This paper presents a planned project to develop and implement an innovative system for generating training materials using open source Large Language Models (LLMs). The aim is to automate and optimize the creation and updating of training materials in technology-intensive industries. Against the background of rapid technological change and the increasing demand for specific and timely training methods, our project aims to create teaching materials efficiently, precisely and in line with demand. The project explores the integration of generative artificial intelligence in the form of open source language models. The aim is to provide individually tailored training content that can be flexibly adapted to different educational levels and learning styles. The methodology of the project is based on the application of design science research. Open source models are used to generate content, which is supplemented by a user-centered interface.

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DITACT - Digital Twin for Automated, Customized Training Documents Generation

  • Ute Dietrich,
  • Dorian Zwanzig

摘要

This paper presents a planned project to develop and implement an innovative system for generating training materials using open source Large Language Models (LLMs). The aim is to automate and optimize the creation and updating of training materials in technology-intensive industries. Against the background of rapid technological change and the increasing demand for specific and timely training methods, our project aims to create teaching materials efficiently, precisely and in line with demand. The project explores the integration of generative artificial intelligence in the form of open source language models. The aim is to provide individually tailored training content that can be flexibly adapted to different educational levels and learning styles. The methodology of the project is based on the application of design science research. Open source models are used to generate content, which is supplemented by a user-centered interface.