AI-driven game design: the EMPAMOS gamification framework

The successful implementation of gamification requires a comprehensive understanding of game design elements, yet existing compilations often lack empirical rigor. Also, while the interplay of individual elements has been considered relevant, there is a lack of methods for combining them. One of the challenges in systematically extracting game design elements is the lack of access to computer game source code. Instead, game design elements are mostly compiled based on subjective experience or literature research. In order to overcome this obstacle, this article uses board game manuals as a new approach. It presents an artificial intelligence (AI)-based analysis of 8,300 board game manuals, identifying 97 detailed game design elements and their interactions as game design molecules. These findings form the EMPAMOS framework, offering precise descriptions of elements and combinations for gamification and game design. Its relevance is demonstrated through a survey and case studies in social work, museum exhibitions, and higher education, showcasing its innovative and practical applicability. The EMPAMOS framework serves as a systematic guideline for gamification and game design in research and practice.

Authors

Institutions

Publication Details

Journal
PeerJ Computer Science
Published
2026-03-11
DOI
https://doi.org/10.7717/peerj-cs.3633
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

AI-driven game design: the EMPAMOS gamification framework

Athanasios Mazarakis, Paula Bräuer, Thomas Voit
PeerJ Computer Science
Educational Games and Gamification
article

AI-driven game design: the EMPAMOS gamification framework

Athanasios Mazarakis, Paula Bräuer, Thomas Voit
article en

Abstract

The successful implementation of gamification requires a comprehensive understanding of game design elements, yet existing compilations often lack empirical rigor. Also, while the interplay of individual elements has been considered relevant, there is a lack of methods for combining them. One of the challenges in systematically extracting game design elements is the lack of access to computer game source code. Instead, game design elements are mostly compiled based on subjective experience or literature research. In order to overcome this obstacle, this article uses board game manuals as a new approach. It presents an artificial intelligence (AI)-based analysis of 8,300 board game manuals, identifying 97 detailed game design elements and their interactions as game design molecules. These findings form the EMPAMOS framework, offering precise descriptions of elements and combinations for gamification and game design. Its relevance is demonstrated through a survey and case studies in social work, museum exhibitions, and higher education, showcasing its innovative and practical applicability. The EMPAMOS framework serves as a systematic guideline for gamification and game design in research and practice.

PeerJ Computer ScienceVol. 12
Christian-Albrechts-Universität zu Kiel (DE), Georg Simon Ohm University of Applied Sciences Nuremberg (DE), Landesamt für Landwirtschaft, Umwelt und ländliche Räume (DE)
Quality Education
Openalex Percentile: Top 29%
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.