Computer Learning Model for Continuous Assessment and Feedback
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Solution Overview
Problem
Current learning techniques fail to effectively assess students' understanding of concepts during their learning journey, often only providing feedback at the endpoint, which may not reflect the student's true understanding, and do not offer real-time guidance to correct misconceptions or identify gaps in knowledge.
Innovation Solution
A computer-implemented method that analyzes a student's descriptive understanding and provides interactive learning materials, allowing for continuous assessment and feedback throughout the learning process, identifying gaps and adjusting the learning trajectory to ensure proficiency in specific knowledge areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional endpoint assessment methods are used, then the learning evaluation is simple to implement, but the measurement precision of student understanding is insufficient
Solution Approach 1:
The patent segments the learning assessment process into multiple intermediate evaluation points along the learning trajectory, rather than relying on a single endpoint assessment. This allows for continuous monitoring of student understanding and identification of gaps in knowledge development.
Solution Approach 2:
The patent implements continuous feedback mechanisms that provide real-time information about student understanding throughout the learning journey. This feedback loop enables dynamic adjustment of learning paths and interventions based on assessed proficiency levels.
2Reliability
If continuous interactive assessment is implemented, then the learning guidance is improved, but the loss of time for processing feedback increases
Solution Approach 1:
The patent pre-establishes proficiency thresholds and learning trajectories before the learning process begins. This allows for automated comparison of student performance against predetermined standards, reducing the time required for real-time feedback processing.
Solution Approach 2:
The system enables students to self-assess their understanding against provided criteria and thresholds, reducing the burden on instructors for continuous evaluation while maintaining assessment quality.
3Measurement precision
If descriptive understanding analysis is used, then the identification of learning gaps is improved, but the difficulty of detecting and measuring student comprehension increases
Solution Approach 1:
The patent transforms qualitative descriptive understanding into quantifiable parameters by comparing student responses against predefined proficiency thresholds. This conversion enables automated analysis while maintaining the nuance of descriptive assessment.
Data Source
AI summary
A learning model is created using a computer which includes receiving input from a user. The learning model includes comparing the input to the knowledge area in a knowledge database to assess a level of proficiency on topics within the knowledge area. The learning model includes determining topics of knowledge within the knowledge area where a user currently meets a proficiency threshold for one or more topics. A work topic is identified within the knowledge area where the user does not meet the proficiency threshold. Study material is presented to the user for the work topic of the knowledge area using an interactive mechanism. Feedback is received regarding the study material for the work topic from the interactive mechanism from the user. The learning model includes evaluating the feedback from the user to determine a score which indicates when the user meets a proficiency threshold for the work topic.