AI NPCs in an Educational Metaverse: Evaluating the Effectiveness of Prompt Templates for Contextual Interactions

Wilkinson Daniel Wong GONZALES*, Daniel Jiandong SHEN, Aihua YAN, Nina XIE, Maria Leonora FRANCISCO, Paulina Pui Yun WONG

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Referred Conference Paperpeer-review

Abstract

The purpose of this study was to evaluate the effectiveness and relevance of AI-powered non-player characters (NPCs) in educational settings within the metaverse platform Classlet, particularly within the domain of applied social sciences. Integrating Speech Act Theory, Prospect Theory, and the Recognition-Primed Decision Model into AI prompt templates enhanced interactions and positively impacted student engagement. The AI NPCs achieved a performance ratio of 128%, providing contextually relevant responses effectively maintained by the prompt templates. A survey on students’ perceptions of the AI and VR integration revealed positive user perceptions, with strong correlations between enjoyment, perceived usefulness, and intent to use. Correlational analysis showed a strong fit (R2 = 0.816) for user intent, which had a mean of 74%. U-tests also indicated that female and non-VR users encountered more technical difficulties. Overall, the results suggest new ways of using AI and VR to promote learning engagement and interactions within applied social sciences.
Original languageEnglish
Title of host publicationInnovating Education with AI : AETS 2024
EditorsEric C. K. CHENG
PublisherSpringer Singapore
Chapter4
Pages53-74
Number of pages22
ISBN (Electronic)9789819649525
ISBN (Print)9789819649518
DOIs
Publication statusPublished - 16 Apr 2025

Publication series

NameLecture Notes in Educational Technology
PublisherSpringer
VolumePart F312
ISSN (Print)2196-4963
ISSN (Electronic)2196-4971

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

Funding

Lingnan University, Hong Kong (Teaching Development Grant, Project Code: 102716; Fund for Innovative Technology-in-Education (FITE) by the University Grants Committee (Project Code: 120042).

Keywords

  • Adaptive Learning Environments
  • AI Educational Agents
  • AI in Education

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