Blockchain/AI (Multi LLM)-based narrative and essay-based automated grading platform

SWAI for Scoring is a blockchain-AI convergence descriptive and essay-type automatic grading platform based on Multi-LLM specialized by subject. It combines a standard rubric-based questioning and grading method based on the achievement standards and core idea evaluation criteria of the 2022 revised curriculum with AI OCR handwriting recognition technology to provide an automated grading environment that can parallel and replace teacher grading. All grading processes and results are recorded on the blockchain to ensure integrity and reliability, and the AI ​​rubric engine provides integrated support for accurate grading, feedback, and analysis functions.

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Features and Benefits

  • Standard rubric-based test creation and grading automation engine

    Operation of an automated grading system based on standard rubrics in accordance with the achievement standards and core idea evaluation criteria of the 2022 revised curriculum.

  • AI OCR-based handwriting digitization processing

    Data purification and evaluation linkage through automatic recognition and digital conversion of handwritten answers

  • Automatic scoring and feedback generation by question type

    Automatic generation of grading basis and feedback comments based on evaluation results

  • Scorer bias and consistency analysis features

    Bias and consistency analysis through comparison of results by grader

  • Ensuring blockchain-based scoring data integrity

    Ensuring data reliability and transparency through blockchain-based records of grading history.

Product Features

  • Standard rubric-based test creation and grading automation

    Automatic application of rubrics and scoring rules for each question based on achievement standards and key idea evaluation criteria.

  • AI OCR-based answer sheet digitization function

    Refinement and processing of grading data through automatic recognition of handwritten answers and text conversion.

  • AI rubric-based automatic grading engine function

    Automated grading and teacher-supplied parallel grading using subject-specific Multi LLMs

  • Ability to generate evaluation result feedback report

    Automatically generate feedback based on grading evidence and provide personalized reports for each learner.

  • Blockchain-based grading history management function

    Ensuring data integrity and reliability through blockchain recording of the grading process and results.

Application Field

  • School Education
    Evaluation Field

    Automated application of performance assessments, essay/descriptive assessments, and subject-specific rubric assessments for middle, high, and university students.

  • Office of Education/Evaluation Agency Scoring System Field

    Establishing a system for standardizing scoring, managing scoring data, and verifying scoring for large-scale tests.

  • Teacher Training and
    Evaluation Feedback Areas

    Strengthening teacher evaluation capabilities and automating feedback using AI-based rubric grading results.

  • Online Learning/AI
    Tutoring Service Field

    Learning support service through automatic grading of learner answers and provision of personalized feedback.

  • Public and Qualification
    Examination Evaluation Field

    Ensuring fairness and reliability of descriptive assessments such as qualification exams and public institution written exams.

Introduction Effect

  • Reduce grading time and improve work efficiency

    AI automatic grading reduces grading time and reduces teacher workload.

  • Ensuring consistency and fairness in grading criteria

    Maintain consistency in assessment criteria through automated grading based on standard rubrics.

  • Ensuring reliability and integrity of scoring results

    Verifying grading history and ensuring reliability through blockchain-based data records.

  • Provide customized feedback to learners

    AI-based analysis to diagnose learner weaknesses and provide individualized feedback.

  • Enhance the usability of evaluation data

    Advancing educational evaluation through statistical and visual analysis of grading results data.

System Configuration Diagram

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You can also contact us by phone (031-972-0409) or email (swempire@swempire.co.kr).

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