Assessment Data Analysis Platform with Interactive Dashboards
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Solution Overview
Problem
Educational institutions face challenges in integrating, analyzing, and understanding assessment data from diverse sources to identify strengths, weaknesses, opportunities, and threats related to program effectiveness, as existing software products often lack comprehensive, consistent, and easily understandable insights for strategic planning and decision-making.
Innovation Solution
A platform that integrates and analyzes assessment data from various sources, providing interactive dashboards for data visualization, normalization of scores, and comparison to external criteria, enabling users to generate tickets for continuous quality improvement tasks and track progress, while also correlating learning outcomes with assessment data to identify gaps and inefficiencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual data collection and analysis methods are used, then flexibility in handling diverse assessment data is maintained, but labor intensity increases and error rates rise
Solution Approach 1:
The system enables automated self-service data collection, integration, and analysis through software products that automatically gather assessment data from diverse sources, integrate it using standardized schemas, and generate analytical insights without requiring manual intervention, thereby resolving the contradiction between operational flexibility and analysis efficiency
Solution Approach 2:
The patent replaces manual mechanical data handling processes with automated computational systems that use standardized data schemas, automated integration algorithms, and analytical engines to process assessment data, eliminating labor-intensive manual operations while maintaining flexibility through configurable data models
2Adaptability or versatility
If existing software products are used for assessment data collection, then specific assessment needs are addressed, but comprehensive and consistent data integration is not achieved
Solution Approach 1:
The system implements a universal data integration framework with standardized schemas that can accommodate multiple assessment data sources and types while maintaining consistency across diverse datasets, enabling the software to serve both specific assessment needs and comprehensive data integration requirements simultaneously
Solution Approach 2:
The patent introduces standardized data schemas and integration layers as intermediaries between diverse assessment data sources and the analysis engine, allowing assessment-specific data to be collected with full functionality while ensuring consistent integration and preventing information loss through standardized transformation processes
3Measurement precision
If detailed assessment data is collected from multiple sources, then analysis comprehensiveness improves, but data processing complexity increases
Solution Approach 1:
The system segments the complex data processing task into distinct modular components including data collection modules, integration modules with standardized schemas, analysis modules, and visualization modules, allowing detailed assessment data to be processed comprehensively while managing complexity through modular architecture
Solution Approach 2:
The patent transforms complex multi-source assessment data into standardized parameters and metrics through automated normalization and aggregation processes, maintaining measurement precision by preserving critical data characteristics while reducing processing complexity through parameter standardization
4Productivity
If automated data analysis is implemented, then productivity and consistency improve, but adaptability to diverse data formats decreases
Solution Approach 1:
The system uses parameter-based standardized schemas that can automatically adapt to diverse data formats through configurable transformation rules, enabling automated data analysis to process multiple formats consistently while maintaining productivity through rule-based automation rather than manual adaptation
Data Source
AI summary
A platform is described for analyzing assessment data, including correlating assessment data with learning outcome data, and presenting analysis results through one or more interactive dashboards. A course syllabus and/or other course described information is analyzed to identify expected target outcomes to be achieved by students of the course, and to identify a relative weight of each of the various target outcomes based on their coverage in the syllabus. Assessment data describing a digitally administered assessment is analyzed to identify the categories that are assessed in the various questions of the assessment. The assessment data, including scores on the assessment, can be presented in an interactive dashboard to indicate how well students are performing on assessments with respect to particular learning outcomes, determine question quality, and present other information regarding assessments and/or curriculum effectiveness.