Dynamic Assessment Generation via Concept Extraction
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Solution Overview
Problem
Static user assessment systems are outdated in rapidly changing fields like science, technology, and artificial intelligence, as they take days to create assessments and fail to incorporate recent information, leading to inaccurate and irrelevant evaluations.
Innovation Solution
A dynamic assessment system that automatically crawls and parses data to generate up-to-date assessments by identifying concepts and creating questions tailored to various expertise levels, using techniques like selective crawling, deep machine learning, and natural language processing to create a knowledge base and assessment questions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static user assessment systems are used, then assessment creation is simple and manual, but the assessments become outdated quickly in rapidly changing fields
Solution Approach 1:
The system enables automatic self-service assessment generation by crawling data sources, extracting concepts, and creating assessments without human intervention. The computer-implemented system autonomously performs data gathering, concept extraction, question generation, and assessment assembly, eliminating the need for manual assessment creation while ensuring assessments remain current with rapidly changing information in specialized fields.
Solution Approach 2:
The patent replaces the mechanical manual process of assessment creation with an automated computer-based system. Instead of human experts manually writing and updating assessments, the system uses automated data crawling, natural language processing, and concept extraction algorithms to generate assessments dynamically, substituting human labor with computational processes that can operate continuously and update assessments in real-time.
2Productivity
If manual assessment creation is used, then control over content is high, but the rate of updating assessments is very slow
Solution Approach 1:
The system performs self-service by automatically executing the complete assessment generation workflow including data crawling from specified sources, concept extraction using natural language processing, question generation based on extracted concepts, and assessment assembly. This autonomous operation enables rapid updates without human intervention, dramatically increasing the assessment update rate while the system manages its own complexity through automated processes.
Solution Approach 2:
The system extracts only the essential elements needed for assessment creation from data sources - specifically crawling for relevant information, extracting key concepts and entities, and pulling out sufficient data to generate questions. This selective extraction approach enables rapid assessment updates by focusing computational resources on extracting only the necessary information rather than processing entire data sources, thereby increasing productivity while managing system complexity.
3Reliability
If assessments are updated frequently to reflect latest information, then relevance improves, but resource consumption increases
Solution Approach 1:
The system extracts only the essential concepts and information needed for assessment generation from crawled data, rather than processing and storing all retrieved information. By extracting only relevant concepts, entities, and question-worthy information, the system maintains assessment relevance through frequent updates while minimizing computational resource consumption by avoiding unnecessary data processing and storage of redundant information.
Solution Approach 2:
The system performs partial action by selectively crawling and processing only portions of data sources that are most relevant to current assessment needs, rather than comprehensively processing all available information. This approach allows the system to update assessments frequently with relevant information while consuming fewer computational resources by focusing processing effort on high-priority data sources and concepts.
Data Source
AI summary
A method, a computer program product, and a computer system for generating and rating assessments is disclosed. Exemplary embodiments include gathering data relating to one or more specialized subject areas and generating a knowledge base based on extracting one or more concepts from the data. Exemplary embodiments further include generating one or more questions and one or more corresponding answer keys relating to the one or more concepts, as well as generating an assessment related to the one or more concepts based on the one or more questions and one or more answer keys.