Learning Support System Scoring Table for Descriptive Answers
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Solution Overview
Problem
Existing online learning methods are limited in providing diverse question types, particularly struggling with automatic scoring of descriptive questions, which hinders the identification of weak learning elements and personalized supplementary learning paths for learners.
Innovation Solution
A method and system that acquire learner scores from descriptive answers using a scoring table, determine weak learning elements, and provide tailored supplementary learning paths by analyzing assessment items and associated learning elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic scoring is used for online assessments, then scoring efficiency is improved, but question type diversity is limited to multiple-choice and short-answer formats
Solution Approach 1:
The patent introduces a scoring table as an intermediary tool that bridges automatic scoring systems and descriptive question types. The scoring table provides structured criteria that can be applied to descriptive answers, enabling automated or semi-automated assessment of previously manually-scored question formats.
2Measurement precision
If manual scoring is used for descriptive questions, then assessment accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The patent segments the assessment process into structured criteria within a scoring table, breaking down complex descriptive answer evaluation into manageable, standardized components. This segmentation enables more efficient processing while maintaining assessment quality.
Solution Approach 2:
The patent changes the parameters of assessment by introducing standardized scoring criteria that transform subjective judgment into more objective, measurable parameters. This allows for consistent evaluation across multiple assessors and questions.
3Ease of operation
If conventional assessment methods are used, then implementation simplicity is maintained, but identification of weak learning elements is insufficient
Solution Approach 1:
The patent implements a feedback mechanism where scoring results from the scoring table are used to identify weak learning elements. The system provides feedback to learners about their specific weaknesses, enabling targeted supplementary learning based on assessed performance.
Data Source
AI summary
The present invention relates to a method, system, and non-transitory computer-readable recording medium for supporting learning. According to one aspect of the invention, there is provided a method for supporting learning, the method comprising the steps of: acquiring a learner's score for at least one assessment item included in a scoring table, wherein the learner has solved a question for learning and the scoring table is applied to a descriptive answer of the learner; determining a weak learning element of the learner with reference to the acquired score and at least one learning element associated with the at least one assessment item; and determining a supplementary learning path to be provided to the learner with reference to the determined weak learning element.