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Natural Language Processing for Quality Assurance for Constructed-Response Tests

Altus Assessments, 2022 2022-08-28

Overview

Developed novel architectures for automating the audit and validation of high-stakes textual assessments using Natural Language Processing (NLP). This innovation addressed the challenge of maintaining quality and fairness in large-scale constructed-response tests.

Key Technologies

  • Natural Language Processing (NLP)
  • Machine Learning
  • Automated Auditing Algorithms

Impact

  • Improved the validity and reliability of high-stakes assessments.
  • Reduced the manual workload for quality assurance.
  • Enhanced fairness and equity in testing processes.