Asynchronous Oral Assessment With AI Rubric-Based Evaluation
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Solution Overview
Problem
Oral assessments are resource-intensive and impractical for large-scale applications due to their traditional one-on-one nature, limiting their use in settings beyond small classrooms.
Innovation Solution
An asynchronous oral assessment system using a structured web-based platform that automatically delivers questions, records verbal responses, and provides automated evaluation tools for scalable and versatile assessment across diverse domains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional one-on-one oral assessments are used, then assessment quality and authenticity are improved, but resource consumption and implementation complexity increase
Solution Approach 1:
The system creates a digital copy of the oral assessment process through automated video recording and AI analysis. Instead of requiring human assessors to manually evaluate each student, the system captures video responses and uses AI to generate transcripts and analyze communication metrics, creating a scalable copy of the assessment process that maintains authenticity while reducing resource consumption.
Solution Approach 2:
The system introduces an AI intermediary that mediates between the student's oral response and the assessment evaluation. The AI engine processes video recordings, generates transcripts, extracts communication metrics, and provides structured feedback, acting as an intermediary that preserves the authenticity of oral assessment while eliminating the need for extensive human resources.
2Measurement precision
If traditional one-on-one oral assessments are used, then in-depth knowledge assessment is improved, but scalability and productivity deteriorate
Solution Approach 1:
The system enables self-service oral assessment where students independently record their responses using the web platform without requiring synchronous instructor presence. The AI engine then automatically processes these recordings, generating transcripts and analysis, allowing students to complete assessments at their own pace while maintaining the depth of knowledge evaluation.
Solution Approach 2:
The system performs preliminary actions by pre-configuring assessment rubrics, communication metrics frameworks, and AI analysis parameters before assessments begin. This preliminary setup enables the system to automatically evaluate numerous assessments without requiring real-time human intervention for each evaluation, thereby improving scalability while maintaining assessment depth.
3Productivity
If automated evaluation tools are added, then assessment efficiency and objectivity are improved, but system complexity increases
Solution Approach 1:
The system achieves multi-functionality by integrating multiple assessment capabilities into a single unified platform. The web-based system simultaneously handles video recording, transcript generation, communication metric extraction, rubric-based evaluation, and feedback delivery, eliminating the need for separate tools and reducing overall system complexity despite the advanced functionalities provided.
Data Source
AI summary
A system may include a web server to receive an input associated with a first user, where the input includes an assessment question and associates the assessment question with a rubric, where the rubric includes a set of criteria, where each criterion of the set of criteria includes a description and a scale with a set of scale values. The system may further include a media server to receive an audiovisual input associated with a second user. The web server may be further configured to generate an evaluation tool accessible by the first user, where the audiovisual recording is embedded in the evaluation tool, and where the evaluation tool further includes a transcript of the audiovisual recording, an analysis of communication metrics associated with the audiovisual recording, and the rubric. The media server may also enable streaming of the audiovisual recording embedded in the evaluation tool.