Ancient Greek Technology: An Immersive Learning Use Case Described Using a Co-Intelligent Custom ChatGPT Assistant
Project Overview
The document explores the integration of generative AI, particularly a custom ChatGPT assistant, within the realm of immersive learning, exemplified through a case study on ancient Greek technology in VRChat. It employs the Immersive Learning Case Sheet (ILCS) method to standardize case descriptions, thereby improving comparability and the quality of research in educational contexts. Key findings indicate that the use of AI significantly enhances the coherence and quality of documentation, facilitating a more effective learning experience. However, challenges persist, such as the dependency on AI for interpretive tasks and the diverse levels of expertise among team members, which can affect the overall effectiveness of the integration. The document underscores the potential of generative AI to transform educational practices while also addressing the need for careful implementation to mitigate reliance on technology and ensure equitable engagement among participants.
Key Applications
Immersive Learning Case Sheet (ILCS) Assistant, a custom ChatGPT tool
Context: Higher Education students learning about ancient Greek technology using VRChat
Implementation: The ILCS Assistant was developed to help document and analyze immersive learning cases by prompting for details, checking compliance with frameworks, and suggesting terminology.
Outcomes: Enhanced clarity and consistency in case descriptions, improved research quality, and facilitated real-time suggestions for documentation.
Challenges: Reliance on AI for interpretive tasks and managing varying levels of expertise within the research team.
Implementation Barriers
Technical Barrier
The ILCS Assistant sometimes deviated from the established frameworks' terminology and reporting formats, leading to potential inaccuracies.
Proposed Solutions: Research teams should verify compliance and accuracy of the AI's suggestions and engage critically with the tool to ensure adherence to standards.
Expertise Barrier
Different levels of familiarity with the ILCS and the case content among team members caused inconsistencies.
Proposed Solutions: Training and familiarization sessions to ensure all team members have a baseline understanding of the ILCS and its application.
Project Team
Vlasis Kasapakis
Researcher
Leonel Morgado
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Vlasis Kasapakis, Leonel Morgado
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai