Conversational Agents, Virtual Worlds, and Beyond: A Review of Large Language Models Enabling Immersive Learning

Andreas Pester, Ahmed Tammaa, Christian Gütl, Alexander Steinmaurer, Samir Abou El-Seoud

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

Large Language Models represent a significant breakthrough in Natural Language Processing research and opened a wide range of application domains. This paper demonstrates the successful integration of Large Language Models into immersive learning environments. The review highlights how this emerging technology aligns with pedagogical principles, enhancing the effectiveness of current educational systems. It also reflects recent advancements in integrating Large Language Models, including fine-tuning, hallucination reduction, fact-checking, and human evaluation of generated results.

Original languageEnglish
Title of host publicationEDUCON 2024 - IEEE Global Engineering Education Conference, Proceedings
PublisherIEEE Computer Society, 1998
Number of pages6
ISBN (Electronic)9798350394023
DOIs
Publication statusPublished - 2024
Event15th IEEE Global Engineering Education Conference: EDUCON 2024 - Kos Island, Greece
Duration: 8 May 202411 May 2024

Conference

Conference15th IEEE Global Engineering Education Conference
Abbreviated titleEDUCON 2024
Country/TerritoryGreece
CityKos Island
Period8/05/2411/05/24

Keywords

  • education
  • immersive learning
  • Large Language Model
  • LLM
  • metaverse
  • pedagogy
  • survey literature review

ASJC Scopus subject areas

  • Information Systems and Management
  • Education
  • General Engineering

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