Non-Dichotomous Assessment Item Encoding for Data Provenance
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Solution Overview
Problem
Traditional dichotomous assessment items face challenges in storing and processing student responses effectively, leading to data loss and inconsistent processing due to their binary scoring system, which limits the preservation of data provenance and information density.
Innovation Solution
The development of non-dichotomous generative assessment items that store student answers in binary format without delimiters, allowing for concatenation and conversion into vector representations for machine learning, and utilizing blockchain for immutable storage, enhancing data processing and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional dichotomous assessment items are used with binary scoring, then the scoring process is simple, but data provenance is lost and information density is reduced
Solution Approach 1:
The patent segments student responses into individual answer choice selections rather than treating them as a single binary outcome. Each answer choice is encoded separately, preserving the provenance of each selection while enabling detailed analysis of response patterns without requiring complex storage structures
Solution Approach 2:
The patent changes the parameter representation from binary (correct/incorrect) to multi-state encoding where each answer choice can be independently tracked. This parameter transformation preserves information about which specific choices were selected while maintaining efficient storage through structured encoding schemes
2Loss of information
If multiple dichotomous items are administered to increase information density, then more information is collected, but the time required for assessment increases
Solution Approach 1:
The patent merges multiple assessment functions into a single non-dichotomous item by allowing students to select multiple answer choices within one question. This consolidation collects information about multiple concepts and reasoning paths in a single assessment event, increasing information density while reducing assessment time
Solution Approach 2:
The patent adds a dimension to assessment by transitioning from single-answer to multi-answer format. This dimensional change enables the collection of richer data about student understanding, including partial knowledge and reasoning patterns, without requiring additional assessment items or time
3Ease of operation
If student responses are stored with delimiters for easy processing, then data readability is improved, but storage efficiency decreases
Solution Approach 1:
The patent extracts the delimiter characters from the data representation and replaces them with structured encoding schemes. By removing unnecessary delimiters and using compact binary or numerical encodings for answer choices, the system maintains ease of processing through programmatic parsing while significantly reducing storage requirements
Data Source
AI summary
Disclosed herein are system and method for generative assessment item development, encoding & analysis, wherein the generative assessment item includes a question and a plurality of possible responses to the question, the plurality of possible responses comprising at least two responses that are not independent, and wherein the plurality of responses are non-dichotomous.