CrossRef Open Access 2026

AI-driven game design: the EMPAMOS gamification framework

Thomas Voit Athanasios Mazarakis Paula Bräuer

Abstrak

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.

Penulis (3)

T

Thomas Voit

A

Athanasios Mazarakis

P

Paula Bräuer

Format Sitasi

Voit, T., Mazarakis, A., Bräuer, P. (2026). AI-driven game design: the EMPAMOS gamification framework. https://doi.org/10.7717/peerj-cs.3633

Akses Cepat

Lihat di Sumber doi.org/10.7717/peerj-cs.3633
Informasi Jurnal
Tahun Terbit
2026
Bahasa
en
Sumber Database
CrossRef
DOI
10.7717/peerj-cs.3633
Akses
Open Access ✓