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September 26, 2025Digital TransformationOpen Access

Neural Network Model for Automated Test Generation for Students in the Moodle System Based on the Analysis of Methodological Materials

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Authors

ККК. С. КурочкаYBY. S. Basharymau

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Overview

System demonstrates effective automated test generation in the Moodle system, highlighting LLM capabilities.

Key Points

  • The study shows the effectiveness of a modular system for generating test materials and reducing labor costs.
  • Test materials were generated using LLMs, demonstrating improved efficiency in monitoring student knowledge.
  • Research included an analysis of methodologies for question generation and quality assessment in educational processes.
  • Implementation highlights the potential of LLMs to adapt and improve automated test generation based on teacher input.

Cite This Study

Курочка et al. (2025) studied this question.

synapsesocial.com/papers/68d6c67db1249cec298b23b9https://doi.org/10.35596/1729-7648-2025-31-3-66-75
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1An Integrated RAG and Agent-Based Architecture for Automated Assessment in Moodle2026
  2. 2Automatic Question & Answer Generation Using Generative Large Language Model (LLM)2025
  3. 3Automated Learning and Scheduling Assistant using LLM2024
  4. 4Review of Natural Language Processing Methods for Automatically Generating Test Tasks2024 · 1 citations
  5. 5LLMs in Automated Assessment: A Role-Based Taxonomy and Framework for Controlled Educational Integration2026