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

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.

Authors

Institutions

Publication Details

Published
2025-05-26
DOI
https://doi.org/10.1109/ichms65439.2025.11154284
Primary Topic
Educational Games and Gamification
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

João Tiago Aparício, Manuela Aparício, Carlos J. Costa
Educational Games and Gamification
article

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

João Tiago Aparício, Manuela Aparício, Carlos J. Costa
article en

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.

University of Lisbon (PT), Universidade Politécnica de Lisboa (PT), Universidade Nova de Lisboa (PT)
Openalex Percentile: Top 73%
Educational Games and Gamification
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.