent assessments while maintaining consistent quality through algorithmic rather than manual processes.
Solution Approach 2:
The patent replaces the mechanical manual process of question creation with an automated computational system. Instead of lecturers manually crafting questions, the system uses automated text processing and question generation algorithms to create assessments, thereby increasing productivity while maintaining quality through systematic rather than subjective processes.
2Reliability
If lecturers manually create and manage questions, then question difficulty and quality can be controlled, but the flexibility to adapt questions is limited
Solution Approach 1:
The system introduces dynamics by allowing question parameters such as difficulty and relevance to be adjusted based on analysis of the training material. The automated system can dynamically generate questions with varying difficulty levels and adapt to different training contents, providing both reliability through controlled generation and flexibility through adaptive parameters.
Solution Approach 2:
The patent applies parameter changes by modifying question characteristics such as difficulty level, topic relevance, and question type based on the analyzed training material. The system can generate questions with different parameters automatically, enabling flexible adaptation to various training scenarios while maintaining quality through systematic parameter control.
3Productivity
If frequent exams are conducted to improve learning efficiency, then learning speed increases, but the manual process becomes unsustainable
Solution Approach 1:
The system resolves the complexity issue by implementing self-service automation. The automated question generation and assessment delivery system handles the entire examination process without requiring proportional manual effort for each exam, making frequent assessments sustainable while maintaining high learning efficiency.
Data Source
AI summary
Systems and methods for conducting an active assessment of students based on the training material uploaded by a lecturer. A training database obtains the training material which is classified based on a content type by the data classifier. According to the content type, a content to text constructor applies different techniques to convert the content into text. The text is analyzed by the text analyzer. The text analyzer includes a semantic analyzer to perform semantic analysis on the text, a question generator to generate a set of questions based on the semantic analysis and select most relevant questions from the set, and an answer generator module to generate at least one correct answer and multiple incorrect answers for each question. The test script is generated including the questions and answers. Based on the selection of the answer, an assessment of the student is performed.