Gamifying Human-AI Interaction: Using Large Language Models for Enhanced Engagement and Learning

Carlos J. Costa, Manuela Aparício, João Tiago Aparício

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

Abstract

This study investigates the synergy between gamification and large language models (LLMs) with human-AI interaction. Motivated by the need to enhance user engagement and learning outcomes, the research addresses how gamification principles can improve the design of LLM-powered systems. This work proposes a framework integrating game mechanics such as narrative-driven interactions, adaptive challenges, personalized feedback, and collaborative problem-solving into LLM applications. Using a mixed-method approach combining conceptual analysis and software prototyping, we illustrate how gamified LLMs enhance motivation, foster trust, and improve performance in diverse contexts, including education, research, and therapy. The findings accentuate the transformative potential of gamification in human-AI collaboration, with implications for designing more intuitive and effective systems.
Original languageEnglish
Title of host publicationIEEE ICHMS 2025
Subtitle of host publication5th IEEE International Conference on Human-Machine Systems
PublisherIEEE Press
Pages325-331
Number of pages7
ISBN (Electronic)979-8-3315-2164-6
DOIs
Publication statusPublished - 2025
Event5th IEEE International Conference on Human-Machine Systems - Marriott Downtown Abu Dhabi, Abu Dhabi, United Arab Emirates
Duration: 26 May 202528 May 2025
Conference number: 5
https://ieee-ichms.org/2025/index.html

Conference

Conference5th IEEE International Conference on Human-Machine Systems
Abbreviated titleIEEE ICHMS 2025
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period26/05/2528/05/25
Internet address

Keywords

  • gamification
  • LLM
  • Human-AI interaction
  • Artificial Intelligence
  • framework

Cite this